From 0072964040b5c5894c6b0569b7de82fd2bf1a83b Mon Sep 17 00:00:00 2001
From: m7pr <marcin.kosinski.mk1@roche.com>
Date: Mon, 19 Feb 2024 10:24:01 +0100
Subject: [PATCH 01/62] initial DESCRIPTION curation

---
 DESCRIPTION | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/DESCRIPTION b/DESCRIPTION
index 06a086873..d4e009640 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,6 +1,6 @@
 Type: Package
 Package: teal.modules.general
-Title: General Modules to Add to a `teal` Application
+Title: General Modules to Add to a 'teal' Application
 Version: 0.2.16.9021
 Date: 2024-02-15
 Authors@R: c(
@@ -13,8 +13,8 @@ Authors@R: c(
     person("Nikolas", "Burkoff", role = "aut"),
     person("F. Hoffmann-La Roche AG", role = c("cph", "fnd"))
   )
-Description: General Purpose Teal Modules.
-License: Apache License 2.0 | file LICENSE
+Description: General Purpose 'teal' Modules.
+License: Apache License 2.0
 URL: https://insightsengineering.github.io/teal.modules.general/,
     https://github.com/insightsengineering/teal.modules.general/
 BugReports: 

From e5813a9c57d556f580d9773287642e8a5096a38e Mon Sep 17 00:00:00 2001
From: m7pr <marcin.kosinski.mk1@roche.com>
Date: Mon, 19 Feb 2024 12:36:35 +0100
Subject: [PATCH 02/62] change DESCRIPTION's Title and Description fields

---
 DESCRIPTION | 6 ++++--
 1 file changed, 4 insertions(+), 2 deletions(-)

diff --git a/DESCRIPTION b/DESCRIPTION
index d4e009640..1fbcf057f 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,6 +1,6 @@
 Type: Package
 Package: teal.modules.general
-Title: General Modules to Add to a 'teal' Application
+Title: General Modules for 'teal' Applications
 Version: 0.2.16.9021
 Date: 2024-02-15
 Authors@R: c(
@@ -13,7 +13,9 @@ Authors@R: c(
     person("Nikolas", "Burkoff", role = "aut"),
     person("F. Hoffmann-La Roche AG", role = c("cph", "fnd"))
   )
-Description: General Purpose 'teal' Modules.
+Description: Prebuilt 'shiny' modules containing tools for viewing data, visualizing data,
+    understanding missing and outlier values within your data and performing simple data analysis. 
+    This extends 'teal' framework that supports reproducible research and analysis.
 License: Apache License 2.0
 URL: https://insightsengineering.github.io/teal.modules.general/,
     https://github.com/insightsengineering/teal.modules.general/

From 72164f7516a69d8d9f30ddd26b5c043e94c8907f Mon Sep 17 00:00:00 2001
From: m7pr <marcin.kosinski.mk1@roche.com>
Date: Mon, 19 Feb 2024 12:41:01 +0100
Subject: [PATCH 03/62] revisit README file

---
 README.md | 29 ++++++++++++++++++++++++-----
 1 file changed, 24 insertions(+), 5 deletions(-)

diff --git a/README.md b/README.md
index 3c9b1fffb..ef66a1ece 100644
--- a/README.md
+++ b/README.md
@@ -1,6 +1,11 @@
 # teal.modules.general
 
 <!-- start badges -->
+[![CRAN Version](https://www.r-pkg.org/badges/version/teal.modules.general?color=green)](https://cran.r-project.org/package=teal.modules.general)
+[![Total Downloads](http://cranlogs.r-pkg.org/badges/grand-total/teal.modules.general?color=green)](https://cran.r-project.org/package=teal.modules.general)
+[![Last Month Downloads](http://cranlogs.r-pkg.org/badges/last-month/teal.modules.general?color=green)](https://cran.r-project.org/package=teal.modules.general)
+[![Last Week Downloads](http://cranlogs.r-pkg.org/badges/last-week/teal.modules.general?color=green)](https://cran.r-project.org/package=teal.modules.general)
+
 [![Check 🛠](https://github.com/insightsengineering/teal.modules.general/actions/workflows/check.yaml/badge.svg)](https://insightsengineering.github.io/teal.modules.general/main/unit-test-report/)
 [![Docs 📚](https://github.com/insightsengineering/teal.modules.general/actions/workflows/docs.yaml/badge.svg)](https://insightsengineering.github.io/teal.modules.general/)
 [![Code Coverage 📔](https://raw.githubusercontent.com/insightsengineering/teal.modules.general/_xml_coverage_reports/data/main/badge.svg)](https://insightsengineering.github.io/teal.modules.general/main/coverage-report/)
@@ -35,17 +40,31 @@ Please see [`teal` gallery](https://github.com/insightsengineering/teal.gallery)
 
 ## Installation
 
-From July 2023 `insightsengineering` packages are available on [r-universe](https://r-universe.dev/).
-
 ```r
 # stable versions
-install.packages('teal.modules.general', repos = c('https://insightsengineering.r-universe.dev', 'https://cloud.r-project.org'))
+install.packages('teal.modules.general')
+
+# install.packages("pak")
+pak::pak("insightsengineering/teal.modules.general@*release")
+```
+
+Alternatively, you might want to use the development version available on [r-universe](https://r-universe.dev/).
 
+```r
 # beta versions
-install.packages('teal.modules.general', repos = c('https://pharmaverse.r-universe.dev', 'https://cloud.r-project.org'))
+install.packages('teal.modules.general', repos = c('https://pharmaverse.r-universe.dev', getOption('repos')))
+
+# install.packages("pak")
+pak::pak("insightsengineering/teal.modules.general")
 ```
 
-See package vignettes `browseVignettes(package = "teal.modules.general")` for usage of this package.
+## Usage
+
+See package vignettes `browseVignettes(package = "teal.modules.general")` for usage of this package or visit [Package Website](https://insightsengineering.github.io/teal.modules.general/latest-tag/).
+
+## Getting help
+
+If you encounter a bug or have a feature request, please file an issue. For questions, discussions, and staying up to date, please use the `teal` channel in the [`pharmaverse` slack workspace](https://pharmaverse.slack.com).
 
 ## Acknowledgment
 

From 549b0fa0aa9fd951f5453e7560b10ab197ec1784 Mon Sep 17 00:00:00 2001
From: m7pr <marcin.kosinski.mk1@roche.com>
Date: Mon, 19 Feb 2024 12:44:09 +0100
Subject: [PATCH 04/62] change Teal to `teal`

---
 R/tm_data_table.R                      | 2 +-
 R/tm_file_viewer.R                     | 2 +-
 man/tm_data_table.Rd                   | 2 +-
 man/tm_file_viewer.Rd                  | 2 +-
 vignettes/using-association-plot.Rmd   | 2 +-
 vignettes/using-bivariate-plot.Rmd     | 2 +-
 vignettes/using-cross-table.Rmd        | 2 +-
 vignettes/using-data-table.Rmd         | 2 +-
 vignettes/using-outliers-module.Rmd    | 2 +-
 vignettes/using-regression-plots.Rmd   | 2 +-
 vignettes/using-response-plot.Rmd      | 2 +-
 vignettes/using-scatterplot-matrix.Rmd | 2 +-
 vignettes/using-scatterplot.Rmd        | 2 +-
 13 files changed, 13 insertions(+), 13 deletions(-)

diff --git a/R/tm_data_table.R b/R/tm_data_table.R
index 29adb0212..5a0c15b13 100644
--- a/R/tm_data_table.R
+++ b/R/tm_data_table.R
@@ -1,4 +1,4 @@
-#' Data Table Viewer Teal Module
+#' Data Table Viewer `teal` Module
 #'
 #' A data table viewer shows the data using a paginated table.
 #' specifically designed for use with `data.frames`.
diff --git a/R/tm_file_viewer.R b/R/tm_file_viewer.R
index deb5632a0..7a3ae61ff 100644
--- a/R/tm_file_viewer.R
+++ b/R/tm_file_viewer.R
@@ -1,4 +1,4 @@
-#' File Viewer Teal Module
+#' File Viewer `teal` Module
 #'
 #' The file viewer module provides a tool to view static files.
 #' Supported formats include text formats, \code{PDF}, \code{PNG}, \code{APNG},
diff --git a/man/tm_data_table.Rd b/man/tm_data_table.Rd
index bec8cde63..a20dd8750 100644
--- a/man/tm_data_table.Rd
+++ b/man/tm_data_table.Rd
@@ -2,7 +2,7 @@
 % Please edit documentation in R/tm_data_table.R
 \name{tm_data_table}
 \alias{tm_data_table}
-\title{Data Table Viewer Teal Module}
+\title{Data Table Viewer \code{teal} Module}
 \usage{
 tm_data_table(
   label = "Data Table",
diff --git a/man/tm_file_viewer.Rd b/man/tm_file_viewer.Rd
index a1be536fb..ace7d9e6d 100644
--- a/man/tm_file_viewer.Rd
+++ b/man/tm_file_viewer.Rd
@@ -2,7 +2,7 @@
 % Please edit documentation in R/tm_file_viewer.R
 \name{tm_file_viewer}
 \alias{tm_file_viewer}
-\title{File Viewer Teal Module}
+\title{File Viewer \code{teal} Module}
 \usage{
 tm_file_viewer(
   label = "File Viewer Module",
diff --git a/vignettes/using-association-plot.Rmd b/vignettes/using-association-plot.Rmd
index 8921c79d1..238d672e9 100644
--- a/vignettes/using-association-plot.Rmd
+++ b/vignettes/using-association-plot.Rmd
@@ -10,7 +10,7 @@ vignette: >
   %\VignetteEncoding{UTF-8}
 ---
 
-# Teal application to use association plot with various datasets types
+# `teal` application to use association plot with various datasets types
 
 This vignette will guide you through 4 parts to create a teal application using
 various types of datasets inside an association plot module:
diff --git a/vignettes/using-bivariate-plot.Rmd b/vignettes/using-bivariate-plot.Rmd
index ed09e6c78..509cd1b3e 100644
--- a/vignettes/using-bivariate-plot.Rmd
+++ b/vignettes/using-bivariate-plot.Rmd
@@ -10,7 +10,7 @@ vignette: >
   %\VignetteEncoding{UTF-8}
 ---
 
-# Teal application to use bivariate plot with various datasets types
+# `teal` application to use bivariate plot with various datasets types
 
 This vignette will guide you through 4 parts to create a teal application using
 various types of datasets inside an bivariate plot module:
diff --git a/vignettes/using-cross-table.Rmd b/vignettes/using-cross-table.Rmd
index 2ab93bd9a..34258cca6 100644
--- a/vignettes/using-cross-table.Rmd
+++ b/vignettes/using-cross-table.Rmd
@@ -10,7 +10,7 @@ vignette: >
   %\VignetteEncoding{UTF-8}
 ---
 
-# Teal application to use cross table with various datasets types
+# `teal` application to use cross table with various datasets types
 
 This vignette will guide you through 4 parts to create a teal application using
 various types of datasets inside an cross table module:
diff --git a/vignettes/using-data-table.Rmd b/vignettes/using-data-table.Rmd
index 77b8d4eb7..35e2ea7a4 100644
--- a/vignettes/using-data-table.Rmd
+++ b/vignettes/using-data-table.Rmd
@@ -10,7 +10,7 @@ vignette: >
   %\VignetteEncoding{UTF-8}
 ---
 
-# Teal application to use association plot with various datasets types
+# `teal` application to use association plot with various datasets types
 
 This vignette will guide you through 4 parts to create a teal application using
 various types of datasets inside a data table module:
diff --git a/vignettes/using-outliers-module.Rmd b/vignettes/using-outliers-module.Rmd
index be6c2325f..b9ea35f7e 100644
--- a/vignettes/using-outliers-module.Rmd
+++ b/vignettes/using-outliers-module.Rmd
@@ -10,7 +10,7 @@ vignette: >
   %\VignetteEncoding{UTF-8}
 ---
 
-# Teal application to analyze and report outliers with various datasets types.
+# `teal` application to analyze and report outliers with various datasets types.
 
 This vignette will guide you through 4 parts to create a teal application using
 various types of datasets inside the outliers module:
diff --git a/vignettes/using-regression-plots.Rmd b/vignettes/using-regression-plots.Rmd
index c409775a3..636d6d974 100644
--- a/vignettes/using-regression-plots.Rmd
+++ b/vignettes/using-regression-plots.Rmd
@@ -11,7 +11,7 @@ vignette: >
 ---
 
 
-# Teal application to use regression plot with various datasets types
+# `teal` application to use regression plot with various datasets types
 
 This vignette will guide you through 4 parts to create a teal application using
 various types of datasets inside an regression plot module:
diff --git a/vignettes/using-response-plot.Rmd b/vignettes/using-response-plot.Rmd
index b60f74387..47eedbbac 100644
--- a/vignettes/using-response-plot.Rmd
+++ b/vignettes/using-response-plot.Rmd
@@ -10,7 +10,7 @@ vignette: >
   %\VignetteEncoding{UTF-8}
 ---
 
-# Teal application to use response plot with various datasets types
+# `teal` application to use response plot with various datasets types
 
 This vignette will guide you through 4 parts to create a teal application using
 various types of datasets inside an response plot module:
diff --git a/vignettes/using-scatterplot-matrix.Rmd b/vignettes/using-scatterplot-matrix.Rmd
index 41fa0aeeb..7ea3ab2c0 100644
--- a/vignettes/using-scatterplot-matrix.Rmd
+++ b/vignettes/using-scatterplot-matrix.Rmd
@@ -11,7 +11,7 @@ vignette: >
 ---
 
 
-# Teal application to use scatter plot matrix with various datasets types
+# `teal` application to use scatter plot matrix with various datasets types
 
 This vignette will guide you through 4 parts to create a teal application using
 various types of datasets inside an scatter plot matrix module:
diff --git a/vignettes/using-scatterplot.Rmd b/vignettes/using-scatterplot.Rmd
index 805a360e3..84f1de4d0 100644
--- a/vignettes/using-scatterplot.Rmd
+++ b/vignettes/using-scatterplot.Rmd
@@ -11,7 +11,7 @@ vignette: >
 ---
 
 
-# Teal application to use scatter plot with various datasets types
+# `teal` application to use scatter plot with various datasets types
 
 This vignette will guide you through 4 parts to create a teal application using
 various types of datasets inside an scatter plot module:

From b3845f087b02de6f50aaf0ace66f922ca5bcd94e Mon Sep 17 00:00:00 2001
From: m7pr <marcin.kosinski.mk1@roche.com>
Date: Mon, 19 Feb 2024 13:10:16 +0100
Subject: [PATCH 05/62] check /main/ to /latest-tag/ in workflows files

---
 .github/CONTRIBUTING.md                 | 4 ++--
 .github/ISSUE_TEMPLATE/cran-release.yml | 2 +-
 .github/ISSUE_TEMPLATE/release.yml      | 2 +-
 .github/workflows/check.yaml            | 2 +-
 .github/workflows/release.yaml          | 2 +-
 5 files changed, 6 insertions(+), 6 deletions(-)

diff --git a/.github/CONTRIBUTING.md b/.github/CONTRIBUTING.md
index 31cb149c9..139e12af1 100644
--- a/.github/CONTRIBUTING.md
+++ b/.github/CONTRIBUTING.md
@@ -131,6 +131,6 @@ If you have further questions regarding the contribution guidelines, please cont
 
 <!-- urls -->
 [docs]: https://insightsengineering.github.io/teal.modules.general/index.html
-[articles]: https://insightsengineering.github.io/teal.modules.general/main/articles/index.html
-[license]: https://insightsengineering.github.io/teal.modules.general/main/LICENSE-text.html
+[articles]: https://insightsengineering.github.io/teal.modules.general/latest-tag/articles/index.html
+[license]: https://insightsengineering.github.io/teal.modules.general/latest-tag/LICENSE-text.html
 [insights]: https://github.com/insightsengineering/teal.modules.general/pulse
diff --git a/.github/ISSUE_TEMPLATE/cran-release.yml b/.github/ISSUE_TEMPLATE/cran-release.yml
index b91449034..fb5761956 100644
--- a/.github/ISSUE_TEMPLATE/cran-release.yml
+++ b/.github/ISSUE_TEMPLATE/cran-release.yml
@@ -119,4 +119,4 @@ body:
       description: Any decision tree(s) that would aid release management
       placeholder: Any decision tree(s) that would aid release management.
       value: |
-        Click [here](https://github.com/insightsengineering/.github/blob/main/.github/ISSUE_TEMPLATE/RELEASE_DECISION_TREE.md) to see the release decision tree.
+        Click [here](https://github.com/insightsengineering/.github/blob/latest-tag/.github/ISSUE_TEMPLATE/RELEASE_DECISION_TREE.md) to see the release decision tree.
diff --git a/.github/ISSUE_TEMPLATE/release.yml b/.github/ISSUE_TEMPLATE/release.yml
index 665688e41..1af87126b 100644
--- a/.github/ISSUE_TEMPLATE/release.yml
+++ b/.github/ISSUE_TEMPLATE/release.yml
@@ -119,4 +119,4 @@ body:
       description: Any decision tree(s) that would aid release management
       placeholder: Any decision tree(s) that would aid release management.
       value: |
-        Click [here](https://github.com/insightsengineering/.github/blob/main/.github/ISSUE_TEMPLATE/RELEASE_DECISION_TREE.md) to see the release decision tree.
+        Click [here](https://github.com/insightsengineering/.github/blob/latest-tag/.github/ISSUE_TEMPLATE/RELEASE_DECISION_TREE.md) to see the release decision tree.
diff --git a/.github/workflows/check.yaml b/.github/workflows/check.yaml
index 57b2feee5..bc9b9786f 100644
--- a/.github/workflows/check.yaml
+++ b/.github/workflows/check.yaml
@@ -40,7 +40,7 @@ jobs:
         checking for unstated dependencies in vignettes .* NOTE
         checking top-level files .* NOTE
       unit-test-report-brand: >-
-        https://raw.githubusercontent.com/insightsengineering/hex-stickers/main/thumbs/teal.png
+        https://raw.githubusercontent.com/insightsengineering/hex-stickers/latest-tag/thumbs/teal.png
   coverage:
     name: Coverage 📔
     uses: insightsengineering/r.pkg.template/.github/workflows/test-coverage.yaml@main
diff --git a/.github/workflows/release.yaml b/.github/workflows/release.yaml
index 0fa4a06c8..557076b4f 100644
--- a/.github/workflows/release.yaml
+++ b/.github/workflows/release.yaml
@@ -54,7 +54,7 @@ jobs:
         checking Rd line widths .* NOTE
         checking top-level files .* NOTE
       unit-test-report-brand: >-
-        https://raw.githubusercontent.com/insightsengineering/hex-stickers/main/thumbs/teal.png
+        https://raw.githubusercontent.com/insightsengineering/hex-stickers/latest-tag/thumbs/teal.png
   coverage:
     name: Coverage 📔
     needs: [release, docs]

From 7537fcc5838911af3ca304d97a99d99760a35568 Mon Sep 17 00:00:00 2001
From: m7pr <marcin.kosinski.mk1@roche.com>
Date: Mon, 19 Feb 2024 13:15:09 +0100
Subject: [PATCH 06/62] add latest-tag/ to urls

---
 .github/CONTRIBUTING.md                | 2 +-
 .github/ISSUE_TEMPLATE/bug.yml         | 6 +++---
 .github/ISSUE_TEMPLATE/feature.yml     | 6 +++---
 .github/ISSUE_TEMPLATE/question.yml    | 6 +++---
 vignettes/teal-modules-general.Rmd     | 6 +++---
 vignettes/using-association-plot.Rmd   | 4 ++--
 vignettes/using-bivariate-plot.Rmd     | 4 ++--
 vignettes/using-cross-table.Rmd        | 4 ++--
 vignettes/using-data-table.Rmd         | 4 ++--
 vignettes/using-outliers-module.Rmd    | 4 ++--
 vignettes/using-regression-plots.Rmd   | 4 ++--
 vignettes/using-response-plot.Rmd      | 4 ++--
 vignettes/using-scatterplot-matrix.Rmd | 4 ++--
 vignettes/using-scatterplot.Rmd        | 4 ++--
 14 files changed, 31 insertions(+), 31 deletions(-)

diff --git a/.github/CONTRIBUTING.md b/.github/CONTRIBUTING.md
index 139e12af1..9683864a4 100644
--- a/.github/CONTRIBUTING.md
+++ b/.github/CONTRIBUTING.md
@@ -130,7 +130,7 @@ The package maintainer also reserves the right to adjust the criteria to recogni
 If you have further questions regarding the contribution guidelines, please contact the package/repository maintainer.
 
 <!-- urls -->
-[docs]: https://insightsengineering.github.io/teal.modules.general/index.html
+[docs]: https://insightsengineering.github.io/teal.modules.general/latest-tag/
 [articles]: https://insightsengineering.github.io/teal.modules.general/latest-tag/articles/index.html
 [license]: https://insightsengineering.github.io/teal.modules.general/latest-tag/LICENSE-text.html
 [insights]: https://github.com/insightsengineering/teal.modules.general/pulse
diff --git a/.github/ISSUE_TEMPLATE/bug.yml b/.github/ISSUE_TEMPLATE/bug.yml
index 9143772f7..ac82deccd 100644
--- a/.github/ISSUE_TEMPLATE/bug.yml
+++ b/.github/ISSUE_TEMPLATE/bug.yml
@@ -33,7 +33,7 @@ body:
     id: code-of-conduct
     attributes:
       label: Code of Conduct
-      description: By submitting this issue, you agree to follow our [Code of Conduct.](https://insightsengineering.github.io/teal.modules.general/CODE_OF_CONDUCT.html)
+      description: By submitting this issue, you agree to follow our [Code of Conduct.](https://insightsengineering.github.io/teal.modules.general/latest-tag/CODE_OF_CONDUCT.html)
       options:
         - label: I agree to follow this project's Code of Conduct.
           required: true
@@ -41,7 +41,7 @@ body:
     id: contributor-guidelines
     attributes:
       label: Contribution Guidelines
-      description: By submitting this issue, you agree to follow our [Contribution Guidelines.](https://insightsengineering.github.io/teal.modules.general/CONTRIBUTING.html)
+      description: By submitting this issue, you agree to follow our [Contribution Guidelines.](https://insightsengineering.github.io/teal.modules.general/latest-tag/CONTRIBUTING.html)
       options:
         - label: I agree to follow this project's Contribution Guidelines.
           required: true
@@ -49,7 +49,7 @@ body:
     id: security-policy
     attributes:
       label: Security Policy
-      description: By submitting this issue, you agree to follow our [Security Policy.](https://github.com/insightsengineering/teal.modules.general/security/policy)
+      description: By submitting this issue, you agree to follow our [Security Policy.](https://github.com/insightsengineering/teal.modules.general/latest-tag/security/policy)
       options:
         - label: I agree to follow this project's Security Policy.
           required: true
diff --git a/.github/ISSUE_TEMPLATE/feature.yml b/.github/ISSUE_TEMPLATE/feature.yml
index 84ec822de..f47d69400 100644
--- a/.github/ISSUE_TEMPLATE/feature.yml
+++ b/.github/ISSUE_TEMPLATE/feature.yml
@@ -13,7 +13,7 @@ body:
     id: code-of-conduct
     attributes:
       label: Code of Conduct
-      description: By submitting this issue, you agree to follow our [Code of Conduct.](https://insightsengineering.github.io/teal.modules.general/CODE_OF_CONDUCT.html)
+      description: By submitting this issue, you agree to follow our [Code of Conduct.](https://insightsengineering.github.io/teal.modules.general/latest-tag/CODE_OF_CONDUCT.html)
       options:
         - label: I agree to follow this project's Code of Conduct.
           required: true
@@ -21,7 +21,7 @@ body:
     id: contributor-guidelines
     attributes:
       label: Contribution Guidelines
-      description: By submitting this issue, you agree to follow our [Contribution Guidelines.](https://insightsengineering.github.io/teal.modules.general/CONTRIBUTING.html)
+      description: By submitting this issue, you agree to follow our [Contribution Guidelines.](https://insightsengineering.github.io/teal.modules.general/latest-tag/CONTRIBUTING.html)
       options:
         - label: I agree to follow this project's Contribution Guidelines.
           required: true
@@ -29,7 +29,7 @@ body:
     id: security-policy
     attributes:
       label: Security Policy
-      description: By submitting this issue, you agree to follow our [Security Policy.](https://github.com/insightsengineering/teal.modules.general/security/policy)
+      description: By submitting this issue, you agree to follow our [Security Policy.](https://github.com/insightsengineering/teal.modules.general/latest-tag/security/policy)
       options:
         - label: I agree to follow this project's Security Policy.
           required: true
diff --git a/.github/ISSUE_TEMPLATE/question.yml b/.github/ISSUE_TEMPLATE/question.yml
index 4c3628c1f..a70c47bb8 100644
--- a/.github/ISSUE_TEMPLATE/question.yml
+++ b/.github/ISSUE_TEMPLATE/question.yml
@@ -13,7 +13,7 @@ body:
     id: code-of-conduct
     attributes:
       label: Code of Conduct
-      description: By submitting this issue, you agree to follow our [Code of Conduct.](https://insightsengineering.github.io/teal.modules.general/CODE_OF_CONDUCT.html)
+      description: By submitting this issue, you agree to follow our [Code of Conduct.](https://insightsengineering.github.io/teal.modules.general/latest-tag/CODE_OF_CONDUCT.html)
       options:
         - label: I agree to follow this project's Code of Conduct.
           required: true
@@ -21,7 +21,7 @@ body:
     id: contributor-guidelines
     attributes:
       label: Contribution Guidelines
-      description: By submitting this issue, you agree to follow our [Contribution Guidelines.](https://insightsengineering.github.io/teal.modules.general/CONTRIBUTING.html)
+      description: By submitting this issue, you agree to follow our [Contribution Guidelines.](https://insightsengineering.github.io/teal.modules.general/latest-tag/CONTRIBUTING.html)
       options:
         - label: I agree to follow this project's Contribution Guidelines.
           required: true
@@ -29,7 +29,7 @@ body:
     id: security-policy
     attributes:
       label: Security Policy
-      description: By submitting this issue, you agree to follow our [Security Policy.](https://github.com/insightsengineering/teal.modules.general/security/policy)
+      description: By submitting this issue, you agree to follow our [Security Policy.](https://github.com/insightsengineering/teal.modules.general/latest-tag/security/policy)
       options:
         - label: I agree to follow this project's Security Policy.
           required: true
diff --git a/vignettes/teal-modules-general.Rmd b/vignettes/teal-modules-general.Rmd
index 588639320..bd1582059 100644
--- a/vignettes/teal-modules-general.Rmd
+++ b/vignettes/teal-modules-general.Rmd
@@ -21,9 +21,9 @@ other `shiny` modules to build a large `teal` / `shiny` app.
 
 The concepts presented here require knowledge about the core features of `teal`, specifically on how to launch a `teal`
 application and how to pass data into it. Therefore, it is highly recommended to refer to the [`README`](https://insightsengineering.github.io/teal/index.html) file and 
-the introductory [vignette](https://insightsengineering.github.io/teal/articles/teal.html) of the `teal` package.
+the introductory [vignette](https://insightsengineering.github.io/teal/latest-tag/articles/teal.html) of the `teal` package.
 
-See also `teal.modules.clinical's` [`README`](https://insightsengineering.github.io/teal.modules.clinical/index.html).
+See also `teal.modules.clinical's` [`README`](https://insightsengineering.github.io/teal.modules.clinical/latest-tag/index.html).
 
 ### Main features
 
@@ -35,7 +35,7 @@ There are five areas of data science that `teal.modules.general` provides tools
 - examining missing and extreme values in data
 - performing data analysis
 
-See [package functions / modules](https://insightsengineering.github.io/teal.modules.general/reference/index.html).
+See [package functions / modules](https://insightsengineering.github.io/teal.modules.general/latest-tag/reference/index.html).
 
 ### Example application
 
diff --git a/vignettes/using-association-plot.Rmd b/vignettes/using-association-plot.Rmd
index 238d672e9..00db48b35 100644
--- a/vignettes/using-association-plot.Rmd
+++ b/vignettes/using-association-plot.Rmd
@@ -55,8 +55,8 @@ ADLB <- teal.modules.general::rADLB %>%
 
 ## Create an `app` variable
 
-This is the most important section. We will use the [`teal::init`](https://insightsengineering.github.io/teal/reference/init) function to
-create an app. The data will be handed over using [`teal.data::cdisc_data`](https://insightsengineering.github.io/teal.data/reference/cdisc_data). The app
+This is the most important section. We will use the [`teal::init`](https://insightsengineering.github.io/teal/latest-tag/reference/init) function to
+create an app. The data will be handed over using [`teal.data::cdisc_data`](https://insightsengineering.github.io/teal.data/latest-tag/reference/cdisc_data). The app
 itself will be constructed by multiple calls of `tm_g_association` using different
 combinations of data sets.
 
diff --git a/vignettes/using-bivariate-plot.Rmd b/vignettes/using-bivariate-plot.Rmd
index 509cd1b3e..021f329b6 100644
--- a/vignettes/using-bivariate-plot.Rmd
+++ b/vignettes/using-bivariate-plot.Rmd
@@ -68,8 +68,8 @@ jk["ADSL2", "ADSL"] <- c("USUBJID", "STUDYID")
 
 ## Create an `app` variable
 
-This is the most important section. We will use the [`teal::init`](https://insightsengineering.github.io/teal/reference/init) function to
-create an app. The data will be handed over using [`teal.data::cdisc_data`](https://insightsengineering.github.io/teal.data/reference/cdisc_data). The app
+This is the most important section. We will use the [`teal::init`](https://insightsengineering.github.io/teal/latest-tag/reference/init) function to
+create an app. The data will be handed over using [`teal.data::cdisc_data`](https://insightsengineering.github.io/teal.data/latest-tag/reference/cdisc_data). The app
 itself will be constructed by multiple calls of `tm_g_bivariate` using different
 combinations of data sets.
 
diff --git a/vignettes/using-cross-table.Rmd b/vignettes/using-cross-table.Rmd
index 34258cca6..9d19e8167 100644
--- a/vignettes/using-cross-table.Rmd
+++ b/vignettes/using-cross-table.Rmd
@@ -54,8 +54,8 @@ join_keys(data) <- default_cdisc_join_keys[datanames]
 
 ## Create an `app` variable
 
-This is the most important section. We will use the [`teal::init`](https://insightsengineering.github.io/teal/reference/init) function to
-create an app. The data will be handed over using [`teal.data::cdisc_data`](https://insightsengineering.github.io/teal.data/reference/cdisc_data). The app
+This is the most important section. We will use the [`teal::init`](https://insightsengineering.github.io/teal/latest-tag/reference/init) function to
+create an app. The data will be handed over using [`teal.data::cdisc_data`](https://insightsengineering.github.io/teal.data/latest-tag/reference/cdisc_data). The app
 itself will be constructed by multiple calls of `tm_t_crosstable` using different
 combinations of data sets.
 
diff --git a/vignettes/using-data-table.Rmd b/vignettes/using-data-table.Rmd
index 35e2ea7a4..e6bedc886 100644
--- a/vignettes/using-data-table.Rmd
+++ b/vignettes/using-data-table.Rmd
@@ -50,8 +50,8 @@ join_keys(data) <- default_cdisc_join_keys[datanames]
 
 ## Create an `app` variable
 
-This is the most important section. We will use the [`teal::init`](https://insightsengineering.github.io/teal/reference/init) function to
-create an app. The data will be handed over using [`teal.data::cdisc_data`](https://insightsengineering.github.io/teal.data/reference/cdisc_data). The app itself will be constructed by multiple calls of `tm_data_table` using different
+This is the most important section. We will use the [`teal::init`](https://insightsengineering.github.io/teal/latest-tag/reference/init) function to
+create an app. The data will be handed over using [`teal.data::cdisc_data`](https://insightsengineering.github.io/teal.data/latest-tag/reference/cdisc_data). The app itself will be constructed by multiple calls of `tm_data_table` using different
 combinations of data sets.
 
 ```{r echo=TRUE, message=FALSE, warning=FALSE, results="hide"}
diff --git a/vignettes/using-outliers-module.Rmd b/vignettes/using-outliers-module.Rmd
index b9ea35f7e..ee9136f8b 100644
--- a/vignettes/using-outliers-module.Rmd
+++ b/vignettes/using-outliers-module.Rmd
@@ -51,8 +51,8 @@ join_keys(data) <- default_cdisc_join_keys[datanames]
 
 ## Create an `app` variable
 
-This is the most important section. We will use the [`teal::init`](https://insightsengineering.github.io/teal/reference/init) function to
-create an app. The data will be handed over using [`teal.data::cdisc_data`](https://insightsengineering.github.io/teal.data/reference/cdisc_data). The app
+This is the most important section. We will use the [`teal::init`](https://insightsengineering.github.io/teal/latest-tag/reference/init) function to
+create an app. The data will be handed over using [`teal.data::cdisc_data`](https://insightsengineering.github.io/teal.data/latest-tag/reference/cdisc_data). The app
 itself will be constructed by multiple calls of `tm_outliers` using different
 combinations of data sets.
 
diff --git a/vignettes/using-regression-plots.Rmd b/vignettes/using-regression-plots.Rmd
index 636d6d974..b2515f1e1 100644
--- a/vignettes/using-regression-plots.Rmd
+++ b/vignettes/using-regression-plots.Rmd
@@ -66,8 +66,8 @@ jk["ADSL2", "ADSL"] <- c("USUBJID", "STUDYID")
 
 ## Create an `app` variable
 
-This is the most important section. We will use the [`teal::init`](https://insightsengineering.github.io/teal/reference/init) function to
-create an app. The data will be handed over using [`teal.data::cdisc_data`](https://insightsengineering.github.io/teal.data/reference/cdisc_data). The app
+This is the most important section. We will use the [`teal::init`](https://insightsengineering.github.io/teal/latest-tag/reference/init) function to
+create an app. The data will be handed over using [`teal.data::cdisc_data`](https://insightsengineering.github.io/teal.data/latest-tag/reference/cdisc_data). The app
 itself will be constructed by multiple calls of `tm_a_regression` using different
 combinations of data sets.
 
diff --git a/vignettes/using-response-plot.Rmd b/vignettes/using-response-plot.Rmd
index 47eedbbac..14baa6ecb 100644
--- a/vignettes/using-response-plot.Rmd
+++ b/vignettes/using-response-plot.Rmd
@@ -65,8 +65,8 @@ jk["ADSL2", "ADSL"] <- c("USUBJID", "STUDYID")
 
 ## Create an `app` variable
 
-This is the most important section. We will use the [`teal::init`](https://insightsengineering.github.io/teal/reference/init) function to
-create an app. The data will be handed over using [`teal.data::cdisc_data`](https://insightsengineering.github.io/teal.data/reference/cdisc_data). The app
+This is the most important section. We will use the [`teal::init`](https://insightsengineering.github.io/teal/latest-tag/reference/init) function to
+create an app. The data will be handed over using [`teal.data::cdisc_data`](https://insightsengineering.github.io/teal.data/latest-tag/reference/cdisc_data). The app
 itself will be constructed by multiple calls of `tm_g_response` using different
 combinations of data sets.
 
diff --git a/vignettes/using-scatterplot-matrix.Rmd b/vignettes/using-scatterplot-matrix.Rmd
index 7ea3ab2c0..ee6a2ff75 100644
--- a/vignettes/using-scatterplot-matrix.Rmd
+++ b/vignettes/using-scatterplot-matrix.Rmd
@@ -66,8 +66,8 @@ jk["ADSL2", "ADSL"] <- c("USUBJID", "STUDYID")
 
 ## Create an `app` variable
 
-This is the most important section. We will use the [`teal::init`](https://insightsengineering.github.io/teal/reference/init) function to
-create an app. The data will be handed over using [`teal.data::cdisc_data`](https://insightsengineering.github.io/teal.data/reference/cdisc_data). The app
+This is the most important section. We will use the [`teal::init`](https://insightsengineering.github.io/teal/latest-tag/reference/init) function to
+create an app. The data will be handed over using [`teal.data::cdisc_data`](https://insightsengineering.github.io/teal.data/latest-tag/reference/cdisc_data). The app
 itself will be constructed by multiple calls of `tm_g_scatterplotmatrix` using different
 combinations of data sets.
 
diff --git a/vignettes/using-scatterplot.Rmd b/vignettes/using-scatterplot.Rmd
index 84f1de4d0..276a8ca11 100644
--- a/vignettes/using-scatterplot.Rmd
+++ b/vignettes/using-scatterplot.Rmd
@@ -66,8 +66,8 @@ jk["ADSL2", "ADSL"] <- c("USUBJID", "STUDYID")
 
 ## Create an `app` variable
 
-This is the most important section. We will use the [`teal::init`](https://insightsengineering.github.io/teal/reference/init) function to
-create an app. The data will be handed over using [`teal.data::cdisc_data`](https://insightsengineering.github.io/teal.data/reference/cdisc_data). The app
+This is the most important section. We will use the [`teal::init`](https://insightsengineering.github.io/teal/latest-tag/reference/init) function to
+create an app. The data will be handed over using [`teal.data::cdisc_data`](https://insightsengineering.github.io/teal.data/latest-tag/reference/cdisc_data). The app
 itself will be constructed by multiple calls of `tm_g_scatterplot` using different
 combinations of data sets.
 

From 7d0ff636dfdb28a1ed67f648bf19d04fcd92bc03 Mon Sep 17 00:00:00 2001
From: m7pr <marcin.kosinski.mk1@roche.com>
Date: Mon, 19 Feb 2024 13:16:55 +0100
Subject: [PATCH 07/62] Remove exception in .lintr: indentation_linter = NULL

---
 .lintr | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/.lintr b/.lintr
index 0a0bb22f3..34473d273 100644
--- a/.lintr
+++ b/.lintr
@@ -1,6 +1,5 @@
 linters: linters_with_defaults(
   line_length_linter = line_length_linter(120),
   cyclocomp_linter = NULL,
-  object_usage_linter = NULL,
-  indentation_linter = NULL
+  object_usage_linter = NULL
   )

From 6767f42d2b6a06bd3e5edbb0ca61615425315daf Mon Sep 17 00:00:00 2001
From: m7pr <marcin.kosinski.mk1@roche.com>
Date: Mon, 19 Feb 2024 13:29:23 +0100
Subject: [PATCH 08/62] add LICENSE to .Rbuildignore

---
 .Rbuildignore | 1 +
 1 file changed, 1 insertion(+)

diff --git a/.Rbuildignore b/.Rbuildignore
index a262382cf..08f35f406 100644
--- a/.Rbuildignore
+++ b/.Rbuildignore
@@ -40,6 +40,7 @@ SECURITY.md
 ^staged_dependencies\.yaml$
 ^\.gitlab-ci\.yml$
 ^LICENSE\.md$
+LICENSE
 coverage.*
 ^sample_files$
 ^\.pre-commit-config\.yaml

From ac43d537ee7a1dc943e29acabd381a3653538338 Mon Sep 17 00:00:00 2001
From: m7pr <marcin.kosinski.mk1@roche.com>
Date: Tue, 20 Feb 2024 10:26:49 +0100
Subject: [PATCH 09/62] extend WORDLIST

---
 inst/WORDLIST | 1 +
 1 file changed, 1 insertion(+)

diff --git a/inst/WORDLIST b/inst/WORDLIST
index 6815d0d95..e59688844 100644
--- a/inst/WORDLIST
+++ b/inst/WORDLIST
@@ -4,6 +4,7 @@ TLG
 facetting
 funder
 pre
+Prebuilt
 repo
 reproducibility
 tabset

From ee2d08b59e3800ff069bb22917a33ba5adfad71c Mon Sep 17 00:00:00 2001
From: Marcin <133694481+m7pr@users.noreply.github.com>
Date: Tue, 20 Feb 2024 12:44:29 +0100
Subject: [PATCH 10/62] Update vignettes/using-association-plot.Rmd

Co-authored-by: kartikeya kirar <kirar.kartikeya1@gmail.com>
Signed-off-by: Marcin <133694481+m7pr@users.noreply.github.com>
---
 vignettes/using-association-plot.Rmd | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/vignettes/using-association-plot.Rmd b/vignettes/using-association-plot.Rmd
index 00db48b35..d73b9ab0d 100644
--- a/vignettes/using-association-plot.Rmd
+++ b/vignettes/using-association-plot.Rmd
@@ -53,7 +53,7 @@ ADLB <- teal.modules.general::rADLB %>%
 # nolint end
 ```
 
-## Create an `app` variable
+## Initialize an app
 
 This is the most important section. We will use the [`teal::init`](https://insightsengineering.github.io/teal/latest-tag/reference/init) function to
 create an app. The data will be handed over using [`teal.data::cdisc_data`](https://insightsengineering.github.io/teal.data/latest-tag/reference/cdisc_data). The app

From f8d3583e828d0d92791db1b67462eff4ba1dfe98 Mon Sep 17 00:00:00 2001
From: m7pr <marcin.kosinski.mk1@roche.com>
Date: Tue, 20 Feb 2024 13:21:23 +0100
Subject: [PATCH 11/62] revert template changes

---
 .github/ISSUE_TEMPLATE/cran-release.yml | 2 +-
 .github/ISSUE_TEMPLATE/release.yml      | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/.github/ISSUE_TEMPLATE/cran-release.yml b/.github/ISSUE_TEMPLATE/cran-release.yml
index fb5761956..b91449034 100644
--- a/.github/ISSUE_TEMPLATE/cran-release.yml
+++ b/.github/ISSUE_TEMPLATE/cran-release.yml
@@ -119,4 +119,4 @@ body:
       description: Any decision tree(s) that would aid release management
       placeholder: Any decision tree(s) that would aid release management.
       value: |
-        Click [here](https://github.com/insightsengineering/.github/blob/latest-tag/.github/ISSUE_TEMPLATE/RELEASE_DECISION_TREE.md) to see the release decision tree.
+        Click [here](https://github.com/insightsengineering/.github/blob/main/.github/ISSUE_TEMPLATE/RELEASE_DECISION_TREE.md) to see the release decision tree.
diff --git a/.github/ISSUE_TEMPLATE/release.yml b/.github/ISSUE_TEMPLATE/release.yml
index 1af87126b..665688e41 100644
--- a/.github/ISSUE_TEMPLATE/release.yml
+++ b/.github/ISSUE_TEMPLATE/release.yml
@@ -119,4 +119,4 @@ body:
       description: Any decision tree(s) that would aid release management
       placeholder: Any decision tree(s) that would aid release management.
       value: |
-        Click [here](https://github.com/insightsengineering/.github/blob/latest-tag/.github/ISSUE_TEMPLATE/RELEASE_DECISION_TREE.md) to see the release decision tree.
+        Click [here](https://github.com/insightsengineering/.github/blob/main/.github/ISSUE_TEMPLATE/RELEASE_DECISION_TREE.md) to see the release decision tree.

From c57bc173901a2d227ee5ab3284e0393e09ffdb81 Mon Sep 17 00:00:00 2001
From: Aleksander Chlebowski <114988527+chlebowa@users.noreply.github.com>
Date: Wed, 21 Feb 2024 16:17:20 +0100
Subject: [PATCH 12/62] 642 unused functions (#659)

Closes #642.

Removed `substitute_q` and `extract_input`.
Added `@keywords internal` to `is_num_var_short`.
---
 R/tm_g_bivariate.R      |  6 ------
 R/tm_variable_browser.R |  2 +-
 R/utils.R               | 18 ------------------
 man/extract_input.Rd    | 23 -----------------------
 4 files changed, 1 insertion(+), 48 deletions(-)
 delete mode 100644 man/extract_input.Rd

diff --git a/R/tm_g_bivariate.R b/R/tm_g_bivariate.R
index 460ba1b9c..e9b3d3106 100644
--- a/R/tm_g_bivariate.R
+++ b/R/tm_g_bivariate.R
@@ -703,12 +703,6 @@ bivariate_plot_call <- function(data_name,
   )
 }
 
-substitute_q <- function(x, env) {
-  stopifnot(is.language(x))
-  call <- substitute(substitute(x, env), list(x = x))
-  eval(call)
-}
-
 
 #' Create ggplot part of plot call
 #'
diff --git a/R/tm_variable_browser.R b/R/tm_variable_browser.R
index 71730bff8..272ca862d 100644
--- a/R/tm_variable_browser.R
+++ b/R/tm_variable_browser.R
@@ -533,7 +533,6 @@ var_missings_info <- function(x) {
 #'
 #' @return character variable containing the HTML code of the \code{sparkline} HTML widget
 #' @keywords internal
-#'
 create_sparklines <- function(arr, width = 150, ...) {
   if (all(is.null(arr))) {
     return("")
@@ -1025,6 +1024,7 @@ plot_var_summary <- function(var,
   plot_main
 }
 
+#' @keywords internal
 is_num_var_short <- function(.unique_records_for_factor, input, data_for_analysis) {
   length(unique(data_for_analysis()$data)) < .unique_records_for_factor && !is.null(input$numeric_as_factor)
 }
diff --git a/R/utils.R b/R/utils.R
index 1d2a1e56d..d4f8c874f 100644
--- a/R/utils.R
+++ b/R/utils.R
@@ -190,24 +190,6 @@ varname_w_label <- function(var_names,
   }
 }
 
-#' Extract html id for `data_extract_ui`
-#' @description The `data_extract_ui` is located under extended html id.
-#'   We could not use \code{ns("original id")} for reference, as it is extended with specific suffixes.
-#' @param varname character original html id.
-#'   This will be mostly retrieved with \code{ns("original id")} in `ui` or
-#'   \code{session$ns("original id")} in server function.
-#' @param dataname character \code{dataname} from data_extract input.
-#'   This might be retrieved like \code{teal.transform::data_extract_spec(...)[[1]]$dataname}.
-#' @param filter logical if the connected \code{extract_data_spec} is used with \code{filter} option.
-#' @keywords internal
-extract_input <- function(varname, dataname, filter = FALSE) {
-  if (filter) {
-    paste0(varname, "-dataset_", dataname, "_singleextract-filter1-vals")
-  } else {
-    paste0(varname, "-dataset_", dataname, "_singleextract-select")
-  }
-}
-
 # see vignette("ggplot2-specs", package="ggplot2")
 shape_names <- c(
   "circle", paste("circle", c("open", "filled", "cross", "plus", "small")), "bullet",
diff --git a/man/extract_input.Rd b/man/extract_input.Rd
deleted file mode 100644
index 5847b36fa..000000000
--- a/man/extract_input.Rd
+++ /dev/null
@@ -1,23 +0,0 @@
-% Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/utils.R
-\name{extract_input}
-\alias{extract_input}
-\title{Extract html id for \code{data_extract_ui}}
-\usage{
-extract_input(varname, dataname, filter = FALSE)
-}
-\arguments{
-\item{varname}{character original html id.
-This will be mostly retrieved with \code{ns("original id")} in \code{ui} or
-\code{session$ns("original id")} in server function.}
-
-\item{dataname}{character \code{dataname} from data_extract input.
-This might be retrieved like \code{teal.transform::data_extract_spec(...)[[1]]$dataname}.}
-
-\item{filter}{logical if the connected \code{extract_data_spec} is used with \code{filter} option.}
-}
-\description{
-The \code{data_extract_ui} is located under extended html id.
-We could not use \code{ns("original id")} for reference, as it is extended with specific suffixes.
-}
-\keyword{internal}

From 400d8cd95df1a94c14331d97da021853fc781f31 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Andr=C3=A9=20Ver=C3=ADssimo?=
 <211358+averissimo@users.noreply.github.com>
Date: Thu, 22 Feb 2024 12:47:16 +0100
Subject: [PATCH 13/62] Adds common `@return` for modules and corrects linting
 (#670)

Part of #624

From this
https://github.com/insightsengineering/teal.modules.general/issues/624#issuecomment-1957830948

#### Changes description

- Adds `@return` tag to `shared_params` to be reused across all
documentation
- Corrects linter errors
---
 R/tm_g_bivariate.R    | 61 +++++++++++++++++++++++++++++++------------
 R/tm_g_distribution.R |  9 +++++--
 R/tm_g_response.R     |  5 ++--
 R/tm_g_scatterplot.R  | 24 +++++++++++------
 R/tm_missing_data.R   |  8 +++---
 R/tm_outliers.R       |  6 +++--
 R/tm_t_crosstable.R   |  2 +-
 R/utils.R             |  2 ++
 man/shared_params.Rd  |  3 +++
 9 files changed, 85 insertions(+), 35 deletions(-)

diff --git a/R/tm_g_bivariate.R b/R/tm_g_bivariate.R
index e9b3d3106..b84fe96cd 100644
--- a/R/tm_g_bivariate.R
+++ b/R/tm_g_bivariate.R
@@ -954,38 +954,67 @@ coloring_ggplot_call <- function(colour,
                                  fill,
                                  size,
                                  is_point = FALSE) {
-  if (!identical(colour, character(0)) && !identical(fill, character(0)) &&
-    is_point && !identical(size, character(0))) {
+  if (
+    !identical(colour, character(0)) &&
+      !identical(fill, character(0)) &&
+      is_point &&
+      !identical(size, character(0))
+  ) {
     substitute(
       expr = aes(colour = colour_name, fill = fill_name, size = size_name),
       env = list(colour_name = as.name(colour), fill_name = as.name(fill), size_name = as.name(size))
     )
-  } else if (identical(colour, character(0)) && !identical(fill, character(0)) &&
-    is_point && identical(size, character(0))) {
+  } else if (
+    identical(colour, character(0)) &&
+      !identical(fill, character(0)) &&
+      is_point &&
+      identical(size, character(0))
+  ) {
     substitute(expr = aes(fill = fill_name), env = list(fill_name = as.name(fill)))
-  } else if (!identical(colour, character(0)) && !identical(fill, character(0)) &&
-    (!is_point || identical(size, character(0)))) {
+  } else if (
+    !identical(colour, character(0)) &&
+      !identical(fill, character(0)) &&
+      (!is_point || identical(size, character(0)))
+  ) {
     substitute(
       expr = aes(colour = colour_name, fill = fill_name),
       env = list(colour_name = as.name(colour), fill_name = as.name(fill))
     )
-  } else if (!identical(colour, character(0)) && identical(fill, character(0)) &&
-    (!is_point || identical(size, character(0)))) {
+  } else if (
+    !identical(colour, character(0)) &&
+      identical(fill, character(0)) &&
+      (!is_point || identical(size, character(0)))
+  ) {
     substitute(expr = aes(colour = colour_name), env = list(colour_name = as.name(colour)))
-  } else if (identical(colour, character(0)) && !identical(fill, character(0)) &&
-    (!is_point || identical(size, character(0)))) {
+  } else if (
+    identical(colour, character(0)) &&
+      !identical(fill, character(0)) &&
+      (!is_point || identical(size, character(0)))
+  ) {
     substitute(expr = aes(fill = fill_name), env = list(fill_name = as.name(fill)))
-  } else if (identical(colour, character(0)) && identical(fill, character(0)) &&
-    is_point && !identical(size, character(0))) {
+  } else if (
+    identical(colour, character(0)) &&
+      identical(fill, character(0)) &&
+      is_point &&
+      !identical(size, character(0))
+  ) {
     substitute(expr = aes(size = size_name), env = list(size_name = as.name(size)))
-  } else if (!identical(colour, character(0)) && identical(fill, character(0)) &&
-    is_point && !identical(size, character(0))) {
+  } else if (
+    !identical(colour, character(0)) &&
+      identical(fill, character(0)) &&
+      is_point &&
+      !identical(size, character(0))
+  ) {
     substitute(
       expr = aes(colour = colour_name, size = size_name),
       env = list(colour_name = as.name(colour), size_name = as.name(size))
     )
-  } else if (identical(colour, character(0)) && !identical(fill, character(0)) &&
-    is_point && !identical(size, character(0))) {
+  } else if (
+    identical(colour, character(0)) &&
+      !identical(fill, character(0)) &&
+      is_point &&
+      !identical(size, character(0))
+  ) {
     substitute(
       expr = aes(colour = colour_name, fill = fill_name, size = size_name),
       env = list(colour_name = as.name(fill), fill_name = as.name(fill), size_name = as.name(size))
diff --git a/R/tm_g_distribution.R b/R/tm_g_distribution.R
index 48a0adef4..484f94305 100644
--- a/R/tm_g_distribution.R
+++ b/R/tm_g_distribution.R
@@ -802,8 +802,13 @@ srv_distribution <- function(id,
           )
         }
 
-        if (length(s_var) == 0 && length(g_var) == 0 && main_type_var == "Density" &&
-          length(t_dist) != 0 && main_type_var == "Density") {
+        if (
+          length(s_var) == 0 &&
+            length(g_var) == 0 &&
+            main_type_var == "Density" &&
+            length(t_dist) != 0 &&
+            main_type_var == "Density"
+        ) {
           map_dist <- stats::setNames(
             c("dnorm", "dlnorm", "dgamma", "dunif"),
             c("normal", "lognormal", "gamma", "unif")
diff --git a/R/tm_g_response.R b/R/tm_g_response.R
index 3ca9acdf0..aba073e8c 100644
--- a/R/tm_g_response.R
+++ b/R/tm_g_response.R
@@ -368,9 +368,8 @@ srv_g_response <- function(id,
       # nolint end
 
       plot_call <- substitute(
-        expr =
-          ggplot(ANL2, aes(x = x_cl, y = ns)) +
-            geom_bar(aes(fill = resp_cl), stat = "identity", position = arg_position),
+        expr = ggplot(ANL2, aes(x = x_cl, y = ns)) +
+          geom_bar(aes(fill = resp_cl), stat = "identity", position = arg_position),
         env = list(
           x_cl = x_cl,
           resp_cl = resp_cl,
diff --git a/R/tm_g_scatterplot.R b/R/tm_g_scatterplot.R
index 9caab3f2c..3ee271844 100644
--- a/R/tm_g_scatterplot.R
+++ b/R/tm_g_scatterplot.R
@@ -459,9 +459,13 @@ srv_g_scatterplot <- function(id,
       teal.transform::compose_and_enable_validators(iv, selector_list)
     })
     iv_facet <- shinyvalidate::InputValidator$new()
-    iv_facet$add_rule("add_density", ~ if (isTRUE(.) &&
-      (length(selector_list()$row_facet()$select) > 0L ||
-        length(selector_list()$col_facet()$select) > 0L)) {
+    iv_facet$add_rule("add_density", ~ if (
+      isTRUE(.) &&
+        (
+          length(selector_list()$row_facet()$select) > 0L ||
+            length(selector_list()$col_facet()$select) > 0L
+        )
+    ) {
       "Cannot add marginal density when Row or Column facetting has been selected"
     })
     iv_facet$enable()
@@ -524,8 +528,10 @@ srv_g_scatterplot <- function(id,
     observeEvent(
       eventExpr = merged$anl_input_r()$columns_source[c("col_facet", "row_facet")],
       handlerExpr = {
-        if (length(merged$anl_input_r()$columns_source$col_facet) == 0 &&
-          length(merged$anl_input_r()$columns_source$row_facet) == 0) {
+        if (
+          length(merged$anl_input_r()$columns_source$col_facet) == 0 &&
+            length(merged$anl_input_r()$columns_source$row_facet) == 0
+        ) {
           shinyjs::hide("free_scales")
         } else {
           shinyjs::show("free_scales")
@@ -582,9 +588,11 @@ srv_g_scatterplot <- function(id,
         \n Uncheck the 'Add marginal density' checkbox to display the plot."
         ))
         validate(need(
-          !(inherits(ANL[[color_by_var]], "Date") ||
-            inherits(ANL[[color_by_var]], "POSIXct") ||
-            inherits(ANL[[color_by_var]], "POSIXlt")),
+          !(
+            inherits(ANL[[color_by_var]], "Date") ||
+              inherits(ANL[[color_by_var]], "POSIXct") ||
+              inherits(ANL[[color_by_var]], "POSIXlt")
+          ),
           "Marginal plots cannot be produced when the points are colored by Date or POSIX variables.
         \n Uncheck the 'Add marginal density' checkbox to display the plot."
         ))
diff --git a/R/tm_missing_data.R b/R/tm_missing_data.R
index 64a81c968..be23ff191 100644
--- a/R/tm_missing_data.R
+++ b/R/tm_missing_data.R
@@ -554,9 +554,11 @@ srv_missing_data <- function(id, data, reporter, filter_panel_api, dataname, par
       # display those previously selected values that are still available
       selected <- if (!is.null(prev_choices) && any(prev_choices %in% choices)) {
         prev_choices[match(choices[choices %in% prev_choices], prev_choices)]
-      } else if (!is.null(prev_choices) &&
-        !any(prev_choices %in% choices) &&
-        isolate(prev_group_by_var()) == input$group_by_var) {
+      } else if (
+        !is.null(prev_choices) &&
+          !any(prev_choices %in% choices) &&
+          isolate(prev_group_by_var()) == input$group_by_var
+      ) {
         # if not any previously selected value is available and the grouping variable is the same,
         # then display NULL
         NULL
diff --git a/R/tm_outliers.R b/R/tm_outliers.R
index e58d2c53f..97da6aa8a 100644
--- a/R/tm_outliers.R
+++ b/R/tm_outliers.R
@@ -417,8 +417,10 @@ srv_outliers <- function(id, data, reporter, filter_panel_api, outlier_var,
                 expr = dplyr::mutate(is_outlier_selected = {
                   q1_q3 <- stats::quantile(outlier_var_name, probs = c(0.25, 0.75))
                   iqr <- q1_q3[2] - q1_q3[1]
-                  !(outlier_var_name >= q1_q3[1] - outlier_definition_param * iqr &
-                    outlier_var_name <= q1_q3[2] + outlier_definition_param * iqr)
+                  !(
+                    outlier_var_name >= q1_q3[1] - outlier_definition_param * iqr &
+                      outlier_var_name <= q1_q3[2] + outlier_definition_param * iqr
+                  )
                 }),
                 env = list(
                   outlier_var_name = as.name(outlier_var),
diff --git a/R/tm_t_crosstable.R b/R/tm_t_crosstable.R
index 809956335..e836b651a 100644
--- a/R/tm_t_crosstable.R
+++ b/R/tm_t_crosstable.R
@@ -283,7 +283,7 @@ srv_t_crosstable <- function(id, data, reporter, filter_panel_api, label, x, y,
           substitute(
             expr = {
               lyt <- basic_tables %>%
-              split_call %>% # styler: off
+                split_call %>% # styler: off
                 rtables::add_colcounts() %>%
                 tern::analyze_vars(
                   vars = x_name,
diff --git a/R/utils.R b/R/utils.R
index d4f8c874f..2d51001bb 100644
--- a/R/utils.R
+++ b/R/utils.R
@@ -25,6 +25,8 @@
 #' @param post_output (`shiny.tag`, optional) with text placed after the output to put the output
 #' into context. For example the [shiny::helpText()] elements are useful.
 #'
+#' @return Object of class `teal_module` to be used in `teal` applications
+#'
 #' @name shared_params
 #' @keywords internal
 NULL
diff --git a/man/shared_params.Rd b/man/shared_params.Rd
index f7fb3ffac..9749a4afa 100644
--- a/man/shared_params.Rd
+++ b/man/shared_params.Rd
@@ -33,6 +33,9 @@ with text placed before the output to put the output into context. For example a
 \item{post_output}{(\code{shiny.tag}, optional) with text placed after the output to put the output
 into context. For example the \code{\link[shiny:helpText]{shiny::helpText()}} elements are useful.}
 }
+\value{
+Object of class \code{teal_module} to be used in \code{teal} applications
+}
 \description{
 Contains arguments that are shared between multiple functions
 in the package to avoid repetition using \code{inheritParams}.

From b67b95725b3b91259c9add243460cb252236367c Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Andr=C3=A9=20Ver=C3=ADssimo?=
 <211358+averissimo@users.noreply.github.com>
Date: Thu, 22 Feb 2024 15:10:18 +0100
Subject: [PATCH 14/62] pre-release: Typo with missing a full stop (#671)

Part of #624

Sorry, I missed a full stop on #670
---
 R/utils.R            | 2 +-
 man/shared_params.Rd | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/R/utils.R b/R/utils.R
index 2d51001bb..0262e0b49 100644
--- a/R/utils.R
+++ b/R/utils.R
@@ -25,7 +25,7 @@
 #' @param post_output (`shiny.tag`, optional) with text placed after the output to put the output
 #' into context. For example the [shiny::helpText()] elements are useful.
 #'
-#' @return Object of class `teal_module` to be used in `teal` applications
+#' @return Object of class `teal_module` to be used in `teal` applications.
 #'
 #' @name shared_params
 #' @keywords internal
diff --git a/man/shared_params.Rd b/man/shared_params.Rd
index 9749a4afa..1d130bd66 100644
--- a/man/shared_params.Rd
+++ b/man/shared_params.Rd
@@ -34,7 +34,7 @@ with text placed before the output to put the output into context. For example a
 into context. For example the \code{\link[shiny:helpText]{shiny::helpText()}} elements are useful.}
 }
 \value{
-Object of class \code{teal_module} to be used in \code{teal} applications
+Object of class \code{teal_module} to be used in \code{teal} applications.
 }
 \description{
 Contains arguments that are shared between multiple functions

From 57a11220e4c7c610e60f8f5f7bb72fd94419ac49 Mon Sep 17 00:00:00 2001
From: Aleksander Chlebowski <114988527+chlebowa@users.noreply.github.com>
Date: Thu, 22 Feb 2024 15:32:46 +0100
Subject: [PATCH 15/62] 643 potential removal of dependencies (#663)

Closes #643
---
 .pre-commit-config.yaml  |  1 -
 DESCRIPTION              | 16 +++++++---------
 NAMESPACE                |  3 +--
 R/teal.modules.general.R |  5 ++---
 R/tm_a_pca.R             |  4 ++--
 R/tm_a_regression.R      |  4 ++--
 R/tm_data_table.R        |  6 +++---
 R/tm_front_page.R        |  2 +-
 R/tm_g_association.R     |  4 ++--
 R/tm_g_bivariate.R       |  4 ++--
 R/tm_g_response.R        |  4 ++--
 R/tm_g_scatterplot.R     |  4 ++--
 R/tm_missing_data.R      | 18 +++++++++---------
 man/tm_a_pca.Rd          |  4 ++--
 man/tm_a_regression.Rd   |  4 ++--
 man/tm_data_table.Rd     |  4 ++--
 man/tm_front_page.Rd     |  2 +-
 man/tm_g_association.Rd  |  4 ++--
 man/tm_g_bivariate.Rd    |  4 ++--
 man/tm_g_response.Rd     |  4 ++--
 man/tm_g_scatterplot.Rd  |  4 ++--
 man/tm_missing_data.Rd   |  4 ++--
 22 files changed, 52 insertions(+), 57 deletions(-)

diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index a80cd7b49..f10b1244e 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -43,7 +43,6 @@ repos:
           - tern
           - tibble
           - tidyr
-          - tidyselect
           - utils
 
       - id: spell-check
diff --git a/DESCRIPTION b/DESCRIPTION
index 9b2b532c9..2e5aafaed 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -13,9 +13,10 @@ Authors@R: c(
     person("Nikolas", "Burkoff", role = "aut"),
     person("F. Hoffmann-La Roche AG", role = c("cph", "fnd"))
   )
-Description: Prebuilt 'shiny' modules containing tools for viewing data, visualizing data,
-    understanding missing and outlier values within your data and performing simple data analysis. 
-    This extends 'teal' framework that supports reproducible research and analysis.
+Description: Prebuilt 'shiny' modules containing tools for viewing data,
+    visualizing data, understanding missing and outlier values within your
+    data and performing simple data analysis.  This extends 'teal'
+    framework that supports reproducible research and analysis.
 License: Apache License 2.0
 URL: https://insightsengineering.github.io/teal.modules.general/,
     https://github.com/insightsengineering/teal.modules.general/
@@ -26,7 +27,6 @@ Depends:
     ggplot2 (>= 3.4.0),
     R (>= 3.6),
     shiny (>= 1.6.0),
-    shinyTree,
     teal (>= 0.14.0.9027),
     teal.transform (>= 0.4.0.9011)
 Imports:
@@ -36,21 +36,21 @@ Imports:
     forcats (>= 1.0.0),
     grid,
     logger (>= 0.2.0),
-    magrittr (>= 1.5),
     scales,
     shinyjs,
+    shinyTree,
     shinyvalidate,
     shinyWidgets (>= 0.5.1),
     stats,
     stringr (>= 1.4.1),
     teal.code (>= 0.4.1.9009),
+    teal.data (>= 0.3.0.9018),
     teal.logger (>= 0.1.1),
     teal.reporter (>= 0.2.0),
     teal.widgets (>= 0.4.0),
     tern (>= 0.7.10),
     tibble (>= 2.0.0),
     tidyr (>= 0.8.3),
-    tidyselect,
     utils
 Suggests:
     broom (>= 0.7.10),
@@ -65,12 +65,10 @@ Suggests:
     knitr (>= 1.42),
     lattice (>= 0.18-4),
     MASS,
-    methods,
     nestcolor (>= 0.1.0),
     rlang (>= 1.0.0),
     rtables (>= 0.5.1),
     sparkline,
-    teal.data (>= 0.3.0.9018),
     testthat (>= 3.0.4)
 VignetteBuilder:
     knitr
@@ -82,7 +80,7 @@ Config/Needs/verdepcheck: haleyjeppson/ggmosaic, tidyverse/ggplot2,
     insightsengineering/teal.code, insightsengineering/teal.logger,
     insightsengineering/teal.reporter, insightsengineering/teal.transform,
     insightsengineering/teal.widgets, insightsengineering/tern,
-    tidyverse/tibble, tidyverse/tidyr, r-lib/tidyselect, tidymodels/broom,
+    tidyverse/tibble, tidyverse/tidyr, tidymodels/broom,
     daattali/colourpicker, daattali/ggExtra, aphalo/ggpmisc, aphalo/ggpp,
     baddstats/goftest, gridExtra, ramnathv/htmlwidgets, jeroen/jsonlite,
     yihui/knitr, deepayan/lattice, MASS, insightsengineering/nestcolor,
diff --git a/NAMESPACE b/NAMESPACE
index 28e4e2d48..86c4c2a5a 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -28,7 +28,6 @@ export(tm_variable_browser)
 import(ggmosaic)
 import(ggplot2)
 import(shiny)
-import(shinyTree)
 import(teal)
 import(teal.transform)
-importFrom(magrittr,"%>%")
+importFrom(dplyr,"%>%")
diff --git a/R/teal.modules.general.R b/R/teal.modules.general.R
index 74c5d52c2..a6cad3d13 100644
--- a/R/teal.modules.general.R
+++ b/R/teal.modules.general.R
@@ -6,10 +6,9 @@
 #' @import ggplot2
 #' @import ggmosaic
 #' @import shiny
-#' @import shinyTree
 #' @import teal
 #' @import teal.transform
-#' @importFrom magrittr %>%
+#' @importFrom dplyr %>%
 #'
 #'
 #' @name teal.modules.general
@@ -19,7 +18,7 @@
 # nolint start
 # Note ggmosaic (version <= 0.3.3) needs to be in DEPENDS as the following does not work if it is imported
 # df <- data.frame(x = c("A", "B", "C", "A"), y = c("Z", "Z", "W", "W"))
-# ggplot(df) +  ggmosaic::geom_mosaic(aes(x = ggmosaic::product(x), fill = y))
+# ggplot(df) + ggmosaic::geom_mosaic(aes(x = ggmosaic::product(x), fill = y))
 # nolint end
 
 # Needed to avoid R CMD note on no visible binding
diff --git a/R/tm_a_pca.R b/R/tm_a_pca.R
index 5fd0400b5..a21edc708 100644
--- a/R/tm_a_pca.R
+++ b/R/tm_a_pca.R
@@ -24,7 +24,7 @@
 #'
 #' data <- teal_data()
 #' data <- within(data, {
-#'   library(nestcolor)
+#'   require(nestcolor)
 #'   USArrests <- USArrests
 #' })
 #' datanames(data) <- "USArrests"
@@ -61,7 +61,7 @@
 #'
 #' data <- teal_data()
 #' data <- within(data, {
-#'   library(nestcolor)
+#'   require(nestcolor)
 #'   ADSL <- rADSL
 #' })
 #' datanames(data) <- "ADSL"
diff --git a/R/tm_a_regression.R b/R/tm_a_regression.R
index fbf45f765..26f3180ba 100644
--- a/R/tm_a_regression.R
+++ b/R/tm_a_regression.R
@@ -35,7 +35,7 @@
 #'
 #' data <- teal_data()
 #' data <- within(data, {
-#'   library(nestcolor)
+#'   require(nestcolor)
 #'   CO2 <- CO2
 #' })
 #' datanames(data) <- c("CO2")
@@ -80,7 +80,7 @@
 #'
 #' data <- teal_data()
 #' data <- within(data, {
-#'   library(nestcolor)
+#'   require(nestcolor)
 #'   ADSL <- rADSL
 #' })
 #' datanames(data) <- "ADSL"
diff --git a/R/tm_data_table.R b/R/tm_data_table.R
index b8b0bcf1e..df7888227 100644
--- a/R/tm_data_table.R
+++ b/R/tm_data_table.R
@@ -31,7 +31,7 @@
 #'
 #' data <- teal_data()
 #' data <- within(data, {
-#'   library(nestcolor)
+#'   require(nestcolor)
 #'   iris <- iris
 #' })
 #' datanames(data) <- c("iris")
@@ -54,7 +54,7 @@
 #' # CDISC data example
 #' data <- teal_data()
 #' data <- within(data, {
-#'   library(nestcolor)
+#'   require(nestcolor)
 #'   ADSL <- rADSL
 #' })
 #' datanames(data) <- "ADSL"
@@ -301,7 +301,7 @@ srv_data_table <- function(id,
       teal::validate_has_data(df, min_nrow = 1L, msg = paste("data", dataname, "is empty"))
 
       dataframe_selected <- if (if_distinct()) {
-        dplyr::count(df, dplyr::across(tidyselect::all_of(variables)))
+        dplyr::count(df, dplyr::across(dplyr::all_of(variables)))
       } else {
         df[variables]
       }
diff --git a/R/tm_front_page.R b/R/tm_front_page.R
index aa755d64f..e2d7def39 100644
--- a/R/tm_front_page.R
+++ b/R/tm_front_page.R
@@ -19,7 +19,7 @@
 #'
 #' data <- teal_data()
 #' data <- within(data, {
-#'   library(nestcolor)
+#'   require(nestcolor)
 #'   ADSL <- teal.modules.general::rADSL
 #'   attr(ADSL, "metadata") <- list("Author" = "NEST team", "data_source" = "synthetic data")
 #' })
diff --git a/R/tm_g_association.R b/R/tm_g_association.R
index 9004fe84f..e262cb584 100644
--- a/R/tm_g_association.R
+++ b/R/tm_g_association.R
@@ -24,7 +24,7 @@
 #'
 #' data <- teal_data()
 #' data <- within(data, {
-#'   library(nestcolor)
+#'   require(nestcolor)
 #'   CO2 <- CO2
 #'   factors <- names(Filter(isTRUE, vapply(CO2, is.factor, logical(1L))))
 #'   CO2[factors] <- lapply(CO2[factors], as.character)
@@ -69,7 +69,7 @@
 #'
 #' data <- teal_data()
 #' data <- within(data, {
-#'   library(nestcolor)
+#'   require(nestcolor)
 #'   ADSL <- rADSL
 #' })
 #' datanames(data) <- "ADSL"
diff --git a/R/tm_g_bivariate.R b/R/tm_g_bivariate.R
index ed49dd21e..fc82181c5 100644
--- a/R/tm_g_bivariate.R
+++ b/R/tm_g_bivariate.R
@@ -49,7 +49,7 @@
 #'
 #' data <- teal_data()
 #' data <- within(data, {
-#'   library(nestcolor)
+#'   require(nestcolor)
 #'   CO2 <- data.frame(CO2)
 #' })
 #' datanames(data) <- c("CO2")
@@ -112,7 +112,7 @@
 #'
 #' data <- teal_data()
 #' data <- within(data, {
-#'   library(nestcolor)
+#'   require(nestcolor)
 #'   ADSL <- rADSL
 #' })
 #' datanames(data) <- c("ADSL")
diff --git a/R/tm_g_response.R b/R/tm_g_response.R
index 517c80edd..386e2aa17 100644
--- a/R/tm_g_response.R
+++ b/R/tm_g_response.R
@@ -30,7 +30,7 @@
 #'
 #' data <- teal_data()
 #' data <- within(data, {
-#'   library(nestcolor)
+#'   require(nestcolor)
 #'   mtcars <- mtcars
 #'   for (v in c("cyl", "vs", "am", "gear")) {
 #'     mtcars[[v]] <- as.factor(mtcars[[v]])
@@ -78,7 +78,7 @@
 #'
 #' data <- teal_data()
 #' data <- within(data, {
-#'   library(nestcolor)
+#'   require(nestcolor)
 #'   ADSL <- rADSL
 #' })
 #' datanames(data) <- c("ADSL")
diff --git a/R/tm_g_scatterplot.R b/R/tm_g_scatterplot.R
index 62d7ccbf7..7f1f5d84d 100644
--- a/R/tm_g_scatterplot.R
+++ b/R/tm_g_scatterplot.R
@@ -39,7 +39,7 @@
 #'
 #' data <- teal_data()
 #' data <- within(data, {
-#'   library(nestcolor)
+#'   require(nestcolor)
 #'   CO2 <- CO2
 #' })
 #' datanames(data) <- "CO2"
@@ -128,7 +128,7 @@
 #'
 #' data <- teal_data()
 #' data <- within(data, {
-#'   library(nestcolor)
+#'   require(nestcolor)
 #'   ADSL <- rADSL
 #' })
 #' datanames(data) <- c("ADSL")
diff --git a/R/tm_missing_data.R b/R/tm_missing_data.R
index 4d733fee0..a5060206d 100644
--- a/R/tm_missing_data.R
+++ b/R/tm_missing_data.R
@@ -28,7 +28,7 @@
 #' # general example data
 #' data <- teal_data()
 #' data <- within(data, {
-#'   library(nestcolor)
+#'   require(nestcolor)
 #'
 #'   add_nas <- function(x) {
 #'     x[sample(seq_along(x), floor(length(x) * runif(1, .05, .17)))] <- NA
@@ -56,7 +56,7 @@
 #' # CDISC example data
 #' data <- teal_data()
 #' data <- within(data, {
-#'   library(nestcolor)
+#'   require(nestcolor)
 #'   ADSL <- rADSL
 #'   ADRS <- rADRS
 #' })
@@ -640,7 +640,7 @@ srv_missing_data <- function(id, data, reporter, filter_panel_api, dataname, par
           substitute(
             expr = summary_plot_obs <- data_frame_call[, analysis_vars] %>%
               dplyr::summarise_all(list(function(x) sum(is.na(x)))) %>%
-              tidyr::pivot_longer(tidyselect::everything(), names_to = "col", values_to = "n_na") %>%
+              tidyr::pivot_longer(dplyr::everything(), names_to = "col", values_to = "n_na") %>%
               dplyr::mutate(n_not_na = nrow(ANL) - n_na) %>%
               tidyr::pivot_longer(-col, names_to = "isna", values_to = "n") %>%
               dplyr::mutate(isna = isna == "n_na", n_pct = n / nrow(ANL) * 100),
@@ -733,7 +733,7 @@ srv_missing_data <- function(id, data, reporter, filter_panel_api, dataname, par
               summary_plot_patients <- ANL[, c(parent_keys, analysis_vars)] %>%
                 dplyr::group_by_at(parent_keys) %>%
                 dplyr::summarise_all(anyNA) %>%
-                tidyr::pivot_longer(cols = !tidyselect::all_of(parent_keys), names_to = "col", values_to = "anyna") %>%
+                tidyr::pivot_longer(cols = !dplyr::all_of(parent_keys), names_to = "col", values_to = "anyna") %>%
                 dplyr::group_by_at(c("col")) %>%
                 dplyr::summarise(count_na = sum(anyna)) %>%
                 dplyr::mutate(count_not_na = ndistinct_subjects - count_na) %>%
@@ -1041,7 +1041,7 @@ srv_missing_data <- function(id, data, reporter, filter_panel_api, dataname, par
 
               summary_data <- dplyr::summarise_all(summary_data, summ_fn) %>%
                 dplyr::mutate(group_var_name := paste0(group_var, ":", group_var_name, "(N=", count_data$n, ")")) %>%
-                tidyr::pivot_longer(!tidyselect::all_of(group_var), names_to = "Variable", values_to = "out") %>%
+                tidyr::pivot_longer(!dplyr::all_of(group_var), names_to = "Variable", values_to = "out") %>%
                 tidyr::pivot_wider(names_from = group_var, values_from = "out") %>%
                 dplyr::mutate(`Variable label` = create_cols_labels(Variable, just_label = TRUE), .after = Variable)
             },
@@ -1056,7 +1056,7 @@ srv_missing_data <- function(id, data, reporter, filter_panel_api, dataname, par
           substitute(
             expr = summary_data <- ANL %>%
               dplyr::summarise_all(summ_fn) %>%
-              tidyr::pivot_longer(tidyselect::everything(),
+              tidyr::pivot_longer(dplyr::everything(),
                 names_to = "Variable",
                 values_to = paste0("Missing (N=", nrow(ANL), ")")
               ) %>%
@@ -1119,7 +1119,7 @@ srv_missing_data <- function(id, data, reporter, filter_panel_api, dataname, par
             # order subjects by decreasing number of missing and then by
             # missingness pattern (defined using sha1)
             order_subjects <- summary_plot_patients %>%
-              dplyr::select(-"id", -tidyselect::all_of(parent_keys)) %>%
+              dplyr::select(-"id", -dplyr::all_of(parent_keys)) %>%
               dplyr::transmute(
                 id = dplyr::row_number(),
                 number_NA = apply(., 1, sum),
@@ -1130,7 +1130,7 @@ srv_missing_data <- function(id, data, reporter, filter_panel_api, dataname, par
 
             # order columns by decreasing percent of missing values
             ordered_columns <- summary_plot_patients %>%
-              dplyr::select(-"id", -tidyselect::all_of(parent_keys)) %>%
+              dplyr::select(-"id", -dplyr::all_of(parent_keys)) %>%
               dplyr::summarise(
                 column = create_cols_labels(colnames(.)),
                 na_count = apply(., MARGIN = 2, FUN = sum),
@@ -1139,7 +1139,7 @@ srv_missing_data <- function(id, data, reporter, filter_panel_api, dataname, par
               dplyr::arrange(na_percent, dplyr::desc(column))
 
             summary_plot_patients <- summary_plot_patients %>%
-              tidyr::gather("col", "isna", -"id", -tidyselect::all_of(parent_keys)) %>%
+              tidyr::gather("col", "isna", -"id", -dplyr::all_of(parent_keys)) %>%
               dplyr::mutate(col = create_cols_labels(col))
           })
         ) %>%
diff --git a/man/tm_a_pca.Rd b/man/tm_a_pca.Rd
index 0242a7910..c152ab5fe 100644
--- a/man/tm_a_pca.Rd
+++ b/man/tm_a_pca.Rd
@@ -72,7 +72,7 @@ library(teal.widgets)
 
 data <- teal_data()
 data <- within(data, {
-  library(nestcolor)
+  require(nestcolor)
   USArrests <- USArrests
 })
 datanames(data) <- "USArrests"
@@ -109,7 +109,7 @@ library(teal.widgets)
 
 data <- teal_data()
 data <- within(data, {
-  library(nestcolor)
+  require(nestcolor)
   ADSL <- rADSL
 })
 datanames(data) <- "ADSL"
diff --git a/man/tm_a_regression.Rd b/man/tm_a_regression.Rd
index 8777542a4..053246eea 100644
--- a/man/tm_a_regression.Rd
+++ b/man/tm_a_regression.Rd
@@ -86,7 +86,7 @@ library(teal.widgets)
 
 data <- teal_data()
 data <- within(data, {
-  library(nestcolor)
+  require(nestcolor)
   CO2 <- CO2
 })
 datanames(data) <- c("CO2")
@@ -131,7 +131,7 @@ library(teal.widgets)
 
 data <- teal_data()
 data <- within(data, {
-  library(nestcolor)
+  require(nestcolor)
   ADSL <- rADSL
 })
 datanames(data) <- "ADSL"
diff --git a/man/tm_data_table.Rd b/man/tm_data_table.Rd
index 064aaaa8b..8cbdde1f0 100644
--- a/man/tm_data_table.Rd
+++ b/man/tm_data_table.Rd
@@ -60,7 +60,7 @@ Note though that sorting of numeric columns with \code{NA}/\code{Inf} will be le
 
 data <- teal_data()
 data <- within(data, {
-  library(nestcolor)
+  require(nestcolor)
   iris <- iris
 })
 datanames(data) <- c("iris")
@@ -83,7 +83,7 @@ if (interactive()) {
 # CDISC data example
 data <- teal_data()
 data <- within(data, {
-  library(nestcolor)
+  require(nestcolor)
   ADSL <- rADSL
 })
 datanames(data) <- "ADSL"
diff --git a/man/tm_front_page.Rd b/man/tm_front_page.Rd
index 0efa390d0..20499592a 100644
--- a/man/tm_front_page.Rd
+++ b/man/tm_front_page.Rd
@@ -42,7 +42,7 @@ This \code{teal} module creates a simple front page for \code{teal} applications
 
 data <- teal_data()
 data <- within(data, {
-  library(nestcolor)
+  require(nestcolor)
   ADSL <- teal.modules.general::rADSL
   attr(ADSL, "metadata") <- list("Author" = "NEST team", "data_source" = "synthetic data")
 })
diff --git a/man/tm_g_association.Rd b/man/tm_g_association.Rd
index d5182e335..1bfeb9c64 100644
--- a/man/tm_g_association.Rd
+++ b/man/tm_g_association.Rd
@@ -69,7 +69,7 @@ library(teal.widgets)
 
 data <- teal_data()
 data <- within(data, {
-  library(nestcolor)
+  require(nestcolor)
   CO2 <- CO2
   factors <- names(Filter(isTRUE, vapply(CO2, is.factor, logical(1L))))
   CO2[factors] <- lapply(CO2[factors], as.character)
@@ -114,7 +114,7 @@ library(teal.widgets)
 
 data <- teal_data()
 data <- within(data, {
-  library(nestcolor)
+  require(nestcolor)
   ADSL <- rADSL
 })
 datanames(data) <- "ADSL"
diff --git a/man/tm_g_bivariate.Rd b/man/tm_g_bivariate.Rd
index f1d0398d6..6ebecdd90 100644
--- a/man/tm_g_bivariate.Rd
+++ b/man/tm_g_bivariate.Rd
@@ -114,7 +114,7 @@ library(teal.widgets)
 
 data <- teal_data()
 data <- within(data, {
-  library(nestcolor)
+  require(nestcolor)
   CO2 <- data.frame(CO2)
 })
 datanames(data) <- c("CO2")
@@ -177,7 +177,7 @@ library(teal.widgets)
 
 data <- teal_data()
 data <- within(data, {
-  library(nestcolor)
+  require(nestcolor)
   ADSL <- rADSL
 })
 datanames(data) <- c("ADSL")
diff --git a/man/tm_g_response.Rd b/man/tm_g_response.Rd
index 71d994bb6..cab67f975 100644
--- a/man/tm_g_response.Rd
+++ b/man/tm_g_response.Rd
@@ -86,7 +86,7 @@ library(teal.widgets)
 
 data <- teal_data()
 data <- within(data, {
-  library(nestcolor)
+  require(nestcolor)
   mtcars <- mtcars
   for (v in c("cyl", "vs", "am", "gear")) {
     mtcars[[v]] <- as.factor(mtcars[[v]])
@@ -134,7 +134,7 @@ library(teal.widgets)
 
 data <- teal_data()
 data <- within(data, {
-  library(nestcolor)
+  require(nestcolor)
   ADSL <- rADSL
 })
 datanames(data) <- c("ADSL")
diff --git a/man/tm_g_scatterplot.Rd b/man/tm_g_scatterplot.Rd
index 16d14c6b0..54e0dfd79 100644
--- a/man/tm_g_scatterplot.Rd
+++ b/man/tm_g_scatterplot.Rd
@@ -100,7 +100,7 @@ library(teal.widgets)
 
 data <- teal_data()
 data <- within(data, {
-  library(nestcolor)
+  require(nestcolor)
   CO2 <- CO2
 })
 datanames(data) <- "CO2"
@@ -189,7 +189,7 @@ library(teal.widgets)
 
 data <- teal_data()
 data <- within(data, {
-  library(nestcolor)
+  require(nestcolor)
   ADSL <- rADSL
 })
 datanames(data) <- c("ADSL")
diff --git a/man/tm_missing_data.Rd b/man/tm_missing_data.Rd
index 9460399f5..08c9090f9 100644
--- a/man/tm_missing_data.Rd
+++ b/man/tm_missing_data.Rd
@@ -66,7 +66,7 @@ tm_missing_data_module <- tm_missing_data(
 # general example data
 data <- teal_data()
 data <- within(data, {
-  library(nestcolor)
+  require(nestcolor)
 
   add_nas <- function(x) {
     x[sample(seq_along(x), floor(length(x) * runif(1, .05, .17)))] <- NA
@@ -94,7 +94,7 @@ if (interactive()) {
 # CDISC example data
 data <- teal_data()
 data <- within(data, {
-  library(nestcolor)
+  require(nestcolor)
   ADSL <- rADSL
   ADRS <- rADRS
 })

From 2d89cfb3d53c9617f52e45ef371218f7f9a1da72 Mon Sep 17 00:00:00 2001
From: Aleksander Chlebowski <114988527+chlebowa@users.noreply.github.com>
Date: Thu, 22 Feb 2024 15:47:16 +0100
Subject: [PATCH 16/62] missed commit in #663 (#672)

missed commit

---------

Signed-off-by: Aleksander Chlebowski <114988527+chlebowa@users.noreply.github.com>
---
 DESCRIPTION | 1 +
 1 file changed, 1 insertion(+)

diff --git a/DESCRIPTION b/DESCRIPTION
index 2e5aafaed..695aed2e8 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -51,6 +51,7 @@ Imports:
     tern (>= 0.7.10),
     tibble (>= 2.0.0),
     tidyr (>= 0.8.3),
+    tools,
     utils
 Suggests:
     broom (>= 0.7.10),

From 2ac9a4d735a1ba0bb64226564c4b205520aeffbd Mon Sep 17 00:00:00 2001
From: Aleksander Chlebowski <114988527+chlebowa@users.noreply.github.com>
Date: Fri, 23 Feb 2024 10:56:12 +0100
Subject: [PATCH 17/62] 658 remove var labels@pre release@main (#673)

Closes #658

All instances of `var_labels` were replaced with
`teal.data::col_labels`.
Source for `var_labels` was removed.
---
 R/tm_a_pca.R            |  2 +-
 R/tm_missing_data.R     |  2 +-
 R/tm_variable_browser.R |  2 +-
 R/utils.R               | 48 -----------------------------------------
 man/var_labels.Rd       | 27 -----------------------
 5 files changed, 3 insertions(+), 78 deletions(-)
 delete mode 100644 man/var_labels.Rd

diff --git a/R/tm_a_pca.R b/R/tm_a_pca.R
index a21edc708..a692e589f 100644
--- a/R/tm_a_pca.R
+++ b/R/tm_a_pca.R
@@ -294,7 +294,7 @@ srv_a_pca <- function(id, data, reporter, filter_panel_api, dat, plot_height, pl
       response[[i]]$select$multiple <- FALSE
       response[[i]]$select$always_selected <- NULL
       response[[i]]$select$selected <- NULL
-      response[[i]]$select$choices <- var_labels(isolate(data())[[response[[i]]$dataname]])
+      response[[i]]$select$choices <- teal.data::col_labels(isolate(data())[[response[[i]]$dataname]])
       response[[i]]$select$choices <- setdiff(
         response[[i]]$select$choices,
         unlist(teal.data::join_keys(isolate(data()))[[response[[i]]$dataname]])
diff --git a/R/tm_missing_data.R b/R/tm_missing_data.R
index a5060206d..4e856dffd 100644
--- a/R/tm_missing_data.R
+++ b/R/tm_missing_data.R
@@ -495,7 +495,7 @@ srv_missing_data <- function(id, data, reporter, filter_panel_api, dataname, par
             },
           env = list(
             new_col_name = new_col_name,
-            column_labels_value = c(var_labels(data_r())[selected_vars()],
+            column_labels_value = c(teal.data::col_labels(data_r())[selected_vars()],
               new_col_name = new_col_name
             )
           )
diff --git a/R/tm_variable_browser.R b/R/tm_variable_browser.R
index 239dc26eb..2e5a53ed5 100644
--- a/R/tm_variable_browser.R
+++ b/R/tm_variable_browser.R
@@ -1078,7 +1078,7 @@ get_plotted_data <- function(input, plot_var, data) {
   varname <- plot_var$variable[[dataset_name]]
   df <- data()[[dataset_name]]
 
-  var_description <- var_labels(df)[[varname]]
+  var_description <- teal.data::col_labels(df)[[varname]]
   list(data = df[[varname]], var_description = var_description)
 }
 
diff --git a/R/utils.R b/R/utils.R
index 0262e0b49..ef6702ee6 100644
--- a/R/utils.R
+++ b/R/utils.R
@@ -272,54 +272,6 @@ include_css_files <- function(pattern = "*") {
 }
 
 
-#' Get Label Attributes of Variables in a \code{data.frame}
-#'
-#' Variable labels can be stored as a \code{label} attribute for each variable.
-#' This functions returns a named character vector with the variable labels
-#' (empty sting if not specified)
-#'
-#' @param x a \code{data.frame} object
-#' @param fill boolean in case the \code{label} attribute does not exist if
-#'   \code{TRUE} the variable names is returned, otherwise \code{NA}
-#'
-#' @return a named character vector with the variable labels, the names
-#'   correspond to the variable names
-#'
-#' @note the `formatters` package is the source of the function.
-#'
-#' @keywords internal
-var_labels <- function(x, fill = FALSE) {
-  stopifnot(is.data.frame(x))
-  if (NCOL(x) == 0) {
-    return(character())
-  }
-
-  y <- Map(function(col, colname) {
-    label <- attr(col, "label")
-
-    if (is.null(label)) {
-      if (fill) {
-        colname
-      } else {
-        NA_character_
-      }
-    } else {
-      if (!is.character(label) && !(length(label) == 1)) {
-        stop("label for variable ", colname, "is not a character string")
-      }
-      as.vector(label)
-    }
-  }, x, colnames(x))
-
-  labels <- unlist(y, recursive = FALSE, use.names = TRUE)
-
-  if (!is.character(labels)) {
-    stop("label extraction failed")
-  }
-
-  labels
-}
-
 #' Get a string with java-script code checking if the specific tab is clicked
 #' @description will be the input for `shiny::conditionalPanel()`
 #' @param id `character(1)` the id of the tab panel with tabs.
diff --git a/man/var_labels.Rd b/man/var_labels.Rd
deleted file mode 100644
index 151778733..000000000
--- a/man/var_labels.Rd
+++ /dev/null
@@ -1,27 +0,0 @@
-% Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/utils.R
-\name{var_labels}
-\alias{var_labels}
-\title{Get Label Attributes of Variables in a \code{data.frame}}
-\usage{
-var_labels(x, fill = FALSE)
-}
-\arguments{
-\item{x}{a \code{data.frame} object}
-
-\item{fill}{boolean in case the \code{label} attribute does not exist if
-\code{TRUE} the variable names is returned, otherwise \code{NA}}
-}
-\value{
-a named character vector with the variable labels, the names
-correspond to the variable names
-}
-\description{
-Variable labels can be stored as a \code{label} attribute for each variable.
-This functions returns a named character vector with the variable labels
-(empty sting if not specified)
-}
-\note{
-the \code{formatters} package is the source of the function.
-}
-\keyword{internal}

From 3118bcb2e9c9f3b166d07abc4dae2fe83d363969 Mon Sep 17 00:00:00 2001
From: Vedha Viyash <49812166+vedhav@users.noreply.github.com>
Date: Mon, 26 Feb 2024 16:16:05 +0530
Subject: [PATCH 18/62] docs: update the vignette author to "NEST CoreDev"
 (#679)

part of #624
---
 vignettes/teal-modules-general.Rmd     | 3 +--
 vignettes/using-association-plot.Rmd   | 3 +--
 vignettes/using-bivariate-plot.Rmd     | 3 +--
 vignettes/using-cross-table.Rmd        | 3 +--
 vignettes/using-data-table.Rmd         | 3 +--
 vignettes/using-outliers-module.Rmd    | 3 +--
 vignettes/using-regression-plots.Rmd   | 3 +--
 vignettes/using-response-plot.Rmd      | 3 +--
 vignettes/using-scatterplot-matrix.Rmd | 3 +--
 vignettes/using-scatterplot.Rmd        | 3 +--
 10 files changed, 10 insertions(+), 20 deletions(-)

diff --git a/vignettes/teal-modules-general.Rmd b/vignettes/teal-modules-general.Rmd
index bd1582059..b125e653c 100644
--- a/vignettes/teal-modules-general.Rmd
+++ b/vignettes/teal-modules-general.Rmd
@@ -1,7 +1,6 @@
 ---
 title: "Getting started with teal.modules.general"
-author: "NEST CoreDev Team"
-date: "01.04.2022"
+author: "NEST CoreDev"
 output: rmarkdown::html_vignette
 vignette: >
   %\VignetteIndexEntry{Getting started with teal.modules.general}
diff --git a/vignettes/using-association-plot.Rmd b/vignettes/using-association-plot.Rmd
index d73b9ab0d..5df6c154d 100644
--- a/vignettes/using-association-plot.Rmd
+++ b/vignettes/using-association-plot.Rmd
@@ -1,7 +1,6 @@
 ---
 title: "Using association plot"
-author: "Dawid Kałędkowski"
-date: "`r Sys.Date()`"
+author: "NEST CoreDev"
 output: rmarkdown::html_vignette
 runtime: shiny
 vignette: >
diff --git a/vignettes/using-bivariate-plot.Rmd b/vignettes/using-bivariate-plot.Rmd
index 021f329b6..74cee6e7f 100644
--- a/vignettes/using-bivariate-plot.Rmd
+++ b/vignettes/using-bivariate-plot.Rmd
@@ -1,7 +1,6 @@
 ---
 title: "Using bivariate plot"
-author: "Dawid Kałędkowski"
-date: "`r Sys.Date()`"
+author: "NEST CoreDev"
 output: rmarkdown::html_vignette
 runtime: shiny
 vignette: >
diff --git a/vignettes/using-cross-table.Rmd b/vignettes/using-cross-table.Rmd
index 9d19e8167..86307941a 100644
--- a/vignettes/using-cross-table.Rmd
+++ b/vignettes/using-cross-table.Rmd
@@ -1,7 +1,6 @@
 ---
 title: "Using cross table"
-author: "Dawid Kałędkowski"
-date: "`r Sys.Date()`"
+author: "NEST CoreDev"
 output: rmarkdown::html_vignette
 runtime: shiny
 vignette: >
diff --git a/vignettes/using-data-table.Rmd b/vignettes/using-data-table.Rmd
index e6bedc886..1ec5b9eac 100644
--- a/vignettes/using-data-table.Rmd
+++ b/vignettes/using-data-table.Rmd
@@ -1,7 +1,6 @@
 ---
 title: "Using data table"
-author: "coreDev team"
-date: "`r Sys.Date()`"
+author: "NEST CoreDev"
 output: rmarkdown::html_vignette
 runtime: shiny
 vignette: >
diff --git a/vignettes/using-outliers-module.Rmd b/vignettes/using-outliers-module.Rmd
index ee9136f8b..151797aa6 100644
--- a/vignettes/using-outliers-module.Rmd
+++ b/vignettes/using-outliers-module.Rmd
@@ -1,7 +1,6 @@
 ---
 title: "Using outliers module"
-author: "Mahmoud Hallal"
-date: "`r Sys.Date()`"
+author: "NEST CoreDev"
 output: rmarkdown::html_vignette
 runtime: shiny
 vignette: >
diff --git a/vignettes/using-regression-plots.Rmd b/vignettes/using-regression-plots.Rmd
index b2515f1e1..18fbed914 100644
--- a/vignettes/using-regression-plots.Rmd
+++ b/vignettes/using-regression-plots.Rmd
@@ -1,7 +1,6 @@
 ---
 title: "Using regression plots"
-author: "Dawid Kałędkowski"
-date: "`r Sys.Date()`"
+author: "NEST CoreDev"
 output: rmarkdown::html_vignette
 runtime: shiny
 vignette: >
diff --git a/vignettes/using-response-plot.Rmd b/vignettes/using-response-plot.Rmd
index 14baa6ecb..e9af17c4b 100644
--- a/vignettes/using-response-plot.Rmd
+++ b/vignettes/using-response-plot.Rmd
@@ -1,7 +1,6 @@
 ---
 title: "Using response plot"
-author: "Dawid Kałędkowski"
-date: "`r Sys.Date()`"
+author: "NEST CoreDev"
 output: rmarkdown::html_vignette
 runtime: shiny
 vignette: >
diff --git a/vignettes/using-scatterplot-matrix.Rmd b/vignettes/using-scatterplot-matrix.Rmd
index ee6a2ff75..7b3167a68 100644
--- a/vignettes/using-scatterplot-matrix.Rmd
+++ b/vignettes/using-scatterplot-matrix.Rmd
@@ -1,7 +1,6 @@
 ---
 title: "Using scatterplot matrix"
-author: "Dawid Kałędkowski"
-date: "`r Sys.Date()`"
+author: "NEST CoreDev"
 output: rmarkdown::html_vignette
 runtime: shiny
 vignette: >
diff --git a/vignettes/using-scatterplot.Rmd b/vignettes/using-scatterplot.Rmd
index 276a8ca11..32c1ec3d1 100644
--- a/vignettes/using-scatterplot.Rmd
+++ b/vignettes/using-scatterplot.Rmd
@@ -1,7 +1,6 @@
 ---
 title: "Using scatterplot"
-author: "Dawid Kałędkowski"
-date: "`r Sys.Date()`"
+author: "NEST CoreDev"
 output: rmarkdown::html_vignette
 runtime: shiny
 vignette: >

From 109065ea80d24820f6ef469a0edc312bfc3aa6f6 Mon Sep 17 00:00:00 2001
From: kartikeya kirar <kirar.kartikeya1@gmail.com>
Date: Mon, 26 Feb 2024 16:39:25 +0530
Subject: [PATCH 19/62] pre-release `tm_variable_browser` document update 
 (#652)

part of
https://github.com/insightsengineering/teal.modules.general/issues/624
---
 R/tm_variable_browser.R    | 143 +++++++++++--------------------------
 man/create_sparklines.Rd   |  22 +-----
 man/tm_variable_browser.Rd |  37 ++++------
 man/validate_input.Rd      |   2 +-
 man/var_missings_info.Rd   |   4 +-
 5 files changed, 61 insertions(+), 147 deletions(-)

diff --git a/R/tm_variable_browser.R b/R/tm_variable_browser.R
index 2e5a53ed5..bc8bd03d7 100644
--- a/R/tm_variable_browser.R
+++ b/R/tm_variable_browser.R
@@ -1,37 +1,28 @@
-#' Variable Browser Teal Module
+#' Variable browser `teal` module
 #'
-#' The variable browser provides a table with variable names and labels and a
-#' plot that visualizes the content of a particular variable.
-#' specifically designed for use with `data.frames`.
+#' Module provides provides a detailed summary and visualization of variable distributions
+#' for `data.frame` objects, with interactive features to customize analysis.
 #'
-#' @details Numeric columns with fewer than 30 distinct values can be treated as either factors
-#' or numbers with a checkbox allowing users to switch how they are treated (if < 6 unique values
-#' then the default is categorical, otherwise it is numeric).
+#' Numeric columns with fewer than 30 distinct values can be treated as either discrete
+#' or continuous with a checkbox allowing users to switch how they are treated(if < 6 unique values
+#' then the default is discrete, otherwise it is continuous).
 #'
 #' @inheritParams teal::module
 #' @inheritParams shared_params
-#' @param parent_dataname (`character(1)`) If this `dataname` exists in `datasets_selected`
-#'   then an extra checkbox will be shown to allow users to not show variables in other datasets
-#'   which exist in this `dataname`.
-#'   This is typically used to remove `ADSL` columns in `CDISC` data. In non `CDISC` data this
-#'   can be ignored. Defaults to `"ADSL"`.
-#' @param datasets_selected (`character`) A vector of datasets which should be
-#'   shown and in what order. Names in the vector have to correspond with datasets names.
-#'   If vector of length zero (default) then all datasets are shown.
-#'   Note: Only datasets of the `data.frame` class are compatible; using other types will cause an error.
-#'
-#' @aliases
-#'   tm_variable_browser_ui,
-#'   tm_variable_browser_srv,
-#'   tm_variable_browser,
-#'   variable_browser_ui,
-#'   variable_browser_srv,
-#'   variable_browser
+#' @param parent_dataname (`character(1)`) string specifying a parent dataset.
+#' If it exists in `datasets_selected`then an extra checkbox will be shown to
+#' allow users to not show variables in other datasets which exist in this `dataname`.
+#' This is typically used to remove `ADSL` columns in `CDISC` data.
+#' In non `CDISC` data this can be ignored. Defaults to `"ADSL"`.
+#' @param datasets_selected (`character`) vector of datasets which should be
+#' shown, in order. Names must correspond with datasets names.
+#' If vector of length zero (default) then all datasets are shown.
+#' Note: Only `data.frame` objects are compatible; using other types will cause an error.
 #'
 #' @examples
 #' library(teal.widgets)
 #'
-#' # module specification used in apps below
+#' # Module specification used in apps below
 #' tm_variable_browser_module <- tm_variable_browser(
 #'   label = "Variable browser",
 #'   ggplot2_args = ggplot2_args(
@@ -116,7 +107,9 @@ tm_variable_browser <- function(label = "Variable Browser",
   )
 }
 
-# ui function
+# UI function for the variable browser module.
+#' @noRd
+#' @keywords internal
 ui_variable_browser <- function(id,
                                 pre_output = NULL,
                                 post_output = NULL) {
@@ -186,6 +179,9 @@ ui_variable_browser <- function(id,
   )
 }
 
+# Server function for the variable browser module.
+#' @noRd
+#' @keywords internal
 srv_variable_browser <- function(id,
                                  data,
                                  reporter,
@@ -533,12 +529,12 @@ srv_variable_browser <- function(id,
 
 #' Summarizes missings occurrence
 #'
-#' Summarizes missings occurrence in vector
+#' Summarizes missings occurrence in vector.
 #' @param x vector of any type and length
-#' @return text describing \code{NA} occurrence.
+#' @return Text describing \code{NA} occurrence.
 #' @keywords internal
 var_missings_info <- function(x) {
-  return(sprintf("%s [%s%%]", sum(is.na(x)), round(mean(is.na(x) * 100), 2)))
+  sprintf("%s [%s%%]", sum(is.na(x)), round(mean(is.na(x) * 100), 2))
 }
 
 #' S3 generic for \code{sparkline} widget HTML
@@ -551,6 +547,8 @@ var_missings_info <- function(x) {
 #' @param width \code{numeric} the width of the \code{sparkline} widget (pixels)
 #' @param ... \code{list} additional options passed to bar plots of \code{jquery.sparkline};  see
 #' \href{https://omnipotent.net/jquery.sparkline/#common}{\code{jquery.sparkline docs}}
+#' @param bar_spacing \code{numeric} the spacing between the bars (in pixels)
+#' @param bar_width \code{numeric} the width of the bars (in pixels)
 #'
 #' @return character variable containing the HTML code of the \code{sparkline} HTML widget
 #' @keywords internal
@@ -561,25 +559,13 @@ create_sparklines <- function(arr, width = 150, ...) {
   UseMethod("create_sparklines")
 }
 
-#' Default method for \code{\link{create_sparklines}}
-#'
-#'
 #' @export
-#' @keywords internal
 #' @rdname create_sparklines
 create_sparklines.default <- function(arr, width = 150, ...) {
-  return(as.character(tags$code("unsupported variable type", class = "text-blue")))
+  as.character(tags$code("unsupported variable type", class = "text-blue"))
 }
 
-#' Generates the HTML code for the \code{sparkline} widget
-#'
-#' @param bar_spacing \code{numeric} the spacing between the bars (in pixels)
-#' @param bar_width \code{numeric} the width of the bars (in pixels)
-#'
-#' @return \code{character} with HTML code for the \code{sparkline} widget
-#'
 #' @export
-#' @keywords internal
 #' @rdname create_sparklines
 create_sparklines.Date <- function(arr, width = 150, bar_spacing = 5, bar_width = 20, ...) {
   arr_num <- as.numeric(arr)
@@ -610,16 +596,7 @@ create_sparklines.Date <- function(arr, width = 150, bar_spacing = 5, bar_width
   )
 }
 
-#' Generates the HTML code for the \code{sparkline} widget
-#'
-#'
-#' @param bar_spacing \code{numeric} the spacing between the bars (in pixels)
-#' @param bar_width \code{numeric} the width of the bars (in pixels)
-#'
-#' @return \code{character} with HTML code for the \code{sparkline} widget
-#'
 #' @export
-#' @keywords internal
 #' @rdname create_sparklines
 create_sparklines.POSIXct <- function(arr, width = 150, bar_spacing = 5, bar_width = 20, ...) {
   arr_num <- as.numeric(arr)
@@ -650,16 +627,7 @@ create_sparklines.POSIXct <- function(arr, width = 150, bar_spacing = 5, bar_wid
   )
 }
 
-#' Generates the HTML code for the \code{sparkline} widget
-#'
-#'
-#' @param bar_spacing \code{numeric} the spacing between the bars (in pixels)
-#' @param bar_width \code{numeric} the width of the bars (in pixels)
-#'
-#' @return \code{character} with HTML code for the \code{sparkline} widget
-#'
 #' @export
-#' @keywords internal
 #' @rdname create_sparklines
 create_sparklines.POSIXlt <- function(arr, width = 150, bar_spacing = 5, bar_width = 20, ...) {
   arr_num <- as.numeric(arr)
@@ -690,46 +658,19 @@ create_sparklines.POSIXlt <- function(arr, width = 150, bar_spacing = 5, bar_wid
   )
 }
 
-
-#' Generates the HTML code for the \code{sparkline} widget
-#'
-#' Coerces a character vector to factor and delegates to the \code{create_sparklines.factor}
-#'
-#'
-#' @return \code{character} with HTML code for the \code{sparkline} widget
-#'
 #' @export
-#' @keywords internal
 #' @rdname create_sparklines
 create_sparklines.character <- function(arr, ...) {
-  return(create_sparklines(as.factor(arr)))
+  create_sparklines(as.factor(arr))
 }
 
-
-#' Generates the HTML code for the \code{sparkline} widget
-#'
-#' Coerces logical vector to factor and delegates to the \code{create_sparklines.factor}
-#'
-#'
-#' @return \code{character} with HTML code for the \code{sparkline} widget
-#'
 #' @export
-#' @keywords internal
 #' @rdname create_sparklines
 create_sparklines.logical <- function(arr, ...) {
-  return(create_sparklines(as.factor(arr)))
+  create_sparklines(as.factor(arr))
 }
 
-
-#' Generates the \code{sparkline} HTML code
-#'
-#' @param bar_spacing \code{numeric} spacing between the bars (in pixels)
-#' @param bar_width \code{numeric} width of the bars (in pixels)
-#'
-#' @return \code{character} with HTML code for the \code{sparkline} widget
-#'
 #' @export
-#' @keywords internal
 #' @rdname create_sparklines
 create_sparklines.factor <- function(arr, width = 150, bar_spacing = 5, bar_width = 20, ...) {
   decreasing_order <- TRUE
@@ -763,13 +704,7 @@ create_sparklines.factor <- function(arr, width = 150, bar_spacing = 5, bar_widt
   )
 }
 
-#' Generates the \code{sparkline} HTML code
-#'
-#'
-#' @return \code{character} with HTML code for the \code{sparkline} widget
-#'
 #' @export
-#' @keywords internal
 #' @rdname create_sparklines
 create_sparklines.numeric <- function(arr, width = 150, ...) {
   if (any(is.infinite(arr))) {
@@ -780,8 +715,7 @@ create_sparklines.numeric <- function(arr, width = 150, ...) {
   }
 
   arr <- arr[!is.na(arr)]
-  res <- sparkline::spk_chr(unname(arr), type = "box", width = width, ...)
-  return(res)
+  sparkline::spk_chr(unname(arr), type = "box", width = width, ...)
 }
 
 #' Summarizes variable
@@ -789,6 +723,7 @@ create_sparklines.numeric <- function(arr, width = 150, ...) {
 #' Creates html summary with statistics relevant to data type. For numeric values it returns central
 #' tendency measures, for factor returns level counts, for Date  date range, for other just
 #' number of levels.
+#'
 #' @param x vector of any type
 #' @param numeric_as_factor \code{logical} should the numeric variable be treated as a factor
 #' @param dt_rows \code{numeric} current/latest `DT` page length
@@ -875,10 +810,10 @@ var_summary_table <- function(x, numeric_as_factor, dt_rows, outlier_definition)
   }
 }
 
-
 #' Plot variable
 #'
 #' Creates summary plot with statistics relevant to data type.
+#'
 #' @inheritParams shared_params
 #' @param var vector of any type to be plotted. For numeric variables it produces histogram with
 #' density line, for factors it creates frequency plot
@@ -1045,6 +980,7 @@ plot_var_summary <- function(var,
   plot_main
 }
 
+#' @noRd
 #' @keywords internal
 is_num_var_short <- function(.unique_records_for_factor, input, data_for_analysis) {
   length(unique(data_for_analysis()$data)) < .unique_records_for_factor && !is.null(input$numeric_as_factor)
@@ -1056,7 +992,7 @@ is_num_var_short <- function(.unique_records_for_factor, input, data_for_analysi
 #' @param plot_var (`list`) list of a data frame and an array of variable names
 #' @param data (`tdata`) the datasets passed to the module
 #'
-#' @returns `logical` TRUE if validations pass; a Shiny validation error otherwise
+#' @returns `logical` TRUE if validations pass; a `shiny` validation error otherwise
 #' @keywords internal
 validate_input <- function(input, plot_var, data) {
   reactive({
@@ -1073,6 +1009,8 @@ validate_input <- function(input, plot_var, data) {
   })
 }
 
+#' @noRd
+#' @keywords internal
 get_plotted_data <- function(input, plot_var, data) {
   dataset_name <- input$tabset_panel
   varname <- plot_var$variable[[dataset_name]]
@@ -1105,7 +1043,6 @@ render_tabset_panel_content <- function(datanames, parent_dataname, output, data
 
 #' Renders a single tab in the left-hand side tabset panel
 #'
-#' @description
 #' Renders a single tab in the left-hand side tabset panel. The rendered tab contains
 #' information about one dataset out of many presented in the module.
 #'
@@ -1152,7 +1089,6 @@ render_tab_header <- function(dataset_name, output, data) {
 
 #' Renders the table for a single dataset in the left-hand side tabset panel
 #'
-#' @description
 #' The table contains column names, column labels,
 #' small summary about NA values and `sparkline` (if appropriate).
 #'
@@ -1271,7 +1207,6 @@ render_tab_table <- function(dataset_name, parent_dataname, output, data, input,
 
 #' Creates observers updating the currently selected column
 #'
-#' @description
 #' The created observers update the column currently selected in the left-hand side
 #' tabset panel.
 #'
@@ -1291,6 +1226,8 @@ establish_updating_selection <- function(datanames, input, plot_var, columns_nam
   })
 }
 
+#' @noRd
+#' @keywords internal
 get_bin_width <- function(x_vec, scaling_factor = 2) {
   x_vec <- x_vec[!is.na(x_vec)]
   qntls <- stats::quantile(x_vec, probs = c(0.1, 0.25, 0.75, 0.9), type = 2)
@@ -1302,6 +1239,8 @@ get_bin_width <- function(x_vec, scaling_factor = 2) {
   if (isTRUE(x_span / binwidth >= 2)) binwidth else x_span / 2
 }
 
+#' @noRd
+#' @keywords internal
 custom_sparkline_formatter <- function(labels, counts) {
   htmlwidgets::JS(
     sprintf(
diff --git a/man/create_sparklines.Rd b/man/create_sparklines.Rd
index 2d7be08ce..18cc1080b 100644
--- a/man/create_sparklines.Rd
+++ b/man/create_sparklines.Rd
@@ -38,34 +38,16 @@ create_sparklines(arr, width = 150, ...)
 \item{...}{\code{list} additional options passed to bar plots of \code{jquery.sparkline};  see
 \href{https://omnipotent.net/jquery.sparkline/#common}{\code{jquery.sparkline docs}}}
 
-\item{bar_spacing}{\code{numeric} spacing between the bars (in pixels)}
+\item{bar_spacing}{\code{numeric} the spacing between the bars (in pixels)}
 
-\item{bar_width}{\code{numeric} width of the bars (in pixels)}
+\item{bar_width}{\code{numeric} the width of the bars (in pixels)}
 }
 \value{
 character variable containing the HTML code of the \code{sparkline} HTML widget
-
-\code{character} with HTML code for the \code{sparkline} widget
-
-\code{character} with HTML code for the \code{sparkline} widget
-
-\code{character} with HTML code for the \code{sparkline} widget
-
-\code{character} with HTML code for the \code{sparkline} widget
-
-\code{character} with HTML code for the \code{sparkline} widget
-
-\code{character} with HTML code for the \code{sparkline} widget
-
-\code{character} with HTML code for the \code{sparkline} widget
 }
 \description{
 Generates the \code{sparkline} HTML code corresponding to the input array.
 For numeric variables creates a box plot, for character and factors - bar plot.
 Produces an empty string for variables of other types.
-
-Coerces a character vector to factor and delegates to the \code{create_sparklines.factor}
-
-Coerces logical vector to factor and delegates to the \code{create_sparklines.factor}
 }
 \keyword{internal}
diff --git a/man/tm_variable_browser.Rd b/man/tm_variable_browser.Rd
index 8ed80bb46..9ea518a85 100644
--- a/man/tm_variable_browser.Rd
+++ b/man/tm_variable_browser.Rd
@@ -2,13 +2,7 @@
 % Please edit documentation in R/tm_variable_browser.R
 \name{tm_variable_browser}
 \alias{tm_variable_browser}
-\alias{tm_variable_browser_ui,}
-\alias{tm_variable_browser_srv,}
-\alias{tm_variable_browser,}
-\alias{variable_browser_ui,}
-\alias{variable_browser_srv,}
-\alias{variable_browser}
-\title{Variable Browser Teal Module}
+\title{Variable browser \code{teal} module}
 \usage{
 tm_variable_browser(
   label = "Variable Browser",
@@ -23,16 +17,16 @@ tm_variable_browser(
 \item{label}{(\code{character(1)}) Label shown in the navigation item for the module or module group.
 For \code{modules()} defaults to \code{"root"}. See \code{Details}.}
 
-\item{datasets_selected}{(\code{character}) A vector of datasets which should be
-shown and in what order. Names in the vector have to correspond with datasets names.
+\item{datasets_selected}{(\code{character}) vector of datasets which should be
+shown, in order. Names must correspond with datasets names.
 If vector of length zero (default) then all datasets are shown.
-Note: Only datasets of the \code{data.frame} class are compatible; using other types will cause an error.}
+Note: Only \code{data.frame} objects are compatible; using other types will cause an error.}
 
-\item{parent_dataname}{(\code{character(1)}) If this \code{dataname} exists in \code{datasets_selected}
-then an extra checkbox will be shown to allow users to not show variables in other datasets
-which exist in this \code{dataname}.
-This is typically used to remove \code{ADSL} columns in \code{CDISC} data. In non \code{CDISC} data this
-can be ignored. Defaults to \code{"ADSL"}.}
+\item{parent_dataname}{(\code{character(1)}) string specifying a parent dataset.
+If it exists in \code{datasets_selected}then an extra checkbox will be shown to
+allow users to not show variables in other datasets which exist in this \code{dataname}.
+This is typically used to remove \code{ADSL} columns in \code{CDISC} data.
+In non \code{CDISC} data this can be ignored. Defaults to \code{"ADSL"}.}
 
 \item{pre_output}{(\code{shiny.tag}, optional)\cr
 with text placed before the output to put the output into context. For example a title.}
@@ -47,19 +41,18 @@ The argument is merged with options variable \code{teal.ggplot2_args} and defaul
 For more details see the vignette: \code{vignette("custom-ggplot2-arguments", package = "teal.widgets")}}
 }
 \description{
-The variable browser provides a table with variable names and labels and a
-plot that visualizes the content of a particular variable.
-specifically designed for use with \code{data.frames}.
+Module provides provides a detailed summary and visualization of variable distributions
+for \code{data.frame} objects, with interactive features to customize analysis.
 }
 \details{
-Numeric columns with fewer than 30 distinct values can be treated as either factors
-or numbers with a checkbox allowing users to switch how they are treated (if < 6 unique values
-then the default is categorical, otherwise it is numeric).
+Numeric columns with fewer than 30 distinct values can be treated as either discrete
+or continuous with a checkbox allowing users to switch how they are treated(if < 6 unique values
+then the default is discrete, otherwise it is continuous).
 }
 \examples{
 library(teal.widgets)
 
-# module specification used in apps below
+# Module specification used in apps below
 tm_variable_browser_module <- tm_variable_browser(
   label = "Variable browser",
   ggplot2_args = ggplot2_args(
diff --git a/man/validate_input.Rd b/man/validate_input.Rd
index d1872efcf..37ab1310d 100644
--- a/man/validate_input.Rd
+++ b/man/validate_input.Rd
@@ -14,7 +14,7 @@ validate_input(input, plot_var, data)
 \item{data}{(\code{tdata}) the datasets passed to the module}
 }
 \value{
-\code{logical} TRUE if validations pass; a Shiny validation error otherwise
+\code{logical} TRUE if validations pass; a \code{shiny} validation error otherwise
 }
 \description{
 Validates the variable browser inputs
diff --git a/man/var_missings_info.Rd b/man/var_missings_info.Rd
index c814a510c..70426bf8d 100644
--- a/man/var_missings_info.Rd
+++ b/man/var_missings_info.Rd
@@ -10,9 +10,9 @@ var_missings_info(x)
 \item{x}{vector of any type and length}
 }
 \value{
-text describing \code{NA} occurrence.
+Text describing \code{NA} occurrence.
 }
 \description{
-Summarizes missings occurrence in vector
+Summarizes missings occurrence in vector.
 }
 \keyword{internal}

From b6f0d28352a8dbd43168b6229eb2c41813299a1d Mon Sep 17 00:00:00 2001
From: kartikeya kirar <kirar.kartikeya1@gmail.com>
Date: Mon, 26 Feb 2024 16:56:40 +0530
Subject: [PATCH 20/62] pre-release `tm_g_bivariate` document update (#660)

part of
https://github.com/insightsengineering/teal.modules.general/issues/624
---
 R/tm_g_bivariate.R    | 138 +++++++++++++++++-------------------------
 man/tm_g_bivariate.Rd |  42 +++++++------
 2 files changed, 79 insertions(+), 101 deletions(-)

diff --git a/R/tm_g_bivariate.R b/R/tm_g_bivariate.R
index fc82181c5..99fa167f4 100644
--- a/R/tm_g_bivariate.R
+++ b/R/tm_g_bivariate.R
@@ -1,52 +1,53 @@
-#' Univariate and bivariate visualizations
-#' @md
+#' Univariate and bivariate visualizations module
 #'
-#' @inheritParams teal::module
-#' @inheritParams shared_params
-#' @param x (`data_extract_spec` or `list` of multiple `data_extract_spec`)
-#'   Variable names selected to plot along the x-axis by default. Variable can be numeric, factor or character.
-#'   No empty selections are allowed!
-#' @param y (`data_extract_spec` or `list` of multiple `data_extract_spec`)
-#'   Variable names selected to plot along the y-axis by default. Variable can be numeric, factor or character.
-#' @param use_density optional, (`logical`) value for whether density (`TRUE`) is plotted or
-#'   frequency (`FALSE`). Defaults to frequency (`FALSE`).
-#' @param row_facet optional, (`data_extract_spec` or `list` of multiple `data_extract_spec`)
-#'   Variables for row facetting.
-#' @param col_facet optional, (`data_extract_spec` or `list` of multiple `data_extract_spec`)
-#'   Variables for col facetting.
-#' @param facet optional, (`logical`) to specify whether the facet encodings `ui` elements are toggled
-#'   on and shown to the user by default. Defaults to `TRUE` if either `row_facet` or `column_facet`
-#'   are supplied.
-#' @param color_settings (`logical`) Whether coloring, filling and size should be applied
-#' and `UI` tool offered to the user.
-#' @param color optional, (`data_extract_spec` or `list` of multiple `data_extract_spec`)
-#'   Variables selected for the outline color inside the coloring settings.
-#'   It will be applied when `color_settings` is set to `TRUE`.
-#' @param fill optional, (`data_extract_spec` or `list` of multiple `data_extract_spec`)
-#'   Variables selected for the fill color inside the coloring settings.
-#'   It will be applied when `color_settings` is set to `TRUE`.
-#' @param size optional, (`data_extract_spec` or `list` of multiple `data_extract_spec`)
-#'   Variables selected for the size of `geom_point` plots inside the coloring settings.
-#'   It will be applied when `color_settings` is set to `TRUE`.
-#' @param free_x_scales optional, (`logical`) Whether X scaling shall be changeable.
-#'   Does not allow scaling to be changed by default (`FALSE`).
-#' @param free_y_scales optional, (`logical`) Whether Y scaling shall be changeable.
-#'   Does not allow scaling to be changed by default (`FALSE`).
-#' @param swap_axes optional, (`logical`) Whether to swap X and Y axes. Defaults to `FALSE`.
+#' Module enables the creation of univariate and bivariate plots,
+#' facilitating the exploration of data distributions and relationships between two variables.
 #'
-#' @details
 #' This is a general module to visualize 1 & 2 dimensional data.
 #'
 #' @note
 #' For more examples, please see the vignette "Using bivariate plot" via
-#'   `vignette("using-bivariate-plot", package = "teal.modules.general")`.
+#' `vignette("using-bivariate-plot", package = "teal.modules.general")`.
 #'
-#' @export
+#' @inheritParams teal::module
+#' @inheritParams shared_params
+#' @param x (`data_extract_spec` or `list` of multiple `data_extract_spec`)
+#' Variable names selected to plot along the x-axis by default.
+#' Can be numeric, factor or character.
+#' No empty selections are allowed.
+#' @param y (`data_extract_spec` or `list` of multiple `data_extract_spec`)
+#' Variable names selected to plot along the y-axis by default.
+#' Can be numeric, factor or character.
+#' @param use_density (`logical`, optional) Indicates whether to plot density (`TRUE`) or frequency (`FALSE`).
+#' Defaults to frequency (`FALSE`).
+#' @param row_facet (`data_extract_spec` or `list` of multiple `data_extract_spec`, optional)
+#' Variables for row facetting.
+#' @param col_facet (`data_extract_spec` or `list` of multiple `data_extract_spec`, optional)
+#' Variables for column facetting.
+#' @param facet (`logical`, optional) to specify whether the facet encodings `ui` elements are toggled
+#' on and shown to the user by default. Defaults to `TRUE` if either `row_facet` or `column_facet`
+#' are supplied.
+#' @param color_settings (`logical`) Whether coloring, filling and size should be applied
+#' and `UI` tool offered to the user.
+#' @param color (`data_extract_spec` or `list` of multiple `data_extract_spec`, optional)
+#' Variables selected for the outline color inside the coloring settings.
+#' It will be applied when `color_settings` is set to `TRUE`.
+#' @param fill (`data_extract_spec` or `list` of multiple `data_extract_spec`, optional)
+#' Variables selected for the fill color inside the coloring settings.
+#' It will be applied when `color_settings` is set to `TRUE`.
+#' @param size (`data_extract_spec` or `list` of multiple `data_extract_spec`, optional)
+#' Variables selected for the size of `geom_point` plots inside the coloring settings.
+#' It will be applied when `color_settings` is set to `TRUE`.
+#' @param free_x_scales (`logical`, optional) Whether X scaling shall be changeable.
+#' Does not allow scaling to be changed by default (`FALSE`).
+#' @param free_y_scales (`logical`, optional) Whether Y scaling shall be changeable.
+#' Does not allow scaling to be changed by default (`FALSE`).
+#' @param swap_axes (`logical`, optional) Whether to swap X and Y axes. Defaults to `FALSE`.
 #'
 #' @examples
-#' # general data exapmle
 #' library(teal.widgets)
 #'
+#' # general data exapmle
 #' data <- teal_data()
 #' data <- within(data, {
 #'   require(nestcolor)
@@ -108,8 +109,6 @@
 #'
 #'
 #' # CDISC data example
-#' library(teal.widgets)
-#'
 #' data <- teal_data()
 #' data <- within(data, {
 #'   require(nestcolor)
@@ -168,6 +167,9 @@
 #' if (interactive()) {
 #'   shinyApp(app$ui, app$server)
 #' }
+#'
+#' @export
+#'
 tm_g_bivariate <- function(label = "Bivariate Plots",
                            x,
                            y,
@@ -289,6 +291,9 @@ tm_g_bivariate <- function(label = "Bivariate Plots",
   )
 }
 
+# UI function for the bivariate module.
+#' @noRd
+#' @keywords internal
 ui_g_bivariate <- function(id, ...) {
   args <- list(...)
   is_single_dataset_value <- teal.transform::is_single_dataset(
@@ -429,7 +434,9 @@ ui_g_bivariate <- function(id, ...) {
   )
 }
 
-
+# Server function for the bivariate module.
+#' @noRd
+#' @keywords internal
 srv_g_bivariate <- function(id,
                             data,
                             reporter,
@@ -710,15 +717,9 @@ srv_g_bivariate <- function(id,
   })
 }
 
-
-#' Get Substituted ggplot call
-#'
+# Get Substituted ggplot call
 #' @noRd
-#'
-#' @examples
-#'
-#' bivariate_plot_call("ANL", "BAGE", "RACE", "numeric", "factor")
-#' bivariate_plot_call("ANL", "BAGE", character(0), "numeric", "NULL")
+#' @keywords internal
 bivariate_plot_call <- function(data_name,
                                 x = character(0),
                                 y = character(0),
@@ -767,30 +768,10 @@ bivariate_plot_call <- function(data_name,
   )
 }
 
-
-#' Create ggplot part of plot call
-#'
-#' Due to the type of the x and y variable the plot type is chosen
-#'
+# Create ggplot part of plot call
+# Due to the type of the x and y variable the plot type is chosen
 #' @noRd
-#'
-#' @examples
-#' bivariate_ggplot_call("numeric", "NULL")
-#' bivariate_ggplot_call("numeric", "NULL", freq = FALSE)
-#'
-#' bivariate_ggplot_call("NULL", "numeric")
-#' bivariate_ggplot_call("NULL", "numeric", freq = FALSE)
-#'
-#' bivariate_ggplot_call("NULL", "factor")
-#' bivariate_ggplot_call("NULL", "factor", freq = FALSE)
-#'
-#' bivariate_ggplot_call("factor", "NULL")
-#' bivariate_ggplot_call("factor", "NULL", freq = FALSE)
-#'
-#' bivariate_ggplot_call("numeric", "numeric")
-#' bivariate_ggplot_call("numeric", "factor")
-#' bivariate_ggplot_call("factor", "numeric")
-#' bivariate_ggplot_call("factor", "factor")
+#' @keywords internal
 bivariate_ggplot_call <- function(x_class = c("NULL", "numeric", "integer", "factor", "character", "logical"),
                                   y_class = c("NULL", "numeric", "integer", "factor", "character", "logical"),
                                   freq = TRUE,
@@ -971,19 +952,12 @@ bivariate_ggplot_call <- function(x_class = c("NULL", "numeric", "integer", "fac
     plot_call <- reduce_plot_call(plot_call, quote(coord_flip()))
   }
 
-  return(plot_call)
+  plot_call
 }
 
-
 #' Create facet call
-#'
 #' @noRd
-#'
-#' @examples
-#'
-#' facet_ggplot_call(LETTERS[1:3])
-#' facet_ggplot_call(NULL, LETTERS[23:26])
-#' facet_ggplot_call(LETTERS[1:3], LETTERS[23:26])
+#' @keywords internal
 facet_ggplot_call <- function(row_facet = character(0),
                               col_facet = character(0),
                               free_x_scales = FALSE,
@@ -1014,6 +988,8 @@ facet_ggplot_call <- function(row_facet = character(0),
   }
 }
 
+#' @noRd
+#' @keywords internal
 coloring_ggplot_call <- function(colour,
                                  fill,
                                  size,
diff --git a/man/tm_g_bivariate.Rd b/man/tm_g_bivariate.Rd
index 6ebecdd90..c97ee92bb 100644
--- a/man/tm_g_bivariate.Rd
+++ b/man/tm_g_bivariate.Rd
@@ -2,7 +2,7 @@
 % Please edit documentation in R/tm_g_bivariate.R
 \name{tm_g_bivariate}
 \alias{tm_g_bivariate}
-\title{Univariate and bivariate visualizations}
+\title{Univariate and bivariate visualizations module}
 \usage{
 tm_g_bivariate(
   label = "Bivariate Plots",
@@ -33,44 +33,46 @@ tm_g_bivariate(
 For \code{modules()} defaults to \code{"root"}. See \code{Details}.}
 
 \item{x}{(\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec})
-Variable names selected to plot along the x-axis by default. Variable can be numeric, factor or character.
-No empty selections are allowed!}
+Variable names selected to plot along the x-axis by default.
+Can be numeric, factor or character.
+No empty selections are allowed.}
 
 \item{y}{(\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec})
-Variable names selected to plot along the y-axis by default. Variable can be numeric, factor or character.}
+Variable names selected to plot along the y-axis by default.
+Can be numeric, factor or character.}
 
-\item{row_facet}{optional, (\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec})
+\item{row_facet}{(\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec}, optional)
 Variables for row facetting.}
 
-\item{col_facet}{optional, (\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec})
-Variables for col facetting.}
+\item{col_facet}{(\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec}, optional)
+Variables for column facetting.}
 
-\item{facet}{optional, (\code{logical}) to specify whether the facet encodings \code{ui} elements are toggled
+\item{facet}{(\code{logical}, optional) to specify whether the facet encodings \code{ui} elements are toggled
 on and shown to the user by default. Defaults to \code{TRUE} if either \code{row_facet} or \code{column_facet}
 are supplied.}
 
-\item{color}{optional, (\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec})
+\item{color}{(\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec}, optional)
 Variables selected for the outline color inside the coloring settings.
 It will be applied when \code{color_settings} is set to \code{TRUE}.}
 
-\item{fill}{optional, (\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec})
+\item{fill}{(\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec}, optional)
 Variables selected for the fill color inside the coloring settings.
 It will be applied when \code{color_settings} is set to \code{TRUE}.}
 
-\item{size}{optional, (\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec})
+\item{size}{(\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec}, optional)
 Variables selected for the size of \code{geom_point} plots inside the coloring settings.
 It will be applied when \code{color_settings} is set to \code{TRUE}.}
 
-\item{use_density}{optional, (\code{logical}) value for whether density (\code{TRUE}) is plotted or
-frequency (\code{FALSE}). Defaults to frequency (\code{FALSE}).}
+\item{use_density}{(\code{logical}, optional) Indicates whether to plot density (\code{TRUE}) or frequency (\code{FALSE}).
+Defaults to frequency (\code{FALSE}).}
 
 \item{color_settings}{(\code{logical}) Whether coloring, filling and size should be applied
 and \code{UI} tool offered to the user.}
 
-\item{free_x_scales}{optional, (\code{logical}) Whether X scaling shall be changeable.
+\item{free_x_scales}{(\code{logical}, optional) Whether X scaling shall be changeable.
 Does not allow scaling to be changed by default (\code{FALSE}).}
 
-\item{free_y_scales}{optional, (\code{logical}) Whether Y scaling shall be changeable.
+\item{free_y_scales}{(\code{logical}, optional) Whether Y scaling shall be changeable.
 Does not allow scaling to be changed by default (\code{FALSE}).}
 
 \item{plot_height}{optional, (\code{numeric}) A vector of length three with \verb{c(value, min and max)}
@@ -82,7 +84,7 @@ for a slider encoding the plot width.}
 \item{rotate_xaxis_labels}{optional, (\code{logical}) Whether to rotate plot X axis labels. Does not
 rotate by default (\code{FALSE}).}
 
-\item{swap_axes}{optional, (\code{logical}) Whether to swap X and Y axes. Defaults to \code{FALSE}.}
+\item{swap_axes}{(\code{logical}, optional) Whether to swap X and Y axes. Defaults to \code{FALSE}.}
 
 \item{ggtheme}{optional, (\code{character}) \code{ggplot2} theme to be used by default. Defaults to \code{"gray"}.}
 
@@ -99,7 +101,8 @@ with text placed before the output to put the output into context. For example a
 into context. For example the \code{\link[shiny:helpText]{shiny::helpText()}} elements are useful.}
 }
 \description{
-Univariate and bivariate visualizations
+Module enables the creation of univariate and bivariate plots,
+facilitating the exploration of data distributions and relationships between two variables.
 }
 \details{
 This is a general module to visualize 1 & 2 dimensional data.
@@ -109,9 +112,9 @@ For more examples, please see the vignette "Using bivariate plot" via
 \code{vignette("using-bivariate-plot", package = "teal.modules.general")}.
 }
 \examples{
-# general data exapmle
 library(teal.widgets)
 
+# general data exapmle
 data <- teal_data()
 data <- within(data, {
   require(nestcolor)
@@ -173,8 +176,6 @@ if (interactive()) {
 
 
 # CDISC data example
-library(teal.widgets)
-
 data <- teal_data()
 data <- within(data, {
   require(nestcolor)
@@ -233,4 +234,5 @@ app <- init(
 if (interactive()) {
   shinyApp(app$ui, app$server)
 }
+
 }

From cb07ccebf3d2be1ef2dc4f7543553d73fece13f8 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Andr=C3=A9=20Ver=C3=ADssimo?=
 <211358+averissimo@users.noreply.github.com>
Date: Mon, 26 Feb 2024 14:13:18 +0100
Subject: [PATCH 21/62] pre-release `tm_g_response` document update (#666)
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

part of #624

~blocked by #651~

---------

Signed-off-by: André Veríssimo <211358+averissimo@users.noreply.github.com>
Co-authored-by: Vedha Viyash <49812166+vedhav@users.noreply.github.com>
---
 R/tm_g_response.R    | 53 +++++++++++++++++++++++++++++---------------
 man/tm_g_response.Rd | 45 ++++++++++++++++++++++++-------------
 2 files changed, 65 insertions(+), 33 deletions(-)

diff --git a/R/tm_g_response.R b/R/tm_g_response.R
index 386e2aa17..52c221e7e 100644
--- a/R/tm_g_response.R
+++ b/R/tm_g_response.R
@@ -1,28 +1,43 @@
-#' Response Plots
-#' @md
+#' Response plot module
+#'
+#' Generates a response plot for a given `response` and `x` variables.
+#' This module allows users customize and add annotations to the plot depending
+#' on the module's arguments.
+#' It supports showing the counts grouped by other variable facets (by row / column),
+#' swapping the coordinates, show count annotations and displaying the response plot
+#' as frequency or density.
 #'
 #' @inheritParams teal::module
 #' @inheritParams shared_params
 #' @param response (`data_extract_spec` or `list` of multiple `data_extract_spec`)
-#'   Which variable to use as the response. You can define one fixed column by using the
-#'   setting `fixed = TRUE` inside the `select_spec`.
-#'  `data_extract_spec` must not allow multiple selection in this case.
+#' Which variable to use as the response.
+#' You can define one fixed column by setting `fixed = TRUE` inside the `select_spec`.
+#'
+#' The `data_extract_spec` must not allow multiple selection in this case.
 #' @param x (`data_extract_spec` or `list` of multiple `data_extract_spec`)
-#'   Which variable to use on the X-axis of the response plot. Allow the user to select multiple
-#'   columns from the `data` allowed in teal.
-#'  `data_extract_spec` must not allow multiple selection in this case.
-#' @param row_facet optional, (`data_extract_spec` or `list` of multiple `data_extract_spec`)
-#'   Which data columns to use for faceting rows.
-#' @param col_facet optional, (`data_extract_spec` or `list` of multiple `data_extract_spec`)
-#'   Which data to use for faceting columns.
-#' @param coord_flip optional, (`logical`) Whether to flip coordinates between `x` and `response`.
-#' @param count_labels optional, (`logical`) Whether to show count labels.
-#'   Defaults to `TRUE`.
-#' @param freq optional, (`logical`) Whether to display frequency (`TRUE`) or density (`FALSE`).
-#'   Defaults to density (`FALSE`).
+#' Specifies which variable to use on the X-axis of the response plot.
+#' Allow the user to select multiple columns from the `data` allowed in teal.
+#'
+#' The `data_extract_spec` must not allow multiple selection in this case.
+#' @param row_facet (`data_extract_spec` or `list` of multiple `data_extract_spec`)
+#' optional specification of the data variable(s) to use for faceting rows.
+#' @param col_facet (`data_extract_spec` or `list` of multiple `data_extract_spec`)
+#' optional specification of the data variable(s) to use for faceting columns.
+#' @param coord_flip (`logical(1)`)
+#' Indicates whether to flip coordinates between `x` and `response`.
+#' The default value is `FALSE` and it will show the `x` variable on the x-axis
+#' and the `response` variable on the y-axis.
+#' @param count_labels (`logical(1)`)
+#' Indicates whether to show count labels.
+#' Defaults to `TRUE`.
+#' @param freq (`logical(1)`)
+#' Indicates whether to display frequency (`TRUE`) or density (`FALSE`).
+#' Defaults to density (`FALSE`).
+#'
+#' @inherit shared_params return
 #'
 #' @note For more examples, please see the vignette "Using response plot" via
-#'   \code{vignette("using-response-plot", package = "teal.modules.general")}.
+#' `vignette("using-response-plot", package = "teal.modules.general")`.
 #'
 #' @examples
 #' # general data example
@@ -195,6 +210,7 @@ tm_g_response <- function(label = "Response Plot",
   )
 }
 
+# UI function for the response module
 ui_g_response <- function(id, ...) {
   ns <- NS(id)
   args <- list(...)
@@ -270,6 +286,7 @@ ui_g_response <- function(id, ...) {
   )
 }
 
+# Server function for the response module
 srv_g_response <- function(id,
                            data,
                            reporter,
diff --git a/man/tm_g_response.Rd b/man/tm_g_response.Rd
index cab67f975..74c6b40ac 100644
--- a/man/tm_g_response.Rd
+++ b/man/tm_g_response.Rd
@@ -2,7 +2,7 @@
 % Please edit documentation in R/tm_g_response.R
 \name{tm_g_response}
 \alias{tm_g_response}
-\title{Response Plots}
+\title{Response plot module}
 \usage{
 tm_g_response(
   label = "Response Plot",
@@ -27,30 +27,37 @@ tm_g_response(
 For \code{modules()} defaults to \code{"root"}. See \code{Details}.}
 
 \item{response}{(\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec})
-Which variable to use as the response. You can define one fixed column by using the
-setting \code{fixed = TRUE} inside the \code{select_spec}.
-\code{data_extract_spec} must not allow multiple selection in this case.}
+Which variable to use as the response.
+You can define one fixed column by setting \code{fixed = TRUE} inside the \code{select_spec}.
+
+The \code{data_extract_spec} must not allow multiple selection in this case.}
 
 \item{x}{(\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec})
-Which variable to use on the X-axis of the response plot. Allow the user to select multiple
-columns from the \code{data} allowed in teal.
-\code{data_extract_spec} must not allow multiple selection in this case.}
+Specifies which variable to use on the X-axis of the response plot.
+Allow the user to select multiple columns from the \code{data} allowed in teal.
+
+The \code{data_extract_spec} must not allow multiple selection in this case.}
 
-\item{row_facet}{optional, (\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec})
-Which data columns to use for faceting rows.}
+\item{row_facet}{(\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec})
+optional specification of the data variable(s) to use for faceting rows.}
 
-\item{col_facet}{optional, (\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec})
-Which data to use for faceting columns.}
+\item{col_facet}{(\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec})
+optional specification of the data variable(s) to use for faceting columns.}
 
-\item{coord_flip}{optional, (\code{logical}) Whether to flip coordinates between \code{x} and \code{response}.}
+\item{coord_flip}{(\code{logical(1)})
+Indicates whether to flip coordinates between \code{x} and \code{response}.
+The default value is \code{FALSE} and it will show the \code{x} variable on the x-axis
+and the \code{response} variable on the y-axis.}
 
-\item{count_labels}{optional, (\code{logical}) Whether to show count labels.
+\item{count_labels}{(\code{logical(1)})
+Indicates whether to show count labels.
 Defaults to \code{TRUE}.}
 
 \item{rotate_xaxis_labels}{optional, (\code{logical}) Whether to rotate plot X axis labels. Does not
 rotate by default (\code{FALSE}).}
 
-\item{freq}{optional, (\code{logical}) Whether to display frequency (\code{TRUE}) or density (\code{FALSE}).
+\item{freq}{(\code{logical(1)})
+Indicates whether to display frequency (\code{TRUE}) or density (\code{FALSE}).
 Defaults to density (\code{FALSE}).}
 
 \item{plot_height}{optional, (\code{numeric}) A vector of length three with \verb{c(value, min and max)}
@@ -73,8 +80,16 @@ with text placed before the output to put the output into context. For example a
 \item{post_output}{(\code{shiny.tag}, optional) with text placed after the output to put the output
 into context. For example the \code{\link[shiny:helpText]{shiny::helpText()}} elements are useful.}
 }
+\value{
+Object of class \code{teal_module} to be used in \code{teal} applications.
+}
 \description{
-Response Plots
+Generates a response plot for a given \code{response} and \code{x} variables.
+This module allows users customize and add annotations to the plot depending
+on the module's arguments.
+It supports showing the counts grouped by other variable facets (by row / column),
+swapping the coordinates, show count annotations and displaying the response plot
+as frequency or density.
 }
 \note{
 For more examples, please see the vignette "Using response plot" via

From 51ef394720c62d08ca61ed770082bedd13650b57 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Andr=C3=A9=20Ver=C3=ADssimo?=
 <211358+averissimo@users.noreply.github.com>
Date: Mon, 26 Feb 2024 14:13:48 +0100
Subject: [PATCH 22/62] pre-release `tm_file_viewer` document update (#665)

part of #624

~blocked by #651~
---
 R/tm_file_viewer.R    | 39 ++++++++++++++++++++-------------------
 man/tm_file_viewer.Rd | 39 ++++++++++++++++++++-------------------
 2 files changed, 40 insertions(+), 38 deletions(-)

diff --git a/R/tm_file_viewer.R b/R/tm_file_viewer.R
index 7a3ae61ff..8be167330 100644
--- a/R/tm_file_viewer.R
+++ b/R/tm_file_viewer.R
@@ -1,34 +1,32 @@
-#' File Viewer `teal` Module
+#' File viewer module
 #'
 #' The file viewer module provides a tool to view static files.
-#' Supported formats include text formats, \code{PDF}, \code{PNG}, \code{APNG},
-#' \code{JPEG}, \code{SVG}, \code{WEBP}, \code{GIF} and \code{BMP}.
+#' Supported formats include text formats, `PDF`, `PNG` `APNG`,
+#' `JPEG` `SVG`, `WEBP`, `GIF` and `BMP`.
 #'
 #' @inheritParams teal::module
 #' @inheritParams shared_params
-#' @param input_path optional, (`list`) of the input paths to either: specific files of accepted formats,
-#'   a directory or a URL. The paths can be specified as absolute paths or relative to the running
-#'   directory of the application. Will default to current working directory if not supplied.
+#' @param input_path (`list`) of the input paths, optional. Each element can be:
 #'
-#' @export
+#' 1. Specific path to files of accepted formats
+#' 2. A directory or a URL
 #'
-#' @examples
-#' data <- teal_data()
-#' data <- within(data, {
-#'   data <- data.frame(1)
-#' })
-#' datanames(data) <- c("data")
+#' The paths can be specified as absolute paths or relative to the running
+#' directory of the application.
+#' Default to the current working directory if not supplied.
+#'
+#' @inherit shared_params return
 #'
-#' app <- teal::init(
-#'   data = data,
-#'   modules = teal::modules(
-#'     teal.modules.general::tm_file_viewer(
+#' @examples
+#' app <- init(
+#'   data = teal_data(data = 1), # Mock dataset to initialize the app without error
+#'   modules = modules(
+#'     tm_file_viewer(
 #'       input_path = list(
 #'         folder = system.file("sample_files", package = "teal.modules.general"),
 #'         png = system.file("sample_files/sample_file.png", package = "teal.modules.general"),
 #'         txt = system.file("sample_files/sample_file.txt", package = "teal.modules.general"),
-#'         url =
-#'           "https://www.fda.gov/files/drugs/published/Portable-Document-Format-Specifications.pdf"
+#'         url = "https://fda.gov/files/drugs/published/Portable-Document-Format-Specifications.pdf"
 #'       )
 #'     )
 #'   )
@@ -36,6 +34,7 @@
 #' if (interactive()) {
 #'   shinyApp(app$ui, app$server)
 #' }
+#' @export
 #'
 tm_file_viewer <- function(label = "File Viewer Module",
                            input_path = list("Current Working Directory" = ".")) {
@@ -90,6 +89,7 @@ tm_file_viewer <- function(label = "File Viewer Module",
   )
 }
 
+# UI function for the file viewer module
 ui_viewer <- function(id, ...) {
   args <- list(...)
   ns <- NS(id)
@@ -116,6 +116,7 @@ ui_viewer <- function(id, ...) {
   )
 }
 
+# Server function for the file viewer module
 srv_viewer <- function(id, input_path) {
   moduleServer(id, function(input, output, session) {
     temp_dir <- tempfile()
diff --git a/man/tm_file_viewer.Rd b/man/tm_file_viewer.Rd
index ace7d9e6d..79a3476f3 100644
--- a/man/tm_file_viewer.Rd
+++ b/man/tm_file_viewer.Rd
@@ -2,7 +2,7 @@
 % Please edit documentation in R/tm_file_viewer.R
 \name{tm_file_viewer}
 \alias{tm_file_viewer}
-\title{File Viewer \code{teal} Module}
+\title{File viewer module}
 \usage{
 tm_file_viewer(
   label = "File Viewer Module",
@@ -13,32 +13,34 @@ tm_file_viewer(
 \item{label}{(\code{character(1)}) Label shown in the navigation item for the module or module group.
 For \code{modules()} defaults to \code{"root"}. See \code{Details}.}
 
-\item{input_path}{optional, (\code{list}) of the input paths to either: specific files of accepted formats,
-a directory or a URL. The paths can be specified as absolute paths or relative to the running
-directory of the application. Will default to current working directory if not supplied.}
+\item{input_path}{(\code{list}) of the input paths, optional. Each element can be:
+\enumerate{
+\item Specific path to files of accepted formats
+\item A directory or a URL
+}
+
+The paths can be specified as absolute paths or relative to the running
+directory of the application.
+Default to the current working directory if not supplied.}
+}
+\value{
+Object of class \code{teal_module} to be used in \code{teal} applications.
 }
 \description{
 The file viewer module provides a tool to view static files.
-Supported formats include text formats, \code{PDF}, \code{PNG}, \code{APNG},
-\code{JPEG}, \code{SVG}, \code{WEBP}, \code{GIF} and \code{BMP}.
+Supported formats include text formats, \code{PDF}, \code{PNG} \code{APNG},
+\code{JPEG} \code{SVG}, \code{WEBP}, \code{GIF} and \code{BMP}.
 }
 \examples{
-data <- teal_data()
-data <- within(data, {
-  data <- data.frame(1)
-})
-datanames(data) <- c("data")
-
-app <- teal::init(
-  data = data,
-  modules = teal::modules(
-    teal.modules.general::tm_file_viewer(
+app <- init(
+  data = teal_data(data = 1), # Mock dataset to initialize the app without error
+  modules = modules(
+    tm_file_viewer(
       input_path = list(
         folder = system.file("sample_files", package = "teal.modules.general"),
         png = system.file("sample_files/sample_file.png", package = "teal.modules.general"),
         txt = system.file("sample_files/sample_file.txt", package = "teal.modules.general"),
-        url =
-          "https://www.fda.gov/files/drugs/published/Portable-Document-Format-Specifications.pdf"
+        url = "https://fda.gov/files/drugs/published/Portable-Document-Format-Specifications.pdf"
       )
     )
   )
@@ -46,5 +48,4 @@ app <- teal::init(
 if (interactive()) {
   shinyApp(app$ui, app$server)
 }
-
 }

From 0cb0b5648ccc07116325a6ac00bf462190ffb12c Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Andr=C3=A9=20Ver=C3=ADssimo?=
 <211358+averissimo@users.noreply.github.com>
Date: Mon, 26 Feb 2024 14:14:06 +0100
Subject: [PATCH 23/62] pre-release `tm_t_crosstable` document update (#664)

part of #624

~blocked by #651~
---
 R/tm_t_crosstable.R    | 31 ++++++++++++++++++++-----------
 man/tm_t_crosstable.Rd | 24 ++++++++++++++++--------
 2 files changed, 36 insertions(+), 19 deletions(-)

diff --git a/R/tm_t_crosstable.R b/R/tm_t_crosstable.R
index cbcdb6d6d..8fdc090e6 100644
--- a/R/tm_t_crosstable.R
+++ b/R/tm_t_crosstable.R
@@ -1,22 +1,29 @@
-#' Create a simple cross-table
-#' @md
+#' Cross-table module
+#'
+#' Generates a simple cross-table of two variables from a dataset with custom
+#' options for showing percentages and sub-totals.
 #'
 #' @inheritParams teal::module
 #' @inheritParams shared_params
 #' @param x (`data_extract_spec` or `list` of multiple `data_extract_spec`)
-#'  Object with all available choices with pre-selected option for variable X - row values. In case
-#'  of `data_extract_spec` use `select_spec(..., ordered = TRUE)` if table elements should be
-#'  rendered according to selection order.
+#' Object with all available choices with pre-selected option for variable X - row values.
+#' In case of `data_extract_spec` use `select_spec(..., ordered = TRUE)` if table elements should be
+#' rendered according to selection order.
 #' @param y (`data_extract_spec` or `list` of multiple `data_extract_spec`)
-#'  Object with all available choices with pre-selected option for variable Y - column values
-#'  \code{data_extract_spec} must not allow multiple selection in this case.
+#' Object with all available choices with pre-selected option for variable Y - column values.
 #'
-#' @param show_percentage optional, (`logical`) Whether to show percentages
-#'   (relevant only when `x` is a `factor`). Defaults to `TRUE`.
-#' @param show_total optional, (`logical`) Whether to show total column. Defaults to `TRUE`.
+#' `data_extract_spec` must not allow multiple selection in this case.
+#' @param show_percentage (`logical(1)`)
+#' Indicates whether to show percentages (relevant only when `x` is a `factor`).
+#' Defaults to `TRUE`.
+#' @param show_total (`logical(1)`)
+#' Indicates whether to show total column.
+#' Defaults to `TRUE`.
 #'
 #' @note For more examples, please see the vignette "Using cross table" via
-#'   `vignette("using-cross-table", package = "teal.modules.general")`.
+#' `vignette("using-cross-table", package = "teal.modules.general")`.
+#'
+#' @inherit shared_params return
 #'
 #' @examples
 #' # general data example
@@ -167,6 +174,7 @@ tm_t_crosstable <- function(label = "Cross Table",
   )
 }
 
+# UI function for the cross-table module
 ui_t_crosstable <- function(id, x, y, show_percentage, show_total, pre_output, post_output, ...) {
   ns <- NS(id)
   is_single_dataset <- teal.transform::is_single_dataset(x, y)
@@ -216,6 +224,7 @@ ui_t_crosstable <- function(id, x, y, show_percentage, show_total, pre_output, p
   )
 }
 
+# Server function for the cross-table module
 srv_t_crosstable <- function(id, data, reporter, filter_panel_api, label, x, y, basic_table_args) {
   with_reporter <- !missing(reporter) && inherits(reporter, "Reporter")
   with_filter <- !missing(filter_panel_api) && inherits(filter_panel_api, "FilterPanelAPI")
diff --git a/man/tm_t_crosstable.Rd b/man/tm_t_crosstable.Rd
index 155f6bc90..6965390ea 100644
--- a/man/tm_t_crosstable.Rd
+++ b/man/tm_t_crosstable.Rd
@@ -2,7 +2,7 @@
 % Please edit documentation in R/tm_t_crosstable.R
 \name{tm_t_crosstable}
 \alias{tm_t_crosstable}
-\title{Create a simple cross-table}
+\title{Cross-table module}
 \usage{
 tm_t_crosstable(
   label = "Cross Table",
@@ -20,18 +20,22 @@ tm_t_crosstable(
 For \code{modules()} defaults to \code{"root"}. See \code{Details}.}
 
 \item{x}{(\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec})
-Object with all available choices with pre-selected option for variable X - row values. In case
-of \code{data_extract_spec} use \code{select_spec(..., ordered = TRUE)} if table elements should be
+Object with all available choices with pre-selected option for variable X - row values.
+In case of \code{data_extract_spec} use \code{select_spec(..., ordered = TRUE)} if table elements should be
 rendered according to selection order.}
 
 \item{y}{(\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec})
-Object with all available choices with pre-selected option for variable Y - column values
+Object with all available choices with pre-selected option for variable Y - column values.
+
 \code{data_extract_spec} must not allow multiple selection in this case.}
 
-\item{show_percentage}{optional, (\code{logical}) Whether to show percentages
-(relevant only when \code{x} is a \code{factor}). Defaults to \code{TRUE}.}
+\item{show_percentage}{(\code{logical(1)})
+Indicates whether to show percentages (relevant only when \code{x} is a \code{factor}).
+Defaults to \code{TRUE}.}
 
-\item{show_total}{optional, (\code{logical}) Whether to show total column. Defaults to \code{TRUE}.}
+\item{show_total}{(\code{logical(1)})
+Indicates whether to show total column.
+Defaults to \code{TRUE}.}
 
 \item{pre_output}{(\code{shiny.tag}, optional)\cr
 with text placed before the output to put the output into context. For example a title.}
@@ -45,8 +49,12 @@ The argument is merged with options variable \code{teal.basic_table_args} and de
 
 For more details see the vignette: \code{vignette("custom-basic-table-arguments", package = "teal.widgets")}}
 }
+\value{
+Object of class \code{teal_module} to be used in \code{teal} applications.
+}
 \description{
-Create a simple cross-table
+Generates a simple cross-table of two variables from a dataset with custom
+options for showing percentages and sub-totals.
 }
 \note{
 For more examples, please see the vignette "Using cross table" via

From 91d9e0203a0012cfda82b3f74f0b65c6bb5cd10b Mon Sep 17 00:00:00 2001
From: kartikeya kirar <kirar.kartikeya1@gmail.com>
Date: Mon, 26 Feb 2024 19:06:18 +0530
Subject: [PATCH 24/62] pre-release `tm_a_pca` document update (#646)

part of
https://github.com/insightsengineering/teal.modules.general/issues/624

~~blocked by
https://github.com/insightsengineering/teal.modules.general/pull/651~~

---------

Signed-off-by: kartikeya kirar <kirar.kartikeya1@gmail.com>
Co-authored-by: Marcin <133694481+m7pr@users.noreply.github.com>
---
 R/tm_a_pca.R    | 40 +++++++++++++++++++++-------------------
 man/tm_a_pca.Rd | 45 ++++++++++++++++++++++++++-------------------
 2 files changed, 47 insertions(+), 38 deletions(-)

diff --git a/R/tm_a_pca.R b/R/tm_a_pca.R
index a692e589f..f5cf694ff 100644
--- a/R/tm_a_pca.R
+++ b/R/tm_a_pca.R
@@ -1,32 +1,37 @@
 #' Principal component analysis module
-#' @md
+#'
+#' Module conducts principal component analysis (PCA) on a given dataset and offers different
+#' ways of visualizing the outcomes, including elbow plot, circle plot, biplot, and eigenvector plot.
+#' Additionally, it enables dynamic customization of plot aesthetics, such as opacity, size, and
+#' font size, through UI inputs.
 #'
 #' @inheritParams teal::module
 #' @inheritParams shared_params
 #' @param dat (`data_extract_spec` or `list` of multiple `data_extract_spec`)
-#'   Columns used to compute PCA.
-#' @param alpha optional, (`numeric`) If scalar then the plot points will have a fixed opacity. If a
-#'   slider should be presented to adjust the plot point opacity dynamically then it can be a vector of
-#'   length three with `c(value, min, max)`.
-#' @param size optional, (`numeric`) If scalar then the plot point sizes will have a fixed size.
-#'   If a slider should be presented to adjust the plot point sizes dynamically then it can be a
-#'   vector of length three with `c(value, min, max)`.
-#' @param font_size optional, (`numeric`) font size control for title, x-axis label, y-axis label and legend.
-#'   If scalar then the font size will have a fixed size. If a slider should be presented to adjust the plot
-#'   point sizes dynamically then it can be a vector of length three with `c(value, min, max)`.
-#'
+#'   specifying columns used to compute PCA.
+#' @param alpha (`numeric`, optional) Specifies point opacity.
+#' - If vector of `length == 1` then the plot points will have a fixed opacity.
+#' - while vector of `value`, `min`, and `max` allows dynamic adjustment.
+#' @param size (`numeric`, optional) Specifies point size.
+#' - If vector of `length == 1` then the plot point sizes will have a fixed size
+#' - while vector of `value`, `min`, and `max` allows dynamic adjustment.
+#' @param font_size (`numeric`, optional) Specifies font size.
+#' It controls the font size for plot titles, axis labels, and legends.
+#' - If vector of `length == 1` then the font sizes will have a fixed size.
+#' - while vector of `value`, `min`, and `max` allows dynamic adjustment.
 #' @templateVar ggnames "Elbow plot", "Circle plot", "Biplot", "Eigenvector plot"
 #' @template ggplot2_args_multi
 #'
 #' @examples
-#' # general data example
 #' library(teal.widgets)
 #'
+#' # general data example
 #' data <- teal_data()
 #' data <- within(data, {
 #'   require(nestcolor)
 #'   USArrests <- USArrests
 #' })
+#'
 #' datanames(data) <- "USArrests"
 #'
 #' app <- init(
@@ -51,14 +56,11 @@
 #'     )
 #'   )
 #' )
-#'
 #' if (interactive()) {
 #'   shinyApp(app$ui, app$server)
 #' }
 #'
 #' # CDISC data example
-#' library(teal.widgets)
-#'
 #' data <- teal_data()
 #' data <- within(data, {
 #'   require(nestcolor)
@@ -70,7 +72,7 @@
 #' app <- init(
 #'   data = data,
 #'   modules = modules(
-#'     teal.modules.general::tm_a_pca(
+#'     tm_a_pca(
 #'       "PCA",
 #'       dat = data_extract_spec(
 #'         dataname = "ADSL",
@@ -89,7 +91,6 @@
 #'     )
 #'   )
 #' )
-#'
 #' if (interactive()) {
 #'   shinyApp(app$ui, app$server)
 #' }
@@ -171,7 +172,7 @@ tm_a_pca <- function(label = "Principal Component Analysis",
   )
 }
 
-
+# UI function for the PCA module
 ui_a_pca <- function(id, ...) {
   ns <- NS(id)
   args <- list(...)
@@ -282,6 +283,7 @@ ui_a_pca <- function(id, ...) {
   )
 }
 
+# Server function for the PCA module
 srv_a_pca <- function(id, data, reporter, filter_panel_api, dat, plot_height, plot_width, ggplot2_args) {
   with_reporter <- !missing(reporter) && inherits(reporter, "Reporter")
   with_filter <- !missing(filter_panel_api) && inherits(filter_panel_api, "FilterPanelAPI")
diff --git a/man/tm_a_pca.Rd b/man/tm_a_pca.Rd
index c152ab5fe..b72a00134 100644
--- a/man/tm_a_pca.Rd
+++ b/man/tm_a_pca.Rd
@@ -24,7 +24,7 @@ tm_a_pca(
 For \code{modules()} defaults to \code{"root"}. See \code{Details}.}
 
 \item{dat}{(\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec})
-Columns used to compute PCA.}
+specifying columns used to compute PCA.}
 
 \item{plot_height}{optional, (\code{numeric}) A vector of length three with \verb{c(value, min and max)}
 for a slider encoding the plot height.}
@@ -45,17 +45,24 @@ For more details see the vignette: \code{vignette("custom-ggplot2-arguments", pa
 \item{rotate_xaxis_labels}{optional, (\code{logical}) Whether to rotate plot X axis labels. Does not
 rotate by default (\code{FALSE}).}
 
-\item{font_size}{optional, (\code{numeric}) font size control for title, x-axis label, y-axis label and legend.
-If scalar then the font size will have a fixed size. If a slider should be presented to adjust the plot
-point sizes dynamically then it can be a vector of length three with \code{c(value, min, max)}.}
-
-\item{alpha}{optional, (\code{numeric}) If scalar then the plot points will have a fixed opacity. If a
-slider should be presented to adjust the plot point opacity dynamically then it can be a vector of
-length three with \code{c(value, min, max)}.}
-
-\item{size}{optional, (\code{numeric}) If scalar then the plot point sizes will have a fixed size.
-If a slider should be presented to adjust the plot point sizes dynamically then it can be a
-vector of length three with \code{c(value, min, max)}.}
+\item{font_size}{(\code{numeric}, optional) Specifies font size.
+It controls the font size for plot titles, axis labels, and legends.
+\itemize{
+\item If vector of \code{length == 1} then the font sizes will have a fixed size.
+\item while vector of \code{value}, \code{min}, and \code{max} allows dynamic adjustment.
+}}
+
+\item{alpha}{(\code{numeric}, optional) Specifies point opacity.
+\itemize{
+\item If vector of \code{length == 1} then the plot points will have a fixed opacity.
+\item while vector of \code{value}, \code{min}, and \code{max} allows dynamic adjustment.
+}}
+
+\item{size}{(\code{numeric}, optional) Specifies point size.
+\itemize{
+\item If vector of \code{length == 1} then the plot point sizes will have a fixed size
+\item while vector of \code{value}, \code{min}, and \code{max} allows dynamic adjustment.
+}}
 
 \item{pre_output}{(\code{shiny.tag}, optional)\cr
 with text placed before the output to put the output into context. For example a title.}
@@ -64,17 +71,21 @@ with text placed before the output to put the output into context. For example a
 into context. For example the \code{\link[shiny:helpText]{shiny::helpText()}} elements are useful.}
 }
 \description{
-Principal component analysis module
+Module conducts principal component analysis (PCA) on a given dataset and offers different
+ways of visualizing the outcomes, including elbow plot, circle plot, biplot, and eigenvector plot.
+Additionally, it enables dynamic customization of plot aesthetics, such as opacity, size, and
+font size, through UI inputs.
 }
 \examples{
-# general data example
 library(teal.widgets)
 
+# general data example
 data <- teal_data()
 data <- within(data, {
   require(nestcolor)
   USArrests <- USArrests
 })
+
 datanames(data) <- "USArrests"
 
 app <- init(
@@ -99,14 +110,11 @@ app <- init(
     )
   )
 )
-
 if (interactive()) {
   shinyApp(app$ui, app$server)
 }
 
 # CDISC data example
-library(teal.widgets)
-
 data <- teal_data()
 data <- within(data, {
   require(nestcolor)
@@ -118,7 +126,7 @@ join_keys(data) <- default_cdisc_join_keys[datanames(data)]
 app <- init(
   data = data,
   modules = modules(
-    teal.modules.general::tm_a_pca(
+    tm_a_pca(
       "PCA",
       dat = data_extract_spec(
         dataname = "ADSL",
@@ -137,7 +145,6 @@ app <- init(
     )
   )
 )
-
 if (interactive()) {
   shinyApp(app$ui, app$server)
 }

From 2e77e2a2bbdefa021dc576ca74d3741d8d356d12 Mon Sep 17 00:00:00 2001
From: kartikeya kirar <kirar.kartikeya1@gmail.com>
Date: Mon, 26 Feb 2024 19:06:31 +0530
Subject: [PATCH 25/62] pre-release `tm_outliers` document update (#653)

part of
https://github.com/insightsengineering/teal.modules.general/issues/624
---
 R/tm_outliers.R    | 16 +++++++++-------
 man/tm_outliers.Rd | 14 +++++++-------
 2 files changed, 16 insertions(+), 14 deletions(-)

diff --git a/R/tm_outliers.R b/R/tm_outliers.R
index 926367fe9..34cccf2b2 100644
--- a/R/tm_outliers.R
+++ b/R/tm_outliers.R
@@ -1,22 +1,24 @@
-#' Outliers Module
+#' Outliers module
 #'
 #' Module to analyze and identify outliers using different methods
+#' such as IQR, Z-score, and Percentiles, and offers visualizations including
+#' box plots, density plots, and cumulative distribution plots to help interpret the outliers.
 #'
 #' @inheritParams teal::module
 #' @inheritParams shared_params
 #'
 #' @param outlier_var (`data_extract_spec` or `list` of multiple `data_extract_spec`)
-#'  variable to consider for the outliers analysis.
-#' @param categorical_var (`data_extract_spec` or `list` of multiple `data_extract_spec`)
-#'   categorical factor to split the selected outlier variables on.
+#' Specifies variable(s) to be analyzed for outliers.
+#' @param categorical_var (`data_extract_spec` or `list` of multiple `data_extract_spec`, optional)
+#' Specifies the categorical variable(s) to split the selected outlier variables on.
 #'
 #' @templateVar ggnames "Boxplot","Density Plot","Cumulative Distribution Plot"
 #' @template ggplot2_args_multi
 #'
 #' @examples
-#' # general data example
 #' library(teal.widgets)
 #'
+#' # general data example
 #' data <- teal_data()
 #' data <- within(data, {
 #'   CO2 <- CO2
@@ -67,8 +69,6 @@
 #' }
 #'
 #' # CDISC data example
-#' library(teal.widgets)
-#'
 #' data <- teal_data()
 #' data <- within(data, {
 #'   ADSL <- rADSL
@@ -169,6 +169,7 @@ tm_outliers <- function(label = "Outliers Module",
   )
 }
 
+# UI function for the outliers module
 ui_outliers <- function(id, ...) {
   args <- list(...)
   ns <- NS(id)
@@ -300,6 +301,7 @@ ui_outliers <- function(id, ...) {
   )
 }
 
+# Server function for the outliers module
 srv_outliers <- function(id, data, reporter, filter_panel_api, outlier_var,
                          categorical_var, plot_height, plot_width, ggplot2_args) {
   with_reporter <- !missing(reporter) && inherits(reporter, "Reporter")
diff --git a/man/tm_outliers.Rd b/man/tm_outliers.Rd
index d6efe45fa..b0898aa19 100644
--- a/man/tm_outliers.Rd
+++ b/man/tm_outliers.Rd
@@ -2,7 +2,7 @@
 % Please edit documentation in R/tm_outliers.R
 \name{tm_outliers}
 \alias{tm_outliers}
-\title{Outliers Module}
+\title{Outliers module}
 \usage{
 tm_outliers(
   label = "Outliers Module",
@@ -21,10 +21,10 @@ tm_outliers(
 For \code{modules()} defaults to \code{"root"}. See \code{Details}.}
 
 \item{outlier_var}{(\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec})
-variable to consider for the outliers analysis.}
+Specifies variable(s) to be analyzed for outliers.}
 
-\item{categorical_var}{(\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec})
-categorical factor to split the selected outlier variables on.}
+\item{categorical_var}{(\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec}, optional)
+Specifies the categorical variable(s) to split the selected outlier variables on.}
 
 \item{ggtheme}{optional, (\code{character}) \code{ggplot2} theme to be used by default. Defaults to \code{"gray"}.}
 
@@ -50,11 +50,13 @@ into context. For example the \code{\link[shiny:helpText]{shiny::helpText()}} el
 }
 \description{
 Module to analyze and identify outliers using different methods
+such as IQR, Z-score, and Percentiles, and offers visualizations including
+box plots, density plots, and cumulative distribution plots to help interpret the outliers.
 }
 \examples{
-# general data example
 library(teal.widgets)
 
+# general data example
 data <- teal_data()
 data <- within(data, {
   CO2 <- CO2
@@ -105,8 +107,6 @@ if (interactive()) {
 }
 
 # CDISC data example
-library(teal.widgets)
-
 data <- teal_data()
 data <- within(data, {
   ADSL <- rADSL

From d5fbe8c2d3b72b217020ef7d2cc7390c8039b450 Mon Sep 17 00:00:00 2001
From: kartikeya kirar <kirar.kartikeya1@gmail.com>
Date: Mon, 26 Feb 2024 19:06:47 +0530
Subject: [PATCH 26/62] pre-release `tm_front_page` document update (#654)

part of
https://github.com/insightsengineering/teal.modules.general/issues/624
---
 R/tm_front_page.R    | 124 +++++++++++++++++++++++--------------------
 man/tm_front_page.Rd |  28 +++++-----
 2 files changed, 80 insertions(+), 72 deletions(-)

diff --git a/R/tm_front_page.R b/R/tm_front_page.R
index e2d7def39..c10ef2bd0 100644
--- a/R/tm_front_page.R
+++ b/R/tm_front_page.R
@@ -1,20 +1,20 @@
 #' Front page module
 #'
-#' @description This `teal` module creates a simple front page for `teal` applications
+#' Creates a simple front page for `teal` applications, displaying
+#' introductory text, tables, additional `html` or `shiny` tags, and footnotes.
 #'
 #' @inheritParams teal::module
-#' @param header_text `character vector` text to be shown at the top of the module, for each
-#'   element, if named the name is shown first in bold as a header followed by the value. The first
-#'   element's header is displayed larger than the others
-#' @param tables `named list of dataframes` tables to be shown in the module
-#' @param additional_tags `shiny.tag.list` or `html` additional shiny tags or `html` to be included after the table,
-#'   for example to include an image, `tagList(tags$img(src = "image.png"))` or to include further `html`,
-#'   `HTML("html text here")`
-#' @param footnotes `character vector` text to be shown at the bottom of the module, for each
-#'   element, if named the name is shown first in bold, followed by the value
-#' @param show_metadata `logical` should the metadata of the datasets be available on the module?
-#' @return A `teal` module to be used in `teal` applications
-#' @export
+#' @param header_text (`character` vector) text to be shown at the top of the module, for each
+#' element, if named the name is shown first in bold as a header followed by the value. The first
+#' element's header is displayed larger than the others.
+#' @param tables (`named list` of `data.frame`s) tables to be shown in the module.
+#' @param additional_tags (`shiny.tag.list` or `html`) additional shiny tags or `html` to be included after the table,
+#' for example to include an image, `tagList(tags$img(src = "image.png"))` or to include further `html`,
+#' `HTML("html text here")`.
+#' @param footnotes (`character` vector) of text to be shown at the bottom of the module, for each
+#' element, if named the name is shown first in bold, followed by the value.
+#' @param show_metadata (`logical`) indicating whether the metadata of the datasets be available on the module.
+#'
 #' @examples
 #'
 #' data <- teal_data()
@@ -37,9 +37,9 @@
 #'   "Table 3" = table_3
 #' )
 #'
-#' app <- teal::init(
+#' app <- init(
 #'   data = data,
-#'   modules = teal::modules(
+#'   modules = modules(
 #'     teal.modules.general::tm_front_page(
 #'       header_text = c(
 #'         "Important information" = "It can go here.",
@@ -54,9 +54,13 @@
 #'   header = tags$h1("Sample Application"),
 #'   footer = tags$p("Application footer"),
 #' )
+#'
 #' if (interactive()) {
 #'   shinyApp(app$ui, app$server)
 #' }
+#'
+#' @export
+#'
 tm_front_page <- function(label = "Front page",
                           header_text = character(0),
                           tables = list(),
@@ -83,6 +87,7 @@ tm_front_page <- function(label = "Front page",
   )
 }
 
+# UI function for the front page module
 ui_front_page <- function(id, ...) {
   args <- list(...)
   ns <- NS(id)
@@ -121,6 +126,52 @@ ui_front_page <- function(id, ...) {
   )
 }
 
+# Server function for the front page module
+srv_front_page <- function(id, data, tables, show_metadata) {
+  checkmate::assert_class(data, "reactive")
+  checkmate::assert_class(isolate(data()), "teal_data")
+  moduleServer(id, function(input, output, session) {
+    ns <- session$ns
+
+    lapply(seq_along(tables), function(idx) {
+      output[[paste0("table_", idx)]] <- renderTable(
+        tables[[idx]],
+        bordered = TRUE,
+        caption = names(tables)[idx],
+        caption.placement = "top"
+      )
+    })
+
+    if (show_metadata) {
+      observeEvent(
+        input$metadata_button, showModal(
+          modalDialog(
+            title = "Metadata",
+            dataTableOutput(ns("metadata_table")),
+            size = "l",
+            easyClose = TRUE
+          )
+        )
+      )
+
+      metadata_data_frame <- reactive({
+        datanames <- teal.data::datanames(data())
+        convert_metadata_to_dataframe(
+          lapply(datanames, function(dataname) attr(data()[[dataname]], "metadata")),
+          datanames
+        )
+      })
+
+      output$metadata_table <- renderDataTable({
+        validate(need(nrow(metadata_data_frame()) > 0, "The data has no associated metadata"))
+        metadata_data_frame()
+      })
+    }
+  })
+}
+
+## utils functions
+
 get_header_tags <- function(header_text) {
   if (length(header_text) == 0) {
     return(list())
@@ -167,49 +218,6 @@ get_footer_tags <- function(footnotes) {
   }, bold_text = bold_texts, value = footnotes)
 }
 
-srv_front_page <- function(id, data, tables, show_metadata) {
-  checkmate::assert_class(data, "reactive")
-  checkmate::assert_class(isolate(data()), "teal_data")
-  moduleServer(id, function(input, output, session) {
-    ns <- session$ns
-
-    lapply(seq_along(tables), function(idx) {
-      output[[paste0("table_", idx)]] <- renderTable(
-        tables[[idx]],
-        bordered = TRUE,
-        caption = names(tables)[idx],
-        caption.placement = "top"
-      )
-    })
-
-    if (show_metadata) {
-      observeEvent(
-        input$metadata_button, showModal(
-          modalDialog(
-            title = "Metadata",
-            dataTableOutput(ns("metadata_table")),
-            size = "l",
-            easyClose = TRUE
-          )
-        )
-      )
-
-      metadata_data_frame <- reactive({
-        datanames <- teal.data::datanames(data())
-        convert_metadata_to_dataframe(
-          lapply(datanames, function(dataname) attr(data()[[dataname]], "metadata")),
-          datanames
-        )
-      })
-
-      output$metadata_table <- renderDataTable({
-        validate(need(nrow(metadata_data_frame()) > 0, "The data has no associated metadata"))
-        metadata_data_frame()
-      })
-    }
-  })
-}
-
 # take a list of metadata, one item per dataset (raw_metadata each element from datasets$get_metadata())
 # and the corresponding datanames and output a data.frame with columns {Dataset, Name, Value}.
 # which are, the Dataset the metadata came from, the metadata's name and value
diff --git a/man/tm_front_page.Rd b/man/tm_front_page.Rd
index 20499592a..e8ca98d77 100644
--- a/man/tm_front_page.Rd
+++ b/man/tm_front_page.Rd
@@ -17,26 +17,24 @@ tm_front_page(
 \item{label}{(\code{character(1)}) Label shown in the navigation item for the module or module group.
 For \code{modules()} defaults to \code{"root"}. See \code{Details}.}
 
-\item{header_text}{\verb{character vector} text to be shown at the top of the module, for each
+\item{header_text}{(\code{character} vector) text to be shown at the top of the module, for each
 element, if named the name is shown first in bold as a header followed by the value. The first
-element's header is displayed larger than the others}
+element's header is displayed larger than the others.}
 
-\item{tables}{\verb{named list of dataframes} tables to be shown in the module}
+\item{tables}{(\verb{named list} of \code{data.frame}s) tables to be shown in the module.}
 
-\item{additional_tags}{\code{shiny.tag.list} or \code{html} additional shiny tags or \code{html} to be included after the table,
+\item{additional_tags}{(\code{shiny.tag.list} or \code{html}) additional shiny tags or \code{html} to be included after the table,
 for example to include an image, \code{tagList(tags$img(src = "image.png"))} or to include further \code{html},
-\code{HTML("html text here")}}
+\code{HTML("html text here")}.}
 
-\item{footnotes}{\verb{character vector} text to be shown at the bottom of the module, for each
-element, if named the name is shown first in bold, followed by the value}
+\item{footnotes}{(\code{character} vector) of text to be shown at the bottom of the module, for each
+element, if named the name is shown first in bold, followed by the value.}
 
-\item{show_metadata}{\code{logical} should the metadata of the datasets be available on the module?}
-}
-\value{
-A \code{teal} module to be used in \code{teal} applications
+\item{show_metadata}{(\code{logical}) indicating whether the metadata of the datasets be available on the module.}
 }
 \description{
-This \code{teal} module creates a simple front page for \code{teal} applications
+Creates a simple front page for \code{teal} applications, displaying
+introductory text, tables, additional \code{html} or \code{shiny} tags, and footnotes.
 }
 \examples{
 
@@ -60,9 +58,9 @@ table_input <- list(
   "Table 3" = table_3
 )
 
-app <- teal::init(
+app <- init(
   data = data,
-  modules = teal::modules(
+  modules = modules(
     teal.modules.general::tm_front_page(
       header_text = c(
         "Important information" = "It can go here.",
@@ -77,7 +75,9 @@ app <- teal::init(
   header = tags$h1("Sample Application"),
   footer = tags$p("Application footer"),
 )
+
 if (interactive()) {
   shinyApp(app$ui, app$server)
 }
+
 }

From 33714aee5513291925caf89c0b598b6d5c6d4573 Mon Sep 17 00:00:00 2001
From: kartikeya kirar <kirar.kartikeya1@gmail.com>
Date: Mon, 26 Feb 2024 19:31:12 +0530
Subject: [PATCH 27/62] pre-release `tm_g_scatterplot` document update (#657)

part of
https://github.com/insightsengineering/teal.modules.general/issues/624
---
 R/tm_g_scatterplot.R    | 68 ++++++++++++++++++++---------------------
 man/tm_g_scatterplot.Rd | 54 +++++++++++++++++---------------
 2 files changed, 63 insertions(+), 59 deletions(-)

diff --git a/R/tm_g_scatterplot.R b/R/tm_g_scatterplot.R
index 7f1f5d84d..2bed23a61 100644
--- a/R/tm_g_scatterplot.R
+++ b/R/tm_g_scatterplot.R
@@ -1,42 +1,43 @@
-#' Create a simple scatterplot
-#'
-#' Create a plot with the \code{\link{ggplot2}[geom_point]} function
-#' @md
-#'
-#' @inheritParams teal::module
-#' @inheritParams shared_params
-#' @param x (`data_extract_spec` or `list` of multiple `data_extract_spec`) Variable
-#'   names selected to plot along the x-axis by default.
-#' @param y (`data_extract_spec` or `list` of multiple `data_extract_spec`) Variable
-#'   names selected to plot along the y-axis by default.
-#' @param color_by optional (`data_extract_spec` or `list` of multiple `data_extract_spec`)
-#'   Defines the color encoding. If `NULL` then no color encoding option will be displayed.
-#' @param size_by optional (`data_extract_spec` or `list` of multiple `data_extract_spec`)
-#'   Defines the point size encoding. If `NULL` then no size encoding option will be displayed.
-#' @param row_facet optional, (`data_extract_spec` or `list` of multiple `data_extract_spec`)
-#'   Which data columns to use for faceting rows.
-#' @param col_facet optional, (`data_extract_spec` or `list` of multiple `data_extract_spec`)
-#'   Which data to use for faceting columns.
-#' @param alpha optional, (`numeric`) If scalar then the plot points will have a fixed opacity. If a
-#'   slider should be presented to adjust the plot point opacity dynamically then it can be a vector of
-#'   length three with `c(value, min, max)`.
-#' @param size optional, (`numeric`) If scalar then the plot point sizes will have a fixed size
-#'   If a slider should be presented to adjust the plot point sizes dynamically then it can be a
-#'   vector of length three with `c(value, min, max)`.
-#' @param shape optional, (`character`) A character vector with the English names of the
-#'   shape, e.g. `c("triangle", "square", "circle")`. It defaults to `shape_names`. This is a complete list from
-#'   `vignette("ggplot2-specs", package="ggplot2")`.
-#' @param max_deg optional, (`integer`) The maximum degree for the polynomial trend line. Must not be less than 1.
-#' @param table_dec optional, (`integer`) Number of decimal places used to round numeric values in the table.
+#' Scatterplot module
 #'
+#' Generates a customizable scatterplot using `ggplot2`.
+#' This module allows users to select variables for the x and y axes,
+#' color and size encodings, faceting options, and more. It supports log transformations,
+#' trend line additions, and dynamic adjustments of point opacity and size through UI controls.
 #'
 #' @note For more examples, please see the vignette "Using scatterplot" via
 #'   `vignette("using-scatterplot", package = "teal.modules.general")`.
 #'
+#' @inheritParams teal::module
+#' @inheritParams shared_params
+#' @param x (`data_extract_spec` or `list` of multiple `data_extract_spec`) Specifies
+#' variable names selected to plot along the x-axis by default.
+#' @param y (`data_extract_spec` or `list` of multiple `data_extract_spec`) Specifies
+#' variable names selected to plot along the y-axis by default.
+#' @param color_by (`data_extract_spec` or `list` of multiple `data_extract_spec`, optional)
+#' Defines the color encoding. If `NULL` then no color encoding option will be displayed.
+#' @param size_by (`data_extract_spec` or `list` of multiple `data_extract_spec`, optional)
+#' Defines the point size encoding. If `NULL` then no size encoding option will be displayed.
+#' @param row_facet (`data_extract_spec` or `list` of multiple `data_extract_spec`, optional)
+#' Specifies the variable(s) for faceting rows.
+#' @param col_facet (`data_extract_spec` or `list` of multiple `data_extract_spec`, optional)
+#' Specifies the variable(s) for faceting columns.
+#' @param alpha (`numeric`, optional) Specifies point opacity.
+#' - If vector of `length == 1` then the plot points will have a fixed opacity.
+#' - while vector of `value`, `min`, and `max` allows dynamic adjustment.
+#' @param size (`numeric`, optional) Specifies point size.
+#' - If vector of `length == 1` then the plot point sizes will have a fixed size
+#' - while vector of `value`, `min`, and `max` allows dynamic adjustment.
+#' @param shape (`character`, optional) A character vector with the names of the
+#' shape, e.g. `c("triangle", "square", "circle")`. It defaults to `shape_names`. This is a complete list from
+#' `vignette("ggplot2-specs", package="ggplot2")`.
+#' @param max_deg (`integer`, optional) The maximum degree for the polynomial trend line. Must not be less than 1.
+#' @param table_dec (`integer`, optional) Number of decimal places used to round numeric values in the table.
+#'
 #' @examples
-#' # general data example
 #' library(teal.widgets)
 #'
+#' # general data example
 #' data <- teal_data()
 #' data <- within(data, {
 #'   require(nestcolor)
@@ -122,10 +123,7 @@
 #'   shinyApp(app$ui, app$server)
 #' }
 #'
-#'
 #' # CDISC data example
-#' library(teal.widgets)
-#'
 #' data <- teal_data()
 #' data <- within(data, {
 #'   require(nestcolor)
@@ -320,6 +318,7 @@ tm_g_scatterplot <- function(label = "Scatterplot",
   )
 }
 
+# UI function for the scatterplot module
 ui_g_scatterplot <- function(id, ...) {
   args <- list(...)
   ns <- NS(id)
@@ -471,6 +470,7 @@ ui_g_scatterplot <- function(id, ...) {
   )
 }
 
+# Server function for the scatterplot module
 srv_g_scatterplot <- function(id,
                               data,
                               reporter,
diff --git a/man/tm_g_scatterplot.Rd b/man/tm_g_scatterplot.Rd
index 54e0dfd79..c6f80e12f 100644
--- a/man/tm_g_scatterplot.Rd
+++ b/man/tm_g_scatterplot.Rd
@@ -2,7 +2,7 @@
 % Please edit documentation in R/tm_g_scatterplot.R
 \name{tm_g_scatterplot}
 \alias{tm_g_scatterplot}
-\title{Create a simple scatterplot}
+\title{Scatterplot module}
 \usage{
 tm_g_scatterplot(
   label = "Scatterplot",
@@ -30,23 +30,23 @@ tm_g_scatterplot(
 \item{label}{(\code{character(1)}) Label shown in the navigation item for the module or module group.
 For \code{modules()} defaults to \code{"root"}. See \code{Details}.}
 
-\item{x}{(\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec}) Variable
-names selected to plot along the x-axis by default.}
+\item{x}{(\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec}) Specifies
+variable names selected to plot along the x-axis by default.}
 
-\item{y}{(\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec}) Variable
-names selected to plot along the y-axis by default.}
+\item{y}{(\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec}) Specifies
+variable names selected to plot along the y-axis by default.}
 
-\item{color_by}{optional (\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec})
+\item{color_by}{(\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec}, optional)
 Defines the color encoding. If \code{NULL} then no color encoding option will be displayed.}
 
-\item{size_by}{optional (\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec})
+\item{size_by}{(\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec}, optional)
 Defines the point size encoding. If \code{NULL} then no size encoding option will be displayed.}
 
-\item{row_facet}{optional, (\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec})
-Which data columns to use for faceting rows.}
+\item{row_facet}{(\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec}, optional)
+Specifies the variable(s) for faceting rows.}
 
-\item{col_facet}{optional, (\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec})
-Which data to use for faceting columns.}
+\item{col_facet}{(\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec}, optional)
+Specifies the variable(s) for faceting columns.}
 
 \item{plot_height}{optional, (\code{numeric}) A vector of length three with \verb{c(value, min and max)}
 for a slider encoding the plot height.}
@@ -54,19 +54,23 @@ for a slider encoding the plot height.}
 \item{plot_width}{optional, (\code{numeric}) A vector of length three with \verb{c(value, min and max)}
 for a slider encoding the plot width.}
 
-\item{alpha}{optional, (\code{numeric}) If scalar then the plot points will have a fixed opacity. If a
-slider should be presented to adjust the plot point opacity dynamically then it can be a vector of
-length three with \code{c(value, min, max)}.}
+\item{alpha}{(\code{numeric}, optional) Specifies point opacity.
+\itemize{
+\item If vector of \code{length == 1} then the plot points will have a fixed opacity.
+\item while vector of \code{value}, \code{min}, and \code{max} allows dynamic adjustment.
+}}
 
-\item{shape}{optional, (\code{character}) A character vector with the English names of the
+\item{shape}{(\code{character}, optional) A character vector with the names of the
 shape, e.g. \code{c("triangle", "square", "circle")}. It defaults to \code{shape_names}. This is a complete list from
 \code{vignette("ggplot2-specs", package="ggplot2")}.}
 
-\item{size}{optional, (\code{numeric}) If scalar then the plot point sizes will have a fixed size
-If a slider should be presented to adjust the plot point sizes dynamically then it can be a
-vector of length three with \code{c(value, min, max)}.}
+\item{size}{(\code{numeric}, optional) Specifies point size.
+\itemize{
+\item If vector of \code{length == 1} then the plot point sizes will have a fixed size
+\item while vector of \code{value}, \code{min}, and \code{max} allows dynamic adjustment.
+}}
 
-\item{max_deg}{optional, (\code{integer}) The maximum degree for the polynomial trend line. Must not be less than 1.}
+\item{max_deg}{(\code{integer}, optional) The maximum degree for the polynomial trend line. Must not be less than 1.}
 
 \item{rotate_xaxis_labels}{optional, (\code{logical}) Whether to rotate plot X axis labels. Does not
 rotate by default (\code{FALSE}).}
@@ -79,7 +83,7 @@ with text placed before the output to put the output into context. For example a
 \item{post_output}{(\code{shiny.tag}, optional) with text placed after the output to put the output
 into context. For example the \code{\link[shiny:helpText]{shiny::helpText()}} elements are useful.}
 
-\item{table_dec}{optional, (\code{integer}) Number of decimal places used to round numeric values in the table.}
+\item{table_dec}{(\code{integer}, optional) Number of decimal places used to round numeric values in the table.}
 
 \item{ggplot2_args}{(\code{ggplot2_args}) object created by \code{\link[teal.widgets:ggplot2_args]{teal.widgets::ggplot2_args()}}
 with settings for the module plot.
@@ -88,16 +92,19 @@ The argument is merged with options variable \code{teal.ggplot2_args} and defaul
 For more details see the vignette: \code{vignette("custom-ggplot2-arguments", package = "teal.widgets")}}
 }
 \description{
-Create a plot with the \code{\link{ggplot2}[geom_point]} function
+Generates a customizable scatterplot using \code{ggplot2}.
+This module allows users to select variables for the x and y axes,
+color and size encodings, faceting options, and more. It supports log transformations,
+trend line additions, and dynamic adjustments of point opacity and size through UI controls.
 }
 \note{
 For more examples, please see the vignette "Using scatterplot" via
 \code{vignette("using-scatterplot", package = "teal.modules.general")}.
 }
 \examples{
-# general data example
 library(teal.widgets)
 
+# general data example
 data <- teal_data()
 data <- within(data, {
   require(nestcolor)
@@ -183,10 +190,7 @@ if (interactive()) {
   shinyApp(app$ui, app$server)
 }
 
-
 # CDISC data example
-library(teal.widgets)
-
 data <- teal_data()
 data <- within(data, {
   require(nestcolor)

From 2d70eabdbfff79508e39470666e83c9d15206bd9 Mon Sep 17 00:00:00 2001
From: kartikeya kirar <kirar.kartikeya1@gmail.com>
Date: Mon, 26 Feb 2024 19:41:49 +0530
Subject: [PATCH 28/62]  pre-release ` tm_data_table`  document update (#667)

part of
https://github.com/insightsengineering/teal.modules.general/issues/624

---------

Signed-off-by: kartikeya kirar <kirar.kartikeya1@gmail.com>
Co-authored-by: Marcin <133694481+m7pr@users.noreply.github.com>
---
 R/tm_data_table.R    | 52 ++++++++++++++++++++++----------------------
 man/tm_data_table.Rd | 31 +++++++++++++-------------
 2 files changed, 42 insertions(+), 41 deletions(-)

diff --git a/R/tm_data_table.R b/R/tm_data_table.R
index df7888227..9d6cd866c 100644
--- a/R/tm_data_table.R
+++ b/R/tm_data_table.R
@@ -1,34 +1,34 @@
-#' Data Table Viewer `teal` Module
+#' Data table viewer module
 #'
-#' A data table viewer shows the data using a paginated table.
-#' specifically designed for use with `data.frames`.
-#' @md
+#' Module provides a dynamic and interactive way to view `data.frame`s in a `teal` application.
+#' It uses the `DT` package to display data tables in a paginated, searchable, and sortable format,
+#' which helps to enhance data exploration and analysis.
+#'
+#' The `DT` package has an option `DT.TOJSON_ARGS` to show `Inf` and `NA` in data tables.
+#' Configure the `DT.TOJSON_ARGS` option via
+#' `options(DT.TOJSON_ARGS = list(na = "string"))` before running the module.
+#' Note though that sorting of numeric columns with `NA`/`Inf` will be lexicographic not numerical.
 #'
 #' @inheritParams teal::module
 #' @inheritParams shared_params
-#' @param variables_selected (`list`) A named list of character vectors of the variables (i.e. columns)
-#'   which should be initially shown for each dataset. Names of list elements should correspond to the names
-#'   of the datasets available in the app. If no entry is specified for a dataset, the first six variables from that
-#'   dataset will initially be shown.
+#' @param variables_selected (`named list`) Character vectors of the variables (i.e. columns)
+#' which should be initially shown for each dataset.
+#' Names of list elements should correspond to the names of the datasets available in the app.
+#' If no entry is specified for a dataset, the first six variables from that
+#' dataset will initially be shown.
 #' @param datasets_selected (`character`) A vector of datasets which should be
-#'   shown and in what order. Names in the vector have to correspond with datasets names.
-#'   If vector of length zero (default) then all datasets are shown.
-#'   Note: Only datasets of the `data.frame` class are compatible;
-#'   using other types will cause an error.
-#' @param dt_args (named `list`) Additional arguments to be passed to `DT::datatable`
-#'   (must not include `data` or `options`).
-#' @param dt_options (named `list`) The `options` argument to `DT::datatable`. By default
-#'   `list(searching = FALSE, pageLength = 30, lengthMenu = c(5, 15, 30, 100), scrollX = TRUE)`
+#' shown and in what order. Names in the vector have to correspond with datasets names.
+#' If vector of `length == 0` (default) then all datasets are shown.
+#' Note: Only datasets of the `data.frame` class are compatible.
+#' @param dt_args (`named list`) Additional arguments to be passed to [DT::datatable()]
+#' (must not include `data` or `options`).
+#' @param dt_options (`named list`) The `options` argument to `DT::datatable`. By default
+#' `list(searching = FALSE, pageLength = 30, lengthMenu = c(5, 15, 30, 100), scrollX = TRUE)`
 #' @param server_rendering (`logical`) should the data table be rendered server side
-#'   (see `server` argument of `DT::renderDataTable()`)
-#' @details
-#'   The `DT` package has an option `DT.TOJSON_ARGS` to show `Inf` and `NA` in data tables. If this is something
-#'   you require then set `options(DT.TOJSON_ARGS =  list(na = "string"))` before running the module.
-#'   Note though that sorting of numeric columns with `NA`/`Inf` will be lexicographic not numerical.
+#' (see `server` argument of [DT::renderDataTable()])
 #'
 #' @examples
 #' # general data example
-#'
 #' data <- teal_data()
 #' data <- within(data, {
 #'   require(nestcolor)
@@ -127,8 +127,7 @@ tm_data_table <- function(label = "Data Table",
   )
 }
 
-
-# ui page module
+# UI page module
 ui_page_data_table <- function(id,
                                pre_output = NULL,
                                post_output = NULL) {
@@ -162,8 +161,7 @@ ui_page_data_table <- function(id,
   )
 }
 
-
-# server page module
+# Server page module
 srv_page_data_table <- function(id,
                                 data,
                                 datasets_selected,
@@ -247,6 +245,7 @@ srv_page_data_table <- function(id,
   })
 }
 
+# UI function for the data_table module
 ui_data_table <- function(id,
                           choices,
                           selected) {
@@ -276,6 +275,7 @@ ui_data_table <- function(id,
   )
 }
 
+# Server function for the data_table module
 srv_data_table <- function(id,
                            data,
                            dataname,
diff --git a/man/tm_data_table.Rd b/man/tm_data_table.Rd
index 8cbdde1f0..3b4136be5 100644
--- a/man/tm_data_table.Rd
+++ b/man/tm_data_table.Rd
@@ -2,7 +2,7 @@
 % Please edit documentation in R/tm_data_table.R
 \name{tm_data_table}
 \alias{tm_data_table}
-\title{Data Table Viewer \code{teal} Module}
+\title{Data table viewer module}
 \usage{
 tm_data_table(
   label = "Data Table",
@@ -20,25 +20,25 @@ tm_data_table(
 \item{label}{(\code{character(1)}) Label shown in the navigation item for the module or module group.
 For \code{modules()} defaults to \code{"root"}. See \code{Details}.}
 
-\item{variables_selected}{(\code{list}) A named list of character vectors of the variables (i.e. columns)
-which should be initially shown for each dataset. Names of list elements should correspond to the names
-of the datasets available in the app. If no entry is specified for a dataset, the first six variables from that
+\item{variables_selected}{(\verb{named list}) Character vectors of the variables (i.e. columns)
+which should be initially shown for each dataset.
+Names of list elements should correspond to the names of the datasets available in the app.
+If no entry is specified for a dataset, the first six variables from that
 dataset will initially be shown.}
 
 \item{datasets_selected}{(\code{character}) A vector of datasets which should be
 shown and in what order. Names in the vector have to correspond with datasets names.
-If vector of length zero (default) then all datasets are shown.
-Note: Only datasets of the \code{data.frame} class are compatible;
-using other types will cause an error.}
+If vector of \code{length == 0} (default) then all datasets are shown.
+Note: Only datasets of the \code{data.frame} class are compatible.}
 
-\item{dt_args}{(named \code{list}) Additional arguments to be passed to \code{DT::datatable}
+\item{dt_args}{(\verb{named list}) Additional arguments to be passed to \code{\link[DT:datatable]{DT::datatable()}}
 (must not include \code{data} or \code{options}).}
 
-\item{dt_options}{(named \code{list}) The \code{options} argument to \code{DT::datatable}. By default
+\item{dt_options}{(\verb{named list}) The \code{options} argument to \code{DT::datatable}. By default
 \code{list(searching = FALSE, pageLength = 30, lengthMenu = c(5, 15, 30, 100), scrollX = TRUE)}}
 
 \item{server_rendering}{(\code{logical}) should the data table be rendered server side
-(see \code{server} argument of \code{DT::renderDataTable()})}
+(see \code{server} argument of \code{\link[DT:dataTableOutput]{DT::renderDataTable()}})}
 
 \item{pre_output}{(\code{shiny.tag}, optional)\cr
 with text placed before the output to put the output into context. For example a title.}
@@ -47,17 +47,18 @@ with text placed before the output to put the output into context. For example a
 into context. For example the \code{\link[shiny:helpText]{shiny::helpText()}} elements are useful.}
 }
 \description{
-A data table viewer shows the data using a paginated table.
-specifically designed for use with \code{data.frames}.
+Module provides a dynamic and interactive way to view \code{data.frame}s in a \code{teal} application.
+It uses the \code{DT} package to display data tables in a paginated, searchable, and sortable format,
+which helps to enhance data exploration and analysis.
 }
 \details{
-The \code{DT} package has an option \code{DT.TOJSON_ARGS} to show \code{Inf} and \code{NA} in data tables. If this is something
-you require then set \code{options(DT.TOJSON_ARGS =  list(na = "string"))} before running the module.
+The \code{DT} package has an option \code{DT.TOJSON_ARGS} to show \code{Inf} and \code{NA} in data tables.
+Configure the \code{DT.TOJSON_ARGS} option via
+\code{options(DT.TOJSON_ARGS = list(na = "string"))} before running the module.
 Note though that sorting of numeric columns with \code{NA}/\code{Inf} will be lexicographic not numerical.
 }
 \examples{
 # general data example
-
 data <- teal_data()
 data <- within(data, {
   require(nestcolor)

From b382d4c381d37b1e007794e4a87dc68155564ab3 Mon Sep 17 00:00:00 2001
From: kartikeya kirar <kirar.kartikeya1@gmail.com>
Date: Mon, 26 Feb 2024 19:50:12 +0530
Subject: [PATCH 29/62] pre-release other utils functions document update 
 (#676)

part of
https://github.com/insightsengineering/teal.modules.general/issues/624

---------

Signed-off-by: kartikeya kirar <kirar.kartikeya1@gmail.com>
Co-authored-by: Vedha Viyash <49812166+vedhav@users.noreply.github.com>
---
 R/data.R                      |  27 +-------
 R/teal.modules.general.R      |   2 +-
 R/utils.R                     | 125 +++++++++++++++++-----------------
 man/add_facet_labels.Rd       |  22 +++---
 man/call_fun_dots.Rd          |   7 +-
 man/include_css_files.Rd      |   4 +-
 man/is_tab_active_js.Rd       |  12 ++--
 man/rADTTE.Rd                 |   4 +-
 man/shared_params.Rd          |  21 +++---
 man/teal.modules.general.Rd   |   2 +-
 man/tm_a_pca.Rd               |  15 ++--
 man/tm_a_regression.Rd        |  15 ++--
 man/tm_data_table.Rd          |   7 +-
 man/tm_g_association.Rd       |  15 ++--
 man/tm_g_bivariate.Rd         |  15 ++--
 man/tm_g_distribution.Rd      |   8 +--
 man/tm_g_response.Rd          |  15 ++--
 man/tm_g_scatterplot.Rd       |  15 ++--
 man/tm_g_scatterplotmatrix.Rd |  15 ++--
 man/tm_missing_data.Rd        |  15 ++--
 man/tm_outliers.Rd            |  15 ++--
 man/tm_t_crosstable.Rd        |   7 +-
 man/tm_variable_browser.Rd    |   7 +-
 man/variable_type_icons.Rd    |  10 +--
 man/varname_w_label.Rd        |  11 +--
 25 files changed, 199 insertions(+), 212 deletions(-)

diff --git a/R/data.R b/R/data.R
index 55670eebe..0f8a64e04 100644
--- a/R/data.R
+++ b/R/data.R
@@ -1,64 +1,39 @@
 #' Random adverse events
-#'
-#' @description Random adverse events
 #' @docType data
-#'
 #' @usage rADAE
-#'
 #' @keywords datasets internal
-#'
 #' @source internal
 #' @name rADAE
 "rADAE"
 
 #' Random lab analysis
-#'
-#' @description Random lab analysis
 #' @docType data
-#'
 #' @usage rADLB
-#'
 #' @keywords datasets internal
-#'
 #' @source internal
 #' @name rADLB
 "rADLB"
 
 #' Random response
-#'
-#' @description Random response
 #' @docType data
-#'
 #' @usage rADRS
-#'
 #' @keywords datasets internal
-#'
 #' @source internal
 #' @name rADRS
 "rADRS"
 
 #' Random patient listing
-#'
-#' @description Random patient listing
 #' @docType data
-#'
 #' @usage rADSL
-#'
 #' @keywords datasets internal
-#'
 #' @source internal
 #' @name rADSL
 "rADSL"
 
-#' Random Time to Event Analysis Dataset
-#'
-#' @description Random Time to Event Analysis Dataset
+#' Random time to event analysis dataset
 #' @docType data
-#'
 #' @usage rADTTE
-#'
 #' @keywords datasets internal
-#'
 #' @source internal
 #' @name rADTTE
 "rADTTE"
diff --git a/R/teal.modules.general.R b/R/teal.modules.general.R
index a6cad3d13..b35caf9dc 100644
--- a/R/teal.modules.general.R
+++ b/R/teal.modules.general.R
@@ -1,4 +1,4 @@
-#' teal.modules.general: General modules to add to a teal application
+#' `teal.modules.general`: General modules to add to a teal application
 #'
 #' The modules in this package are generic modules that should work with any data set
 #' (not necessarily for clinical trials data).
diff --git a/R/utils.R b/R/utils.R
index ef6702ee6..fd0dbef79 100644
--- a/R/utils.R
+++ b/R/utils.R
@@ -1,29 +1,30 @@
-#' Shared Parameters
+#' Shared parameters documentation
 #'
-#' @description Contains arguments that are shared between multiple functions
-#'   in the package to avoid repetition using `inheritParams`.
+#' Defines common arguments shared across multiple functions in the package
+#' to avoid repetition by using `inheritParams`.
 #'
-#' @param plot_height optional, (`numeric`) A vector of length three with `c(value, min and max)`
-#'   for a slider encoding the plot height.
-#' @param plot_width optional, (`numeric`) A vector of length three with `c(value, min and max)`
-#'   for a slider encoding the plot width.
+#' @param plot_height optional, (`numeric`) Specifies the plot height as a three-element vector of
+#' `value`, `min`, and `max` intended for use with a slider UI element.
+#' @param plot_width optional, (`numeric`) Specifies the plot width as a three-element vector of
+#' `value`, `min`, and `max` for a slider encoding the plot width.
 #' @param rotate_xaxis_labels optional, (`logical`) Whether to rotate plot X axis labels. Does not
-#'   rotate by default (`FALSE`).
+#' rotate by default (`FALSE`).
 #' @param ggtheme optional, (`character`) `ggplot2` theme to be used by default. Defaults to `"gray"`.
 #' @param ggplot2_args (`ggplot2_args`) object created by [teal.widgets::ggplot2_args()]
-#'  with settings for the module plot.
-#'  The argument is merged with options variable `teal.ggplot2_args` and default module setup.
+#' with settings for the module plot.
+#' The argument is merged with options variable `teal.ggplot2_args` and default module setup.
 #'
-#'  For more details see the vignette: `vignette("custom-ggplot2-arguments", package = "teal.widgets")`
+#' For more details see the vignette: `vignette("custom-ggplot2-arguments", package = "teal.widgets")`
 #' @param basic_table_args (`basic_table_args`) object created by [teal.widgets::basic_table_args()]
-#'  with settings for the module table.
-#'  The argument is merged with options variable `teal.basic_table_args` and default module setup.
+#' with settings for the module table.
+#' The argument is merged with options variable `teal.basic_table_args` and default module setup.
 #'
-#'  For more details see the vignette: `vignette("custom-basic-table-arguments", package = "teal.widgets")`
-#' @param pre_output (`shiny.tag`, optional)\cr
+#' For more details see the vignette: `vignette("custom-basic-table-arguments", package = "teal.widgets")`
+#' @param pre_output (`shiny.tag`, optional) Text or UI element to be displayed before the module's output,
+#' providing context or a title.
 #'  with text placed before the output to put the output into context. For example a title.
-#' @param post_output (`shiny.tag`, optional) with text placed after the output to put the output
-#' into context. For example the [shiny::helpText()] elements are useful.
+#' @param post_output (`shiny.tag`, optional) Text or UI element to be displayed after the module's output,
+#' adding context or further instructions. Elements like `shiny::helpText()` are useful.
 #'
 #' @return Object of class `teal_module` to be used in `teal` applications.
 #'
@@ -31,23 +32,20 @@
 #' @keywords internal
 NULL
 
-#' Add axis labels that show facetting variable
+#' Add labels for facets to a ggplot2 object
 #'
-#' Add axis labels that show facetting variable
+#' Enhances a ggplot2 plot by adding labels that describe
+#' the faceting variables along the x and y axes.
 #'
-#' @param p `ggplot2` object to add facet labels to
-#' @param xfacet_label label of facet along x axis (nothing created if NULL),
-#'   if vector, will be concatenated with " & "
-#' @param yfacet_label label of facet along y axis (nothing created if NULL),
-#'   if vector, will be concatenated with " & "
+#' @param p (`ggplot2`) object to which facet labels will be added.
+#' @param xfacet_label (`character`) Label for the facet along the x-axis.
+#' If `NULL`, no label is added. If a vector, labels are joined with " & ".
+#' @param yfacet_label (`character`) Label for the facet along the y-axis.
+#' Similar behavior to `xfacet_label`.
 #'
-#' @return grid grob object (to be drawn with \code{grid.draw})
-#'
-#' @export
+#' @return Returns `grid` or `grob` object (to be drawn with `grid.draw`)
 #'
 #' @examples
-#' # we put donttest to avoid strictr error with seq along.with argument
-#' \donttest{
 #' library(ggplot2)
 #' library(grid)
 #'
@@ -55,7 +53,7 @@ NULL
 #'   aes(x = mpg, y = disp) +
 #'   geom_point() +
 #'   facet_grid(gear ~ cyl)
-#' p
+#'
 #' xfacet_label <- "cylinders"
 #' yfacet_label <- "gear"
 #' res <- add_facet_labels(p, xfacet_label, yfacet_label)
@@ -68,7 +66,8 @@ NULL
 #' grid.draw(add_facet_labels(p, xfacet_label, yfacet_label = NULL))
 #' grid.newpage()
 #' grid.draw(add_facet_labels(p, xfacet_label = NULL, yfacet_label = NULL))
-#' }
+#'
+#' @export
 #'
 add_facet_labels <- function(p, xfacet_label = NULL, yfacet_label = NULL) {
   checkmate::assert_class(p, classes = "ggplot")
@@ -122,46 +121,42 @@ add_facet_labels <- function(p, xfacet_label = NULL, yfacet_label = NULL) {
 
 #' Call a function with a character vector for the \code{...} argument
 #'
-#' @param fun (\code{character}) Name of a function where the \code{...} argument
+#' @param fun (`character`) Name of a function where the \code{...} argument
 #'   shall be replaced by values from \code{str_args}.
-#' @param str_args (\code{character}) A character vector that the function shall
+#' @param str_args (`character`) A character vector that the function shall
 #'  be executed with
 #'
-#' @return: call (i.e. expression) of the function provided by \code{fun}
+#' @return Call (i.e. expression) of the function provided by \code{fun}
 #'  with arguments provided by \code{str_args}.
-#' @keywords internal
 #'
 #' @examples
-#' \dontrun{
+#' call_fun_dots <- getFromNamespace("call_fun_dots", "teal.modules.general")
+#'
 #' a <- 1
 #' b <- 2
 #' call_fun_dots("sum", c("a", "b"))
 #' eval(call_fun_dots("sum", c("a", "b")))
-#' }
+#'
+#' @keywords internal
+#'
 call_fun_dots <- function(fun, str_args) {
   do.call("call", c(list(fun), lapply(str_args, as.name)), quote = TRUE)
 }
 
-#' Get variable name with label
+#' Generate a string for a variable including its label
 #'
-#' @param var_names (\code{character}) Name of variable to extract labels from.
-#' @param dataset (\code{dataset}) Name of analysis dataset.
-#' @param prefix (\code{character}) String to paste to the beginning of the
+#' @param var_names (`character`) Name of variable to extract labels from.
+#' @param dataset (`dataset`) Name of analysis dataset.
+#' @param prefix (`character`) String to paste to the beginning of the
 #'   variable name with label.
-#' @param suffix (\code{character}) String to paste to the end of the variable
+#' @param suffix (`character`) String to paste to the end of the variable
 #'   name with label.
-#' @param wrap_width (\code{numeric}) Number of characters to wrap original
+#' @param wrap_width (`numeric`) Number of characters to wrap original
 #'   label to. Defaults to 80.
 #'
-#' @return (\code{character}) String with variable name and label.
+#' @return (`character`) String with variable name and label.
 #' @keywords internal
 #'
-#' @examples
-#' \dontrun{
-#' ADSL <- teal.modules.general::rADSL
-#'
-#' varname_w_label("AGE", ADSL)
-#' }
 varname_w_label <- function(var_names,
                             dataset,
                             wrap_width = 80,
@@ -205,17 +200,20 @@ shape_names <- c(
 #' Get icons to represent variable types in dataset
 #'
 #' @param var_type (`character`)\cr
-#'  of R internal types (classes).
+#'  of `R` internal types (classes).
 #'
-#' @return (`character`)\cr
-#'  vector of HTML icons corresponding to data type in each column.
-#' @keywords internal
+#' @return Vector of HTML icons corresponding to data type in each column.
 #'
 #' @examples
-#' teal.modules.general:::variable_type_icons(c(
+#' variable_type_icons <- getFromNamespace("variable_type_icons", "teal.modules.general")
+#'
+#' variable_type_icons(c(
 #'   "integer", "numeric", "logical", "Date", "POSIXct", "POSIXlt",
 #'   "factor", "character", "unknown", ""
 #' ))
+#'
+#' @keywords internal
+#'
 variable_type_icons <- function(var_type) {
   checkmate::assert_character(var_type, any.missing = FALSE)
 
@@ -256,10 +254,11 @@ variable_type_icons <- function(var_type) {
 #' not work with `devtools`. Therefore, we redefine this method in each package
 #' as needed. Thus, we do not export this method
 #'
-#' @param pattern (`character`) pattern of files to be included
+#' @param pattern (`character`) optional regular expression to match the file names to be included.
 #'
-#' @return HTML code that includes `CSS` files
+#' @return HTML code that includes `CSS` files.
 #' @keywords internal
+#'
 include_css_files <- function(pattern = "*") {
   css_files <- list.files(
     system.file("css", package = "teal.modules.general", mustWork = TRUE),
@@ -271,12 +270,14 @@ include_css_files <- function(pattern = "*") {
   return(shiny::singleton(shiny::tags$head(lapply(css_files, shiny::includeCSS))))
 }
 
-
-#' Get a string with java-script code checking if the specific tab is clicked
-#' @description will be the input for `shiny::conditionalPanel()`
-#' @param id `character(1)` the id of the tab panel with tabs.
-#' @param name `character(1)` the name of the tab.
+#' JavaScript condition to check if a specific tab is active
+#'
+#' @param id (`character(1)`) the id of the tab panel with tabs.
+#' @param name (`character(1)`) the name of the tab.
+#' @return JavaScript expression to be used in `shiny::conditionalPanel()` to determine
+#' if the specified tab is active.
 #' @keywords internal
+#'
 is_tab_active_js <- function(id, name) {
   # supporting the bs3 and higher version at the same time
   sprintf(
diff --git a/man/add_facet_labels.Rd b/man/add_facet_labels.Rd
index 00dffea1b..02cd828ba 100644
--- a/man/add_facet_labels.Rd
+++ b/man/add_facet_labels.Rd
@@ -2,28 +2,27 @@
 % Please edit documentation in R/utils.R
 \name{add_facet_labels}
 \alias{add_facet_labels}
-\title{Add axis labels that show facetting variable}
+\title{Add labels for facets to a ggplot2 object}
 \usage{
 add_facet_labels(p, xfacet_label = NULL, yfacet_label = NULL)
 }
 \arguments{
-\item{p}{\code{ggplot2} object to add facet labels to}
+\item{p}{(\code{ggplot2}) object to which facet labels will be added.}
 
-\item{xfacet_label}{label of facet along x axis (nothing created if NULL),
-if vector, will be concatenated with " & "}
+\item{xfacet_label}{(\code{character}) Label for the facet along the x-axis.
+If \code{NULL}, no label is added. If a vector, labels are joined with " & ".}
 
-\item{yfacet_label}{label of facet along y axis (nothing created if NULL),
-if vector, will be concatenated with " & "}
+\item{yfacet_label}{(\code{character}) Label for the facet along the y-axis.
+Similar behavior to \code{xfacet_label}.}
 }
 \value{
-grid grob object (to be drawn with \code{grid.draw})
+Returns \code{grid} or \code{grob} object (to be drawn with \code{grid.draw})
 }
 \description{
-Add axis labels that show facetting variable
+Enhances a ggplot2 plot by adding labels that describe
+the faceting variables along the x and y axes.
 }
 \examples{
-# we put donttest to avoid strictr error with seq along.with argument
-\donttest{
 library(ggplot2)
 library(grid)
 
@@ -31,7 +30,7 @@ p <- ggplot(mtcars) +
   aes(x = mpg, y = disp) +
   geom_point() +
   facet_grid(gear ~ cyl)
-p
+
 xfacet_label <- "cylinders"
 yfacet_label <- "gear"
 res <- add_facet_labels(p, xfacet_label, yfacet_label)
@@ -44,6 +43,5 @@ grid.newpage()
 grid.draw(add_facet_labels(p, xfacet_label, yfacet_label = NULL))
 grid.newpage()
 grid.draw(add_facet_labels(p, xfacet_label = NULL, yfacet_label = NULL))
-}
 
 }
diff --git a/man/call_fun_dots.Rd b/man/call_fun_dots.Rd
index 001a654b2..249ed5438 100644
--- a/man/call_fun_dots.Rd
+++ b/man/call_fun_dots.Rd
@@ -14,18 +14,19 @@ shall be replaced by values from \code{str_args}.}
 be executed with}
 }
 \value{
-: call (i.e. expression) of the function provided by \code{fun}
+Call (i.e. expression) of the function provided by \code{fun}
 with arguments provided by \code{str_args}.
 }
 \description{
 Call a function with a character vector for the \code{...} argument
 }
 \examples{
-\dontrun{
+call_fun_dots <- getFromNamespace("call_fun_dots", "teal.modules.general")
+
 a <- 1
 b <- 2
 call_fun_dots("sum", c("a", "b"))
 eval(call_fun_dots("sum", c("a", "b")))
-}
+
 }
 \keyword{internal}
diff --git a/man/include_css_files.Rd b/man/include_css_files.Rd
index dad825f75..44c46e76d 100644
--- a/man/include_css_files.Rd
+++ b/man/include_css_files.Rd
@@ -7,10 +7,10 @@
 include_css_files(pattern = "*")
 }
 \arguments{
-\item{pattern}{(\code{character}) pattern of files to be included}
+\item{pattern}{(\code{character}) optional regular expression to match the file names to be included.}
 }
 \value{
-HTML code that includes \code{CSS} files
+HTML code that includes \code{CSS} files.
 }
 \description{
 \code{system.file} should not be used to access files in other packages, it does
diff --git a/man/is_tab_active_js.Rd b/man/is_tab_active_js.Rd
index 05b67aa04..1d8031073 100644
--- a/man/is_tab_active_js.Rd
+++ b/man/is_tab_active_js.Rd
@@ -2,16 +2,20 @@
 % Please edit documentation in R/utils.R
 \name{is_tab_active_js}
 \alias{is_tab_active_js}
-\title{Get a string with java-script code checking if the specific tab is clicked}
+\title{JavaScript condition to check if a specific tab is active}
 \usage{
 is_tab_active_js(id, name)
 }
 \arguments{
-\item{id}{\code{character(1)} the id of the tab panel with tabs.}
+\item{id}{(\code{character(1)}) the id of the tab panel with tabs.}
 
-\item{name}{\code{character(1)} the name of the tab.}
+\item{name}{(\code{character(1)}) the name of the tab.}
+}
+\value{
+JavaScript expression to be used in \code{shiny::conditionalPanel()} to determine
+if the specified tab is active.
 }
 \description{
-will be the input for \code{shiny::conditionalPanel()}
+JavaScript condition to check if a specific tab is active
 }
 \keyword{internal}
diff --git a/man/rADTTE.Rd b/man/rADTTE.Rd
index 56d859833..185d391d9 100644
--- a/man/rADTTE.Rd
+++ b/man/rADTTE.Rd
@@ -3,7 +3,7 @@
 \docType{data}
 \name{rADTTE}
 \alias{rADTTE}
-\title{Random Time to Event Analysis Dataset}
+\title{Random time to event analysis dataset}
 \format{
 An object of class \code{tbl_df} (inherits from \code{tbl}, \code{data.frame}) with 2000 rows and 67 columns.
 }
@@ -14,7 +14,7 @@ internal
 rADTTE
 }
 \description{
-Random Time to Event Analysis Dataset
+Random time to event analysis dataset
 }
 \keyword{datasets}
 \keyword{internal}
diff --git a/man/shared_params.Rd b/man/shared_params.Rd
index 1d130bd66..22c4ee66a 100644
--- a/man/shared_params.Rd
+++ b/man/shared_params.Rd
@@ -2,13 +2,13 @@
 % Please edit documentation in R/utils.R
 \name{shared_params}
 \alias{shared_params}
-\title{Shared Parameters}
+\title{Shared parameters documentation}
 \arguments{
-\item{plot_height}{optional, (\code{numeric}) A vector of length three with \verb{c(value, min and max)}
-for a slider encoding the plot height.}
+\item{plot_height}{optional, (\code{numeric}) Specifies the plot height as a three-element vector of
+\code{value}, \code{min}, and \code{max} intended for use with a slider UI element.}
 
-\item{plot_width}{optional, (\code{numeric}) A vector of length three with \verb{c(value, min and max)}
-for a slider encoding the plot width.}
+\item{plot_width}{optional, (\code{numeric}) Specifies the plot width as a three-element vector of
+\code{value}, \code{min}, and \code{max} for a slider encoding the plot width.}
 
 \item{rotate_xaxis_labels}{optional, (\code{logical}) Whether to rotate plot X axis labels. Does not
 rotate by default (\code{FALSE}).}
@@ -27,17 +27,18 @@ The argument is merged with options variable \code{teal.basic_table_args} and de
 
 For more details see the vignette: \code{vignette("custom-basic-table-arguments", package = "teal.widgets")}}
 
-\item{pre_output}{(\code{shiny.tag}, optional)\cr
+\item{pre_output}{(\code{shiny.tag}, optional) Text or UI element to be displayed before the module's output,
+providing context or a title.
 with text placed before the output to put the output into context. For example a title.}
 
-\item{post_output}{(\code{shiny.tag}, optional) with text placed after the output to put the output
-into context. For example the \code{\link[shiny:helpText]{shiny::helpText()}} elements are useful.}
+\item{post_output}{(\code{shiny.tag}, optional) Text or UI element to be displayed after the module's output,
+adding context or further instructions. Elements like \code{shiny::helpText()} are useful.}
 }
 \value{
 Object of class \code{teal_module} to be used in \code{teal} applications.
 }
 \description{
-Contains arguments that are shared between multiple functions
-in the package to avoid repetition using \code{inheritParams}.
+Defines common arguments shared across multiple functions in the package
+to avoid repetition by using \code{inheritParams}.
 }
 \keyword{internal}
diff --git a/man/teal.modules.general.Rd b/man/teal.modules.general.Rd
index 4a9330dab..6c36e3436 100644
--- a/man/teal.modules.general.Rd
+++ b/man/teal.modules.general.Rd
@@ -4,7 +4,7 @@
 \name{teal.modules.general}
 \alias{teal.modules.general-package}
 \alias{teal.modules.general}
-\title{teal.modules.general: General modules to add to a teal application}
+\title{\code{teal.modules.general}: General modules to add to a teal application}
 \description{
 The modules in this package are generic modules that should work with any data set
 (not necessarily for clinical trials data).
diff --git a/man/tm_a_pca.Rd b/man/tm_a_pca.Rd
index b72a00134..fd9a063e7 100644
--- a/man/tm_a_pca.Rd
+++ b/man/tm_a_pca.Rd
@@ -26,11 +26,11 @@ For \code{modules()} defaults to \code{"root"}. See \code{Details}.}
 \item{dat}{(\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec})
 specifying columns used to compute PCA.}
 
-\item{plot_height}{optional, (\code{numeric}) A vector of length three with \verb{c(value, min and max)}
-for a slider encoding the plot height.}
+\item{plot_height}{optional, (\code{numeric}) Specifies the plot height as a three-element vector of
+\code{value}, \code{min}, and \code{max} intended for use with a slider UI element.}
 
-\item{plot_width}{optional, (\code{numeric}) A vector of length three with \verb{c(value, min and max)}
-for a slider encoding the plot width.}
+\item{plot_width}{optional, (\code{numeric}) Specifies the plot width as a three-element vector of
+\code{value}, \code{min}, and \code{max} for a slider encoding the plot width.}
 
 \item{ggtheme}{optional, (\code{character}) \code{ggplot2} theme to be used by default. Defaults to \code{"gray"}.}
 
@@ -64,11 +64,12 @@ It controls the font size for plot titles, axis labels, and legends.
 \item while vector of \code{value}, \code{min}, and \code{max} allows dynamic adjustment.
 }}
 
-\item{pre_output}{(\code{shiny.tag}, optional)\cr
+\item{pre_output}{(\code{shiny.tag}, optional) Text or UI element to be displayed before the module's output,
+providing context or a title.
 with text placed before the output to put the output into context. For example a title.}
 
-\item{post_output}{(\code{shiny.tag}, optional) with text placed after the output to put the output
-into context. For example the \code{\link[shiny:helpText]{shiny::helpText()}} elements are useful.}
+\item{post_output}{(\code{shiny.tag}, optional) Text or UI element to be displayed after the module's output,
+adding context or further instructions. Elements like \code{shiny::helpText()} are useful.}
 }
 \description{
 Module conducts principal component analysis (PCA) on a given dataset and offers different
diff --git a/man/tm_a_regression.Rd b/man/tm_a_regression.Rd
index 053246eea..100cdaeab 100644
--- a/man/tm_a_regression.Rd
+++ b/man/tm_a_regression.Rd
@@ -30,11 +30,11 @@ Regressor variables from an incoming dataset with filtering and selecting.}
 \item{response}{(\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec})
 Response variables from an incoming dataset with filtering and selecting.}
 
-\item{plot_height}{optional, (\code{numeric}) A vector of length three with \verb{c(value, min and max)}
-for a slider encoding the plot height.}
+\item{plot_height}{optional, (\code{numeric}) Specifies the plot height as a three-element vector of
+\code{value}, \code{min}, and \code{max} intended for use with a slider UI element.}
 
-\item{plot_width}{optional, (\code{numeric}) A vector of length three with \verb{c(value, min and max)}
-for a slider encoding the plot width.}
+\item{plot_width}{optional, (\code{numeric}) Specifies the plot width as a three-element vector of
+\code{value}, \code{min}, and \code{max} for a slider encoding the plot width.}
 
 \item{alpha}{optional, (\code{numeric}) If scalar then the plot points will have a fixed opacity. If a
 slider should be presented to adjust the plot point opacity dynamically then it can be a vector of
@@ -54,11 +54,12 @@ List names should match the following: \verb{c("default", "Response vs Regressor
 
 For more details see the vignette: \code{vignette("custom-ggplot2-arguments", package = "teal.widgets")}.}
 
-\item{pre_output}{(\code{shiny.tag}, optional)\cr
+\item{pre_output}{(\code{shiny.tag}, optional) Text or UI element to be displayed before the module's output,
+providing context or a title.
 with text placed before the output to put the output into context. For example a title.}
 
-\item{post_output}{(\code{shiny.tag}, optional) with text placed after the output to put the output
-into context. For example the \code{\link[shiny:helpText]{shiny::helpText()}} elements are useful.}
+\item{post_output}{(\code{shiny.tag}, optional) Text or UI element to be displayed after the module's output,
+adding context or further instructions. Elements like \code{shiny::helpText()} are useful.}
 
 \item{default_plot_type}{optional, (\code{numeric}) Defaults to Response vs Regressor.
 \enumerate{
diff --git a/man/tm_data_table.Rd b/man/tm_data_table.Rd
index 3b4136be5..40bf5e54b 100644
--- a/man/tm_data_table.Rd
+++ b/man/tm_data_table.Rd
@@ -40,11 +40,12 @@ Note: Only datasets of the \code{data.frame} class are compatible.}
 \item{server_rendering}{(\code{logical}) should the data table be rendered server side
 (see \code{server} argument of \code{\link[DT:dataTableOutput]{DT::renderDataTable()}})}
 
-\item{pre_output}{(\code{shiny.tag}, optional)\cr
+\item{pre_output}{(\code{shiny.tag}, optional) Text or UI element to be displayed before the module's output,
+providing context or a title.
 with text placed before the output to put the output into context. For example a title.}
 
-\item{post_output}{(\code{shiny.tag}, optional) with text placed after the output to put the output
-into context. For example the \code{\link[shiny:helpText]{shiny::helpText()}} elements are useful.}
+\item{post_output}{(\code{shiny.tag}, optional) Text or UI element to be displayed after the module's output,
+adding context or further instructions. Elements like \code{shiny::helpText()} are useful.}
 }
 \description{
 Module provides a dynamic and interactive way to view \code{data.frame}s in a \code{teal} application.
diff --git a/man/tm_g_association.Rd b/man/tm_g_association.Rd
index 1bfeb9c64..dc45e7014 100644
--- a/man/tm_g_association.Rd
+++ b/man/tm_g_association.Rd
@@ -33,20 +33,21 @@ associated variables.}
 \item{show_association}{optional, (\code{logical}) Whether show association of \code{vars}
 with reference variable. Defaults to \code{TRUE}.}
 
-\item{plot_height}{optional, (\code{numeric}) A vector of length three with \verb{c(value, min and max)}
-for a slider encoding the plot height.}
+\item{plot_height}{optional, (\code{numeric}) Specifies the plot height as a three-element vector of
+\code{value}, \code{min}, and \code{max} intended for use with a slider UI element.}
 
-\item{plot_width}{optional, (\code{numeric}) A vector of length three with \verb{c(value, min and max)}
-for a slider encoding the plot width.}
+\item{plot_width}{optional, (\code{numeric}) Specifies the plot width as a three-element vector of
+\code{value}, \code{min}, and \code{max} for a slider encoding the plot width.}
 
 \item{distribution_theme, association_theme}{optional, (\code{character}) \code{ggplot2} themes to be used by default.
 Default to \code{"gray"}.}
 
-\item{pre_output}{(\code{shiny.tag}, optional)\cr
+\item{pre_output}{(\code{shiny.tag}, optional) Text or UI element to be displayed before the module's output,
+providing context or a title.
 with text placed before the output to put the output into context. For example a title.}
 
-\item{post_output}{(\code{shiny.tag}, optional) with text placed after the output to put the output
-into context. For example the \code{\link[shiny:helpText]{shiny::helpText()}} elements are useful.}
+\item{post_output}{(\code{shiny.tag}, optional) Text or UI element to be displayed after the module's output,
+adding context or further instructions. Elements like \code{shiny::helpText()} are useful.}
 
 \item{ggplot2_args}{optional, (\code{ggplot2_args}) object created by \code{\link[teal.widgets:ggplot2_args]{teal.widgets::ggplot2_args()}}
 with settings for all the plots or named list of \code{ggplot2_args} objects for plot-specific settings.
diff --git a/man/tm_g_bivariate.Rd b/man/tm_g_bivariate.Rd
index c97ee92bb..6993e682b 100644
--- a/man/tm_g_bivariate.Rd
+++ b/man/tm_g_bivariate.Rd
@@ -75,11 +75,11 @@ Does not allow scaling to be changed by default (\code{FALSE}).}
 \item{free_y_scales}{(\code{logical}, optional) Whether Y scaling shall be changeable.
 Does not allow scaling to be changed by default (\code{FALSE}).}
 
-\item{plot_height}{optional, (\code{numeric}) A vector of length three with \verb{c(value, min and max)}
-for a slider encoding the plot height.}
+\item{plot_height}{optional, (\code{numeric}) Specifies the plot height as a three-element vector of
+\code{value}, \code{min}, and \code{max} intended for use with a slider UI element.}
 
-\item{plot_width}{optional, (\code{numeric}) A vector of length three with \verb{c(value, min and max)}
-for a slider encoding the plot width.}
+\item{plot_width}{optional, (\code{numeric}) Specifies the plot width as a three-element vector of
+\code{value}, \code{min}, and \code{max} for a slider encoding the plot width.}
 
 \item{rotate_xaxis_labels}{optional, (\code{logical}) Whether to rotate plot X axis labels. Does not
 rotate by default (\code{FALSE}).}
@@ -94,11 +94,12 @@ The argument is merged with options variable \code{teal.ggplot2_args} and defaul
 
 For more details see the vignette: \code{vignette("custom-ggplot2-arguments", package = "teal.widgets")}}
 
-\item{pre_output}{(\code{shiny.tag}, optional)\cr
+\item{pre_output}{(\code{shiny.tag}, optional) Text or UI element to be displayed before the module's output,
+providing context or a title.
 with text placed before the output to put the output into context. For example a title.}
 
-\item{post_output}{(\code{shiny.tag}, optional) with text placed after the output to put the output
-into context. For example the \code{\link[shiny:helpText]{shiny::helpText()}} elements are useful.}
+\item{post_output}{(\code{shiny.tag}, optional) Text or UI element to be displayed after the module's output,
+adding context or further instructions. Elements like \code{shiny::helpText()} are useful.}
 }
 \description{
 Module enables the creation of univariate and bivariate plots,
diff --git a/man/tm_g_distribution.Rd b/man/tm_g_distribution.Rd
index a359f7333..a28ed628a 100644
--- a/man/tm_g_distribution.Rd
+++ b/man/tm_g_distribution.Rd
@@ -50,11 +50,11 @@ If a slider should be presented to adjust the number of histogram bins dynamical
 vector of length three with \code{c(value, min, max)}.
 Defaults to \code{c(30L, 1L, 100L)}.}
 
-\item{plot_height}{optional, (\code{numeric}) A vector of length three with \verb{c(value, min and max)}
-for a slider encoding the plot height.}
+\item{plot_height}{optional, (\code{numeric}) Specifies the plot height as a three-element vector of
+\code{value}, \code{min}, and \code{max} intended for use with a slider UI element.}
 
-\item{plot_width}{optional, (\code{numeric}) A vector of length three with \verb{c(value, min and max)}
-for a slider encoding the plot width.}
+\item{plot_width}{optional, (\code{numeric}) Specifies the plot width as a three-element vector of
+\code{value}, \code{min}, and \code{max} for a slider encoding the plot width.}
 
 \item{pre_output}{(\code{shiny.tag}, optional)\cr
 with text placed before the output to put the output into context. For example a title.}
diff --git a/man/tm_g_response.Rd b/man/tm_g_response.Rd
index 74c6b40ac..51c737d52 100644
--- a/man/tm_g_response.Rd
+++ b/man/tm_g_response.Rd
@@ -60,11 +60,11 @@ rotate by default (\code{FALSE}).}
 Indicates whether to display frequency (\code{TRUE}) or density (\code{FALSE}).
 Defaults to density (\code{FALSE}).}
 
-\item{plot_height}{optional, (\code{numeric}) A vector of length three with \verb{c(value, min and max)}
-for a slider encoding the plot height.}
+\item{plot_height}{optional, (\code{numeric}) Specifies the plot height as a three-element vector of
+\code{value}, \code{min}, and \code{max} intended for use with a slider UI element.}
 
-\item{plot_width}{optional, (\code{numeric}) A vector of length three with \verb{c(value, min and max)}
-for a slider encoding the plot width.}
+\item{plot_width}{optional, (\code{numeric}) Specifies the plot width as a three-element vector of
+\code{value}, \code{min}, and \code{max} for a slider encoding the plot width.}
 
 \item{ggtheme}{optional, (\code{character}) \code{ggplot2} theme to be used by default. Defaults to \code{"gray"}.}
 
@@ -74,11 +74,12 @@ The argument is merged with options variable \code{teal.ggplot2_args} and defaul
 
 For more details see the vignette: \code{vignette("custom-ggplot2-arguments", package = "teal.widgets")}}
 
-\item{pre_output}{(\code{shiny.tag}, optional)\cr
+\item{pre_output}{(\code{shiny.tag}, optional) Text or UI element to be displayed before the module's output,
+providing context or a title.
 with text placed before the output to put the output into context. For example a title.}
 
-\item{post_output}{(\code{shiny.tag}, optional) with text placed after the output to put the output
-into context. For example the \code{\link[shiny:helpText]{shiny::helpText()}} elements are useful.}
+\item{post_output}{(\code{shiny.tag}, optional) Text or UI element to be displayed after the module's output,
+adding context or further instructions. Elements like \code{shiny::helpText()} are useful.}
 }
 \value{
 Object of class \code{teal_module} to be used in \code{teal} applications.
diff --git a/man/tm_g_scatterplot.Rd b/man/tm_g_scatterplot.Rd
index c6f80e12f..3dc11cac4 100644
--- a/man/tm_g_scatterplot.Rd
+++ b/man/tm_g_scatterplot.Rd
@@ -48,11 +48,11 @@ Specifies the variable(s) for faceting rows.}
 \item{col_facet}{(\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec}, optional)
 Specifies the variable(s) for faceting columns.}
 
-\item{plot_height}{optional, (\code{numeric}) A vector of length three with \verb{c(value, min and max)}
-for a slider encoding the plot height.}
+\item{plot_height}{optional, (\code{numeric}) Specifies the plot height as a three-element vector of
+\code{value}, \code{min}, and \code{max} intended for use with a slider UI element.}
 
-\item{plot_width}{optional, (\code{numeric}) A vector of length three with \verb{c(value, min and max)}
-for a slider encoding the plot width.}
+\item{plot_width}{optional, (\code{numeric}) Specifies the plot width as a three-element vector of
+\code{value}, \code{min}, and \code{max} for a slider encoding the plot width.}
 
 \item{alpha}{(\code{numeric}, optional) Specifies point opacity.
 \itemize{
@@ -77,11 +77,12 @@ rotate by default (\code{FALSE}).}
 
 \item{ggtheme}{optional, (\code{character}) \code{ggplot2} theme to be used by default. Defaults to \code{"gray"}.}
 
-\item{pre_output}{(\code{shiny.tag}, optional)\cr
+\item{pre_output}{(\code{shiny.tag}, optional) Text or UI element to be displayed before the module's output,
+providing context or a title.
 with text placed before the output to put the output into context. For example a title.}
 
-\item{post_output}{(\code{shiny.tag}, optional) with text placed after the output to put the output
-into context. For example the \code{\link[shiny:helpText]{shiny::helpText()}} elements are useful.}
+\item{post_output}{(\code{shiny.tag}, optional) Text or UI element to be displayed after the module's output,
+adding context or further instructions. Elements like \code{shiny::helpText()} are useful.}
 
 \item{table_dec}{(\code{integer}, optional) Number of decimal places used to round numeric values in the table.}
 
diff --git a/man/tm_g_scatterplotmatrix.Rd b/man/tm_g_scatterplotmatrix.Rd
index 071175f9d..120a32476 100644
--- a/man/tm_g_scatterplotmatrix.Rd
+++ b/man/tm_g_scatterplotmatrix.Rd
@@ -22,17 +22,18 @@ Plotting variables from an incoming dataset with filtering and selecting. In cas
 \code{data_extract_spec} use \code{select_spec(..., ordered = TRUE)} if plot elements should be
 rendered according to selection order.}
 
-\item{plot_height}{optional, (\code{numeric}) A vector of length three with \verb{c(value, min and max)}
-for a slider encoding the plot height.}
+\item{plot_height}{optional, (\code{numeric}) Specifies the plot height as a three-element vector of
+\code{value}, \code{min}, and \code{max} intended for use with a slider UI element.}
 
-\item{plot_width}{optional, (\code{numeric}) A vector of length three with \verb{c(value, min and max)}
-for a slider encoding the plot width.}
+\item{plot_width}{optional, (\code{numeric}) Specifies the plot width as a three-element vector of
+\code{value}, \code{min}, and \code{max} for a slider encoding the plot width.}
 
-\item{pre_output}{(\code{shiny.tag}, optional)\cr
+\item{pre_output}{(\code{shiny.tag}, optional) Text or UI element to be displayed before the module's output,
+providing context or a title.
 with text placed before the output to put the output into context. For example a title.}
 
-\item{post_output}{(\code{shiny.tag}, optional) with text placed after the output to put the output
-into context. For example the \code{\link[shiny:helpText]{shiny::helpText()}} elements are useful.}
+\item{post_output}{(\code{shiny.tag}, optional) Text or UI element to be displayed after the module's output,
+adding context or further instructions. Elements like \code{shiny::helpText()} are useful.}
 }
 \description{
 The available datasets to choose from for each dataset selector is the same and
diff --git a/man/tm_missing_data.Rd b/man/tm_missing_data.Rd
index 08c9090f9..87b513723 100644
--- a/man/tm_missing_data.Rd
+++ b/man/tm_missing_data.Rd
@@ -21,11 +21,11 @@ tm_missing_data(
 \item{label}{(\code{character(1)}) Label shown in the navigation item for the module or module group.
 For \code{modules()} defaults to \code{"root"}. See \code{Details}.}
 
-\item{plot_height}{optional, (\code{numeric}) A vector of length three with \verb{c(value, min and max)}
-for a slider encoding the plot height.}
+\item{plot_height}{optional, (\code{numeric}) Specifies the plot height as a three-element vector of
+\code{value}, \code{min}, and \code{max} intended for use with a slider UI element.}
 
-\item{plot_width}{optional, (\code{numeric}) A vector of length three with \verb{c(value, min and max)}
-for a slider encoding the plot width.}
+\item{plot_width}{optional, (\code{numeric}) Specifies the plot width as a three-element vector of
+\code{value}, \code{min}, and \code{max} for a slider encoding the plot width.}
 
 \item{parent_dataname}{(\code{character(1)}) If this \code{dataname} exists in then "the by subject"graph is displayed.
 For \code{CDISC} data. In non \code{CDISC} data this can be ignored. Defaults to \code{"ADSL"}.}
@@ -40,11 +40,12 @@ List names should match the following: \code{c("default", "Summary Obs", "Summar
 
 For more details see the vignette: \code{vignette("custom-ggplot2-arguments", package = "teal.widgets")}.}
 
-\item{pre_output}{(\code{shiny.tag}, optional)\cr
+\item{pre_output}{(\code{shiny.tag}, optional) Text or UI element to be displayed before the module's output,
+providing context or a title.
 with text placed before the output to put the output into context. For example a title.}
 
-\item{post_output}{(\code{shiny.tag}, optional) with text placed after the output to put the output
-into context. For example the \code{\link[shiny:helpText]{shiny::helpText()}} elements are useful.}
+\item{post_output}{(\code{shiny.tag}, optional) Text or UI element to be displayed after the module's output,
+adding context or further instructions. Elements like \code{shiny::helpText()} are useful.}
 }
 \description{
 Present analysis of missing observations and patients.
diff --git a/man/tm_outliers.Rd b/man/tm_outliers.Rd
index b0898aa19..9bda163f3 100644
--- a/man/tm_outliers.Rd
+++ b/man/tm_outliers.Rd
@@ -36,17 +36,18 @@ List names should match the following: \code{c("default", "Boxplot","Density Plo
 
 For more details see the vignette: \code{vignette("custom-ggplot2-arguments", package = "teal.widgets")}.}
 
-\item{plot_height}{optional, (\code{numeric}) A vector of length three with \verb{c(value, min and max)}
-for a slider encoding the plot height.}
+\item{plot_height}{optional, (\code{numeric}) Specifies the plot height as a three-element vector of
+\code{value}, \code{min}, and \code{max} intended for use with a slider UI element.}
 
-\item{plot_width}{optional, (\code{numeric}) A vector of length three with \verb{c(value, min and max)}
-for a slider encoding the plot width.}
+\item{plot_width}{optional, (\code{numeric}) Specifies the plot width as a three-element vector of
+\code{value}, \code{min}, and \code{max} for a slider encoding the plot width.}
 
-\item{pre_output}{(\code{shiny.tag}, optional)\cr
+\item{pre_output}{(\code{shiny.tag}, optional) Text or UI element to be displayed before the module's output,
+providing context or a title.
 with text placed before the output to put the output into context. For example a title.}
 
-\item{post_output}{(\code{shiny.tag}, optional) with text placed after the output to put the output
-into context. For example the \code{\link[shiny:helpText]{shiny::helpText()}} elements are useful.}
+\item{post_output}{(\code{shiny.tag}, optional) Text or UI element to be displayed after the module's output,
+adding context or further instructions. Elements like \code{shiny::helpText()} are useful.}
 }
 \description{
 Module to analyze and identify outliers using different methods
diff --git a/man/tm_t_crosstable.Rd b/man/tm_t_crosstable.Rd
index 6965390ea..dcbc021a9 100644
--- a/man/tm_t_crosstable.Rd
+++ b/man/tm_t_crosstable.Rd
@@ -37,11 +37,12 @@ Defaults to \code{TRUE}.}
 Indicates whether to show total column.
 Defaults to \code{TRUE}.}
 
-\item{pre_output}{(\code{shiny.tag}, optional)\cr
+\item{pre_output}{(\code{shiny.tag}, optional) Text or UI element to be displayed before the module's output,
+providing context or a title.
 with text placed before the output to put the output into context. For example a title.}
 
-\item{post_output}{(\code{shiny.tag}, optional) with text placed after the output to put the output
-into context. For example the \code{\link[shiny:helpText]{shiny::helpText()}} elements are useful.}
+\item{post_output}{(\code{shiny.tag}, optional) Text or UI element to be displayed after the module's output,
+adding context or further instructions. Elements like \code{shiny::helpText()} are useful.}
 
 \item{basic_table_args}{(\code{basic_table_args}) object created by \code{\link[teal.widgets:basic_table_args]{teal.widgets::basic_table_args()}}
 with settings for the module table.
diff --git a/man/tm_variable_browser.Rd b/man/tm_variable_browser.Rd
index 9ea518a85..c5b6d81a7 100644
--- a/man/tm_variable_browser.Rd
+++ b/man/tm_variable_browser.Rd
@@ -28,11 +28,12 @@ allow users to not show variables in other datasets which exist in this \code{da
 This is typically used to remove \code{ADSL} columns in \code{CDISC} data.
 In non \code{CDISC} data this can be ignored. Defaults to \code{"ADSL"}.}
 
-\item{pre_output}{(\code{shiny.tag}, optional)\cr
+\item{pre_output}{(\code{shiny.tag}, optional) Text or UI element to be displayed before the module's output,
+providing context or a title.
 with text placed before the output to put the output into context. For example a title.}
 
-\item{post_output}{(\code{shiny.tag}, optional) with text placed after the output to put the output
-into context. For example the \code{\link[shiny:helpText]{shiny::helpText()}} elements are useful.}
+\item{post_output}{(\code{shiny.tag}, optional) Text or UI element to be displayed after the module's output,
+adding context or further instructions. Elements like \code{shiny::helpText()} are useful.}
 
 \item{ggplot2_args}{(\code{ggplot2_args}) object created by \code{\link[teal.widgets:ggplot2_args]{teal.widgets::ggplot2_args()}}
 with settings for the module plot.
diff --git a/man/variable_type_icons.Rd b/man/variable_type_icons.Rd
index 1b7150e9d..9d564369b 100644
--- a/man/variable_type_icons.Rd
+++ b/man/variable_type_icons.Rd
@@ -8,19 +8,21 @@ variable_type_icons(var_type)
 }
 \arguments{
 \item{var_type}{(\code{character})\cr
-of R internal types (classes).}
+of \code{R} internal types (classes).}
 }
 \value{
-(\code{character})\cr
-vector of HTML icons corresponding to data type in each column.
+Vector of HTML icons corresponding to data type in each column.
 }
 \description{
 Get icons to represent variable types in dataset
 }
 \examples{
-teal.modules.general:::variable_type_icons(c(
+variable_type_icons <- getFromNamespace("variable_type_icons", "teal.modules.general")
+
+variable_type_icons(c(
   "integer", "numeric", "logical", "Date", "POSIXct", "POSIXlt",
   "factor", "character", "unknown", ""
 ))
+
 }
 \keyword{internal}
diff --git a/man/varname_w_label.Rd b/man/varname_w_label.Rd
index 6e241bf42..f752406d7 100644
--- a/man/varname_w_label.Rd
+++ b/man/varname_w_label.Rd
@@ -2,7 +2,7 @@
 % Please edit documentation in R/utils.R
 \name{varname_w_label}
 \alias{varname_w_label}
-\title{Get variable name with label}
+\title{Generate a string for a variable including its label}
 \usage{
 varname_w_label(
   var_names,
@@ -30,13 +30,6 @@ name with label.}
 (\code{character}) String with variable name and label.
 }
 \description{
-Get variable name with label
-}
-\examples{
-\dontrun{
-ADSL <- teal.modules.general::rADSL
-
-varname_w_label("AGE", ADSL)
-}
+Generate a string for a variable including its label
 }
 \keyword{internal}

From 4a34ee80309fad46c865663de1e6aed4a47c6e81 Mon Sep 17 00:00:00 2001
From: kartikeya kirar <kirar.kartikeya1@gmail.com>
Date: Mon, 26 Feb 2024 19:50:42 +0530
Subject: [PATCH 30/62] pre-release `tm_missing_data` document update (#668)

part of
https://github.com/insightsengineering/teal.modules.general/issues/624

---------

Co-authored-by: go_gonzo <dawid.kaledkowski@gmail.com>
---
 R/tm_missing_data.R    | 21 ++++++++++++++-------
 man/tm_missing_data.Rd | 14 ++++++++------
 2 files changed, 22 insertions(+), 13 deletions(-)

diff --git a/R/tm_missing_data.R b/R/tm_missing_data.R
index 4e856dffd..48f9f9941 100644
--- a/R/tm_missing_data.R
+++ b/R/tm_missing_data.R
@@ -1,13 +1,15 @@
-#' Missing data module
+#' Missing data analysis module
 #'
-#' Present analysis of missing observations and patients.
-#' specifically designed for use with `data.frames`.
+#' Module analyzes missing data in `data.frame`s to help users explore missing observations and
+#' gain insights into the completeness of their data.
+#' It is useful for clinical data analysis within the context of CDISC standards and
+#' adaptable for general data analysis purposes.
 #'
 #' @inheritParams teal::module
 #' @inheritParams shared_params
-#' @param parent_dataname (`character(1)`) If this `dataname` exists in then "the by subject"graph is displayed.
-#'   For `CDISC` data. In non `CDISC` data this can be ignored. Defaults to `"ADSL"`.
-#' @param ggtheme optional, (`character`) `ggplot2` theme to be used by default. Defaults to `"classic"`.
+#' @param parent_dataname (`character(1)`) Specifies the parent dataset name. Default is `ADSL` for CDISC data.
+#' If provided and exists, enables additional analysis "by subject". For non-CDISC data, this parameter can be ignored.
+#' @param ggtheme (`character`, optional) Specifies the default `ggplot2` theme for plots. Defaults to `classic`.
 #'
 #' @templateVar ggnames "Summary Obs", "Summary Patients", "Combinations Main", "Combinations Hist", "By Subject"
 #' @template ggplot2_args_multi
@@ -120,6 +122,7 @@ tm_missing_data <- function(label = "Missing data",
   )
 }
 
+# UI function for the missing data module (all datasets)
 ui_page_missing_data <- function(id, pre_output = NULL, post_output = NULL) {
   ns <- NS(id)
   shiny::tagList(
@@ -144,6 +147,7 @@ ui_page_missing_data <- function(id, pre_output = NULL, post_output = NULL) {
   )
 }
 
+# Server function for the missing data module (all datasets)
 srv_page_missing_data <- function(id, data, reporter, filter_panel_api, parent_dataname,
                                   plot_height, plot_width, ggplot2_args, ggtheme) {
   moduleServer(id, function(input, output, session) {
@@ -230,6 +234,7 @@ srv_page_missing_data <- function(id, data, reporter, filter_panel_api, parent_d
   })
 }
 
+# UI function for the missing data module (single dataset)
 ui_missing_data <- function(id, by_subject_plot = FALSE) {
   ns <- NS(id)
 
@@ -299,6 +304,7 @@ ui_missing_data <- function(id, by_subject_plot = FALSE) {
   )
 }
 
+# UI encoding for the missing data module (all datasets)
 encoding_missing_data <- function(id, summary_per_patient = FALSE, ggtheme, datanames) {
   ns <- NS(id)
 
@@ -387,6 +393,7 @@ encoding_missing_data <- function(id, summary_per_patient = FALSE, ggtheme, data
   )
 }
 
+# Server function for the missing data (single dataset)
 srv_missing_data <- function(id, data, reporter, filter_panel_api, dataname, parent_dataname,
                              plot_height, plot_width, ggplot2_args) {
   with_reporter <- !missing(reporter) && inherits(reporter, "Reporter")
@@ -491,7 +498,7 @@ srv_missing_data <- function(id, data, reporter, filter_panel_api, dataname, par
               } else {
                 labels <- ifelse(cols == new_col_name | cols == "", cols, paste0(column_labels[cols], " [", cols, "]"))
               }
-              return(labels)
+              labels
             },
           env = list(
             new_col_name = new_col_name,
diff --git a/man/tm_missing_data.Rd b/man/tm_missing_data.Rd
index 87b513723..6ca59c853 100644
--- a/man/tm_missing_data.Rd
+++ b/man/tm_missing_data.Rd
@@ -2,7 +2,7 @@
 % Please edit documentation in R/tm_missing_data.R
 \name{tm_missing_data}
 \alias{tm_missing_data}
-\title{Missing data module}
+\title{Missing data analysis module}
 \usage{
 tm_missing_data(
   label = "Missing data",
@@ -27,10 +27,10 @@ For \code{modules()} defaults to \code{"root"}. See \code{Details}.}
 \item{plot_width}{optional, (\code{numeric}) Specifies the plot width as a three-element vector of
 \code{value}, \code{min}, and \code{max} for a slider encoding the plot width.}
 
-\item{parent_dataname}{(\code{character(1)}) If this \code{dataname} exists in then "the by subject"graph is displayed.
-For \code{CDISC} data. In non \code{CDISC} data this can be ignored. Defaults to \code{"ADSL"}.}
+\item{parent_dataname}{(\code{character(1)}) Specifies the parent dataset name. Default is \code{ADSL} for CDISC data.
+If provided and exists, enables additional analysis "by subject". For non-CDISC data, this parameter can be ignored.}
 
-\item{ggtheme}{optional, (\code{character}) \code{ggplot2} theme to be used by default. Defaults to \code{"classic"}.}
+\item{ggtheme}{(\code{character}, optional) Specifies the default \code{ggplot2} theme for plots. Defaults to \code{classic}.}
 
 \item{ggplot2_args}{optional, (\code{ggplot2_args}) object created by \code{\link[teal.widgets:ggplot2_args]{teal.widgets::ggplot2_args()}}
 with settings for all the plots or named list of \code{ggplot2_args} objects for plot-specific settings.
@@ -48,8 +48,10 @@ with text placed before the output to put the output into context. For example a
 adding context or further instructions. Elements like \code{shiny::helpText()} are useful.}
 }
 \description{
-Present analysis of missing observations and patients.
-specifically designed for use with \code{data.frames}.
+Module analyzes missing data in \code{data.frame}s to help users explore missing observations and
+gain insights into the completeness of their data.
+It is useful for clinical data analysis within the context of CDISC standards and
+adaptable for general data analysis purposes.
 }
 \examples{
 library(teal.widgets)

From 39ede58a572b83a5d4deb57ad4f8b9e7f2e74c88 Mon Sep 17 00:00:00 2001
From: kartikeya kirar <kirar.kartikeya1@gmail.com>
Date: Mon, 26 Feb 2024 20:26:51 +0530
Subject: [PATCH 31/62] pre-release `tm_g_scatterplotmatrix` document update
 (#661)
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

part of
https://github.com/insightsengineering/teal.modules.general/issues/624

---------

Signed-off-by: kartikeya kirar <kirar.kartikeya1@gmail.com>
Co-authored-by: André Veríssimo <211358+averissimo@users.noreply.github.com>
---
 R/tm_g_scatterplotmatrix.R         | 59 +++++++++++++++++-------------
 man/get_scatterplotmatrix_stats.Rd | 32 ++++++++--------
 man/tm_g_scatterplotmatrix.Rd      |  9 +++--
 3 files changed, 54 insertions(+), 46 deletions(-)

diff --git a/R/tm_g_scatterplotmatrix.R b/R/tm_g_scatterplotmatrix.R
index 6f740f032..a334686cd 100644
--- a/R/tm_g_scatterplotmatrix.R
+++ b/R/tm_g_scatterplotmatrix.R
@@ -1,20 +1,20 @@
-#' Create a scatterplot matrix
+#' Scatterplot matrix module
 #'
-#' The available datasets to choose from for each dataset selector is the same and
-#' determined by the argument `variables`.
-#' @md
+#' Generates a scatterplot matrix from selected `variables` from datasets.
+#' Each plot within the matrix represents the relationship between two variables,
+#' providing the overview of correlations and distributions across selected data.
+#'
+#' @note For more examples, please see the vignette "Using scatterplot matrix" via
+#' `vignette("using-scatterplot-matrix", package = "teal.modules.general")`.
 #'
 #' @inheritParams teal::module
 #' @inheritParams tm_g_scatterplot
 #' @inheritParams shared_params
 #'
 #' @param variables (`data_extract_spec` or `list` of multiple `data_extract_spec`)
-#'  Plotting variables from an incoming dataset with filtering and selecting. In case of
-#'  `data_extract_spec` use `select_spec(..., ordered = TRUE)` if plot elements should be
-#'  rendered according to selection order.
-#'
-#' @note For more examples, please see the vignette "Using scatterplot matrix" via
-#'   \code{vignette("using-scatterplot-matrix", package = "teal.modules.general")}.
+#' Specifies plotting variables from an incoming dataset with filtering and selecting. In case of
+#' `data_extract_spec` use `select_spec(..., ordered = TRUE)` if plot elements should be
+#' rendered according to selection order.
 #'
 #' @examples
 #' # general data example
@@ -187,6 +187,7 @@ tm_g_scatterplotmatrix <- function(label = "Scatterplot Matrix",
   )
 }
 
+# UI function for the scatterplot matrix module
 ui_g_scatterplotmatrix <- function(id, ...) {
   args <- list(...)
   is_single_dataset_value <- teal.transform::is_single_dataset(args$variables)
@@ -243,6 +244,7 @@ ui_g_scatterplotmatrix <- function(id, ...) {
   )
 }
 
+# Server function for the scatterplot matrix module
 srv_g_scatterplotmatrix <- function(id, data, reporter, filter_panel_api, variables, plot_height, plot_width) {
   with_reporter <- !missing(reporter) && inherits(reporter, "Reporter")
   with_filter <- !missing(filter_panel_api) && inherits(filter_panel_api, "FilterPanelAPI")
@@ -461,26 +463,28 @@ srv_g_scatterplotmatrix <- function(id, data, reporter, filter_panel_api, variab
 }
 
 #' Get stats for x-y pairs in scatterplot matrix
-#' @description uses stats::cor.test per default for all numerical input variables and converts results
-#'  to character vector. Could be extended if different stats for different variable
-#'  types are needed. Meant to be called from \code{lattice::panel.text}.
-#' @param x \code{numeric}
-#' @param y \code{numeric}
-#' @param .f \code{function}, function that accepts x and y as formula input \code{~ x + y}.
-#' Default \code{stats::cor.test}
-#' @param .f_args \code{list} of arguments to be passed to \code{.f}
-#' @param round_stat \code{integer}
-#' @param round_pval \code{integer}
-#' @details presently we need to use a formula input for \code{stats::cor.test} because
-#' \code{na.fail} only gets evaluated when a formula is passed (see below).
-#' \preformatted{
+#'
+#' Uses [stats::cor.test()] per default for all numerical input variables and converts results
+#' to character vector.
+#' Could be extended if different stats for different variable types are needed.
+#' Meant to be called from [lattice::panel.text()].
+#'
+#' Presently we need to use a formula input for `stats::cor.test` because
+#' `na.fail` only gets evaluated when a formula is passed (see below).
+#' ```
 #' x = c(1,3,5,7,NA)
 #' y = c(3,6,7,8,1)
 #' stats::cor.test(x, y, na.action = "na.fail")
 #' stats::cor.test(~ x + y,  na.action = "na.fail")
-#' }
-#' @return \code{character} with stats. For \code{stats::cor.test} correlation coefficient and p-value.
-#' @export
+#' ```
+#' @param x,y (`numeric`) vectors of data values. `x` and `y` must have the same length.
+#' @param .f (`function`) function that accepts x and y as formula input `~ x + y`.
+#' Default `stats::cor.test`.
+#' @param .f_args (`list`) of arguments to be passed to `.f`.
+#' @param round_stat (`integer(1)`) optional. Number of decimal places to use when rounding the estimate.
+#' @param round_pval (`integer(1)`) optional. Number of decimal places to use when rounding the p-value.
+#'
+#' @return Character with stats. For [stats::cor.test()] correlation coefficient and p-value.
 #' @examples
 #' set.seed(1)
 #' x <- runif(25, 0, 1)
@@ -492,6 +496,9 @@ srv_g_scatterplotmatrix <- function(id, data, reporter, filter_panel_api, variab
 #'   method = "pearson",
 #'   na.action = na.fail
 #' ))
+#'
+#' @export
+#'
 get_scatterplotmatrix_stats <- function(x, y,
                                         .f = stats::cor.test,
                                         .f_args = list(),
diff --git a/man/get_scatterplotmatrix_stats.Rd b/man/get_scatterplotmatrix_stats.Rd
index 514c70f43..f50928b5c 100644
--- a/man/get_scatterplotmatrix_stats.Rd
+++ b/man/get_scatterplotmatrix_stats.Rd
@@ -14,36 +14,35 @@ get_scatterplotmatrix_stats(
 )
 }
 \arguments{
-\item{x}{\code{numeric}}
+\item{x, y}{(\code{numeric}) vectors of data values. \code{x} and \code{y} must have the same length.}
 
-\item{y}{\code{numeric}}
+\item{.f}{(\code{function}) function that accepts x and y as formula input \code{~ x + y}.
+Default \code{stats::cor.test}.}
 
-\item{.f}{\code{function}, function that accepts x and y as formula input \code{~ x + y}.
-Default \code{stats::cor.test}}
+\item{.f_args}{(\code{list}) of arguments to be passed to \code{.f}.}
 
-\item{.f_args}{\code{list} of arguments to be passed to \code{.f}}
+\item{round_stat}{(\code{integer(1)}) optional. Number of decimal places to use when rounding the estimate.}
 
-\item{round_stat}{\code{integer}}
-
-\item{round_pval}{\code{integer}}
+\item{round_pval}{(\code{integer(1)}) optional. Number of decimal places to use when rounding the p-value.}
 }
 \value{
-\code{character} with stats. For \code{stats::cor.test} correlation coefficient and p-value.
+Character with stats. For \code{\link[stats:cor.test]{stats::cor.test()}} correlation coefficient and p-value.
 }
 \description{
-uses stats::cor.test per default for all numerical input variables and converts results
-to character vector. Could be extended if different stats for different variable
-types are needed. Meant to be called from \code{lattice::panel.text}.
+Uses \code{\link[stats:cor.test]{stats::cor.test()}} per default for all numerical input variables and converts results
+to character vector.
+Could be extended if different stats for different variable types are needed.
+Meant to be called from \code{\link[lattice:llines]{lattice::panel.text()}}.
 }
 \details{
-presently we need to use a formula input for \code{stats::cor.test} because
+Presently we need to use a formula input for \code{stats::cor.test} because
 \code{na.fail} only gets evaluated when a formula is passed (see below).
-\preformatted{
-x = c(1,3,5,7,NA)
+
+\if{html}{\out{<div class="sourceCode">}}\preformatted{x = c(1,3,5,7,NA)
 y = c(3,6,7,8,1)
 stats::cor.test(x, y, na.action = "na.fail")
 stats::cor.test(~ x + y,  na.action = "na.fail")
-}
+}\if{html}{\out{</div>}}
 }
 \examples{
 set.seed(1)
@@ -56,4 +55,5 @@ get_scatterplotmatrix_stats(x, y, .f = stats::cor.test, .f_args = list(
   method = "pearson",
   na.action = na.fail
 ))
+
 }
diff --git a/man/tm_g_scatterplotmatrix.Rd b/man/tm_g_scatterplotmatrix.Rd
index 120a32476..4b9ca755d 100644
--- a/man/tm_g_scatterplotmatrix.Rd
+++ b/man/tm_g_scatterplotmatrix.Rd
@@ -2,7 +2,7 @@
 % Please edit documentation in R/tm_g_scatterplotmatrix.R
 \name{tm_g_scatterplotmatrix}
 \alias{tm_g_scatterplotmatrix}
-\title{Create a scatterplot matrix}
+\title{Scatterplot matrix module}
 \usage{
 tm_g_scatterplotmatrix(
   label = "Scatterplot Matrix",
@@ -18,7 +18,7 @@ tm_g_scatterplotmatrix(
 For \code{modules()} defaults to \code{"root"}. See \code{Details}.}
 
 \item{variables}{(\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec})
-Plotting variables from an incoming dataset with filtering and selecting. In case of
+Specifies plotting variables from an incoming dataset with filtering and selecting. In case of
 \code{data_extract_spec} use \code{select_spec(..., ordered = TRUE)} if plot elements should be
 rendered according to selection order.}
 
@@ -36,8 +36,9 @@ with text placed before the output to put the output into context. For example a
 adding context or further instructions. Elements like \code{shiny::helpText()} are useful.}
 }
 \description{
-The available datasets to choose from for each dataset selector is the same and
-determined by the argument \code{variables}.
+Generates a scatterplot matrix from selected \code{variables} from datasets.
+Each plot within the matrix represents the relationship between two variables,
+providing the overview of correlations and distributions across selected data.
 }
 \note{
 For more examples, please see the vignette "Using scatterplot matrix" via

From da6ab637adf935be26d44cb4a43e442bb6787074 Mon Sep 17 00:00:00 2001
From: m7pr <marcin.kosinski.mk1@roche.com>
Date: Mon, 26 Feb 2024 16:23:36 +0100
Subject: [PATCH 32/62] backticks for ggplot2

---
 R/utils.R               | 4 ++--
 man/add_facet_labels.Rd | 4 ++--
 2 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/R/utils.R b/R/utils.R
index fd0dbef79..cdcb4ece7 100644
--- a/R/utils.R
+++ b/R/utils.R
@@ -32,9 +32,9 @@
 #' @keywords internal
 NULL
 
-#' Add labels for facets to a ggplot2 object
+#' Add labels for facets to a `ggplot2` object
 #'
-#' Enhances a ggplot2 plot by adding labels that describe
+#' Enhances a `ggplot2` plot by adding labels that describe
 #' the faceting variables along the x and y axes.
 #'
 #' @param p (`ggplot2`) object to which facet labels will be added.
diff --git a/man/add_facet_labels.Rd b/man/add_facet_labels.Rd
index 02cd828ba..439b43998 100644
--- a/man/add_facet_labels.Rd
+++ b/man/add_facet_labels.Rd
@@ -2,7 +2,7 @@
 % Please edit documentation in R/utils.R
 \name{add_facet_labels}
 \alias{add_facet_labels}
-\title{Add labels for facets to a ggplot2 object}
+\title{Add labels for facets to a \code{ggplot2} object}
 \usage{
 add_facet_labels(p, xfacet_label = NULL, yfacet_label = NULL)
 }
@@ -19,7 +19,7 @@ Similar behavior to \code{xfacet_label}.}
 Returns \code{grid} or \code{grob} object (to be drawn with \code{grid.draw})
 }
 \description{
-Enhances a ggplot2 plot by adding labels that describe
+Enhances a \code{ggplot2} plot by adding labels that describe
 the faceting variables along the x and y axes.
 }
 \examples{

From 658743c089fd69224c97d5b416320a72b88b214e Mon Sep 17 00:00:00 2001
From: m7pr <marcin.kosinski.mk1@roche.com>
Date: Mon, 26 Feb 2024 16:25:49 +0100
Subject: [PATCH 33/62] WORDLIST fixes

---
 R/tm_missing_data.R    | 6 +++---
 inst/WORDLIST          | 3 +++
 man/tm_missing_data.Rd | 6 +++---
 3 files changed, 9 insertions(+), 6 deletions(-)

diff --git a/R/tm_missing_data.R b/R/tm_missing_data.R
index 48f9f9941..595ca99a2 100644
--- a/R/tm_missing_data.R
+++ b/R/tm_missing_data.R
@@ -2,13 +2,13 @@
 #'
 #' Module analyzes missing data in `data.frame`s to help users explore missing observations and
 #' gain insights into the completeness of their data.
-#' It is useful for clinical data analysis within the context of CDISC standards and
+#' It is useful for clinical data analysis within the context of `CDISC` standards and
 #' adaptable for general data analysis purposes.
 #'
 #' @inheritParams teal::module
 #' @inheritParams shared_params
-#' @param parent_dataname (`character(1)`) Specifies the parent dataset name. Default is `ADSL` for CDISC data.
-#' If provided and exists, enables additional analysis "by subject". For non-CDISC data, this parameter can be ignored.
+#' @param parent_dataname (`character(1)`) Specifies the parent dataset name. Default is `ADSL` for `CDISC` data.
+#' If provided and exists, enables additional analysis "by subject". For non-`CDISC` data, this parameter can be ignored.
 #' @param ggtheme (`character`, optional) Specifies the default `ggplot2` theme for plots. Defaults to `classic`.
 #'
 #' @templateVar ggnames "Summary Obs", "Summary Patients", "Combinations Main", "Combinations Hist", "By Subject"
diff --git a/inst/WORDLIST b/inst/WORDLIST
index e59688844..e192da222 100644
--- a/inst/WORDLIST
+++ b/inst/WORDLIST
@@ -1,3 +1,4 @@
+customizable
 Forkers
 Hoffmann
 TLG
@@ -7,4 +8,6 @@ pre
 Prebuilt
 repo
 reproducibility
+sortable
 tabset
+UI
diff --git a/man/tm_missing_data.Rd b/man/tm_missing_data.Rd
index 6ca59c853..94e026581 100644
--- a/man/tm_missing_data.Rd
+++ b/man/tm_missing_data.Rd
@@ -27,8 +27,8 @@ For \code{modules()} defaults to \code{"root"}. See \code{Details}.}
 \item{plot_width}{optional, (\code{numeric}) Specifies the plot width as a three-element vector of
 \code{value}, \code{min}, and \code{max} for a slider encoding the plot width.}
 
-\item{parent_dataname}{(\code{character(1)}) Specifies the parent dataset name. Default is \code{ADSL} for CDISC data.
-If provided and exists, enables additional analysis "by subject". For non-CDISC data, this parameter can be ignored.}
+\item{parent_dataname}{(\code{character(1)}) Specifies the parent dataset name. Default is \code{ADSL} for \code{CDISC} data.
+If provided and exists, enables additional analysis "by subject". For non-\code{CDISC} data, this parameter can be ignored.}
 
 \item{ggtheme}{(\code{character}, optional) Specifies the default \code{ggplot2} theme for plots. Defaults to \code{classic}.}
 
@@ -50,7 +50,7 @@ adding context or further instructions. Elements like \code{shiny::helpText()} a
 \description{
 Module analyzes missing data in \code{data.frame}s to help users explore missing observations and
 gain insights into the completeness of their data.
-It is useful for clinical data analysis within the context of CDISC standards and
+It is useful for clinical data analysis within the context of \code{CDISC} standards and
 adaptable for general data analysis purposes.
 }
 \examples{

From 8d02d0c8309878cafa56587a4d7494b2300970de Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Andr=C3=A9=20Ver=C3=ADssimo?=
 <211358+averissimo@users.noreply.github.com>
Date: Mon, 26 Feb 2024 16:37:36 +0100
Subject: [PATCH 34/62] pre-release: Update verdpecheck and pre-commit (#683)

# Pull Request

Part of #624

Follow-up to:

- #643

### Changes description

- Removes `magrittr` from `Config/Needs/verdepcheck`
- Re-order `verdpecheck` with same order on `Depends`, `Imports`,
`Suggests`
- Re-order `pre-commit` config with same order on `Depends`, `Imports`,
`Suggests`
- Add remote repo to `htmlwidgets/sparkline` (despite not being updated
in years) in `verdepcheck`
---
 .pre-commit-config.yaml |  5 ++---
 DESCRIPTION             | 13 +++++++------
 2 files changed, 9 insertions(+), 9 deletions(-)

diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index f10b1244e..32b229ef8 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -18,17 +18,17 @@ repos:
           - ggmosaic
           - ggplot2
           - shiny
-          - shinyTree
           - insightsengineering/teal
+          - insightsengineering/teal.transform
           - checkmate
           - dplyr
           - DT
           - forcats
           - grid
           - logger
-          - magrittr
           - scales
           - shinyjs
+          - shinyTree
           - shinyvalidate
           - shinyWidgets
           - stats
@@ -38,7 +38,6 @@ repos:
           - insightsengineering/teal.logger
           - insightsengineering/teal.reporter
           - insightsengineering/teal.slice
-          - insightsengineering/teal.transform
           - insightsengineering/teal.widgets
           - tern
           - tibble
diff --git a/DESCRIPTION b/DESCRIPTION
index 695aed2e8..c33ad34be 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -74,19 +74,20 @@ Suggests:
 VignetteBuilder:
     knitr
 Config/Needs/verdepcheck: haleyjeppson/ggmosaic, tidyverse/ggplot2,
-    rstudio/shiny, shinyTree/shinyTree, insightsengineering/teal,
+    rstudio/shiny, insightsengineering/teal, insightsengineering/teal.transform,
     mllg/checkmate, tidyverse/dplyr, rstudio/DT, tidyverse/forcats,
-    daroczig/logger, tidyverse/magrittr, r-lib/scales, daattali/shinyjs,
+    daroczig/logger, r-lib/scales, daattali/shinyjs,
+    shinyTree/shinyTree,
     rstudio/shinyvalidate, dreamRs/shinyWidgets, tidyverse/stringr,
-    insightsengineering/teal.code, insightsengineering/teal.logger,
-    insightsengineering/teal.reporter, insightsengineering/teal.transform,
+    insightsengineering/teal.code, insightsengineering/teal.data,
+    insightsengineering/teal.logger, insightsengineering/teal.reporter,
     insightsengineering/teal.widgets, insightsengineering/tern,
     tidyverse/tibble, tidyverse/tidyr, tidymodels/broom,
     daattali/colourpicker, daattali/ggExtra, aphalo/ggpmisc, aphalo/ggpp,
     baddstats/goftest, gridExtra, ramnathv/htmlwidgets, jeroen/jsonlite,
     yihui/knitr, deepayan/lattice, MASS, insightsengineering/nestcolor,
-    r-lib/rlang, insightsengineering/rtables, sparkline,
-    insightsengineering/teal.data, r-lib/testthat
+    r-lib/rlang, insightsengineering/rtables, htmlwidgets/sparkline,
+    r-lib/testthat
 Config/Needs/website: insightsengineering/nesttemplate
 Encoding: UTF-8
 Language: en-US

From 7c6cde071eac6b646c977b948f5e6dddf1973465 Mon Sep 17 00:00:00 2001
From: m7pr <marcin.kosinski.mk1@roche.com>
Date: Mon, 26 Feb 2024 16:44:52 +0100
Subject: [PATCH 35/62] superlint fix

---
 R/tm_missing_data.R    | 3 ++-
 man/tm_missing_data.Rd | 3 ++-
 2 files changed, 4 insertions(+), 2 deletions(-)

diff --git a/R/tm_missing_data.R b/R/tm_missing_data.R
index 595ca99a2..ce4240ded 100644
--- a/R/tm_missing_data.R
+++ b/R/tm_missing_data.R
@@ -8,7 +8,8 @@
 #' @inheritParams teal::module
 #' @inheritParams shared_params
 #' @param parent_dataname (`character(1)`) Specifies the parent dataset name. Default is `ADSL` for `CDISC` data.
-#' If provided and exists, enables additional analysis "by subject". For non-`CDISC` data, this parameter can be ignored.
+#' If provided and exists, enables additional analysis "by subject". For non-`CDISC` data, this parameter can be
+#' ignored.
 #' @param ggtheme (`character`, optional) Specifies the default `ggplot2` theme for plots. Defaults to `classic`.
 #'
 #' @templateVar ggnames "Summary Obs", "Summary Patients", "Combinations Main", "Combinations Hist", "By Subject"
diff --git a/man/tm_missing_data.Rd b/man/tm_missing_data.Rd
index 94e026581..e94ed9dfe 100644
--- a/man/tm_missing_data.Rd
+++ b/man/tm_missing_data.Rd
@@ -28,7 +28,8 @@ For \code{modules()} defaults to \code{"root"}. See \code{Details}.}
 \code{value}, \code{min}, and \code{max} for a slider encoding the plot width.}
 
 \item{parent_dataname}{(\code{character(1)}) Specifies the parent dataset name. Default is \code{ADSL} for \code{CDISC} data.
-If provided and exists, enables additional analysis "by subject". For non-\code{CDISC} data, this parameter can be ignored.}
+If provided and exists, enables additional analysis "by subject". For non-\code{CDISC} data, this parameter can be
+ignored.}
 
 \item{ggtheme}{(\code{character}, optional) Specifies the default \code{ggplot2} theme for plots. Defaults to \code{classic}.}
 

From b3ed9fafbea109f203ba2f02385d797ae804c9e7 Mon Sep 17 00:00:00 2001
From: kartikeya kirar <kirar.kartikeya1@gmail.com>
Date: Tue, 27 Feb 2024 12:58:56 +0530
Subject: [PATCH 36/62] pre-release `tm_g_association` document update (#656)

part of
https://github.com/insightsengineering/teal.modules.general/issues/624
---
 R/tm_g_association.R    | 33 +++++++++++++++++++--------------
 man/tm_g_association.Rd | 19 ++++++++++---------
 2 files changed, 29 insertions(+), 23 deletions(-)

diff --git a/R/tm_g_association.R b/R/tm_g_association.R
index e262cb584..1ee28d45a 100644
--- a/R/tm_g_association.R
+++ b/R/tm_g_association.R
@@ -1,27 +1,32 @@
-#' Stack Plots of variables and show association with reference variable
-#' @md
+#' Stack plots of variables and show association with reference variable
+#'
+#' Module provides functionality for visualizing the distribution of variables and
+#' their association with a reference variable.
+#' It supports configuring the appearance of the plots, including themes and whether to show associations.
+#'
+#'
+#' @note For more examples, please see the vignette "Using association plot" via
+#' `vignette("using-association-plot", package = "teal.modules.general")`.
 #'
 #' @inheritParams teal::module
 #' @inheritParams shared_params
 #' @param ref (`data_extract_spec` or `list` of multiple `data_extract_spec`)
-#'   reference variable, must set `multiple = FALSE`.
+#' Reference variable, must accepts a `data_extract_spec` with `select_spec(multiple = FALSE)`
+#' to ensure single selection option.
 #' @param vars (`data_extract_spec` or `list` of multiple `data_extract_spec`)
-#'   associated variables.
-#' @param show_association optional, (`logical`) Whether show association of `vars`
-#'   with reference variable. Defaults to `TRUE`.
-#' @param distribution_theme,association_theme optional, (`character`) `ggplot2` themes to be used by default.
-#'   Default to `"gray"`.
+#' Variables to be associated with the reference variable.
+#' @param show_association (`logical`) optional whether show association of `vars`
+#' with reference variable. Defaults to `TRUE`.
+#' @param distribution_theme,association_theme (`character`) optional `ggplot2` themes to be used by default.
+#' Default to `"gray"`.
 #'
 #' @templateVar ggnames "Bivariate1", "Bivariate2"
 #' @template ggplot2_args_multi
 #'
-#' @note For more examples, please see the vignette "Using association plot" via
-#'   \code{vignette("using-association-plot", package = "teal.modules.general")}.
-#'
 #' @examples
-#' # general data exapmle
 #' library(teal.widgets)
 #'
+#' # general data example
 #' data <- teal_data()
 #' data <- within(data, {
 #'   require(nestcolor)
@@ -65,8 +70,6 @@
 #' }
 #'
 #' # CDISC data example
-#' library(teal.widgets)
-#'
 #' data <- teal_data()
 #' data <- within(data, {
 #'   require(nestcolor)
@@ -172,6 +175,7 @@ tm_g_association <- function(label = "Association",
   )
 }
 
+# UI function for the association module
 ui_tm_g_association <- function(id, ...) {
   ns <- NS(id)
   args <- list(...)
@@ -249,6 +253,7 @@ ui_tm_g_association <- function(id, ...) {
   )
 }
 
+# Server function for the association module
 srv_tm_g_association <- function(id,
                                  data,
                                  reporter,
diff --git a/man/tm_g_association.Rd b/man/tm_g_association.Rd
index dc45e7014..aa851556a 100644
--- a/man/tm_g_association.Rd
+++ b/man/tm_g_association.Rd
@@ -2,7 +2,7 @@
 % Please edit documentation in R/tm_g_association.R
 \name{tm_g_association}
 \alias{tm_g_association}
-\title{Stack Plots of variables and show association with reference variable}
+\title{Stack plots of variables and show association with reference variable}
 \usage{
 tm_g_association(
   label = "Association",
@@ -25,12 +25,13 @@ tm_g_association(
 For \code{modules()} defaults to \code{"root"}. See \code{Details}.}
 
 \item{ref}{(\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec})
-reference variable, must set \code{multiple = FALSE}.}
+Reference variable, must accepts a \code{data_extract_spec} with \code{select_spec(multiple = FALSE)}
+to ensure single selection option.}
 
 \item{vars}{(\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec})
-associated variables.}
+Variables to be associated with the reference variable.}
 
-\item{show_association}{optional, (\code{logical}) Whether show association of \code{vars}
+\item{show_association}{(\code{logical}) optional whether show association of \code{vars}
 with reference variable. Defaults to \code{TRUE}.}
 
 \item{plot_height}{optional, (\code{numeric}) Specifies the plot height as a three-element vector of
@@ -39,7 +40,7 @@ with reference variable. Defaults to \code{TRUE}.}
 \item{plot_width}{optional, (\code{numeric}) Specifies the plot width as a three-element vector of
 \code{value}, \code{min}, and \code{max} for a slider encoding the plot width.}
 
-\item{distribution_theme, association_theme}{optional, (\code{character}) \code{ggplot2} themes to be used by default.
+\item{distribution_theme, association_theme}{(\code{character}) optional \code{ggplot2} themes to be used by default.
 Default to \code{"gray"}.}
 
 \item{pre_output}{(\code{shiny.tag}, optional) Text or UI element to be displayed before the module's output,
@@ -58,16 +59,18 @@ List names should match the following: \code{c("default", "Bivariate1", "Bivaria
 For more details see the vignette: \code{vignette("custom-ggplot2-arguments", package = "teal.widgets")}.}
 }
 \description{
-Stack Plots of variables and show association with reference variable
+Module provides functionality for visualizing the distribution of variables and
+their association with a reference variable.
+It supports configuring the appearance of the plots, including themes and whether to show associations.
 }
 \note{
 For more examples, please see the vignette "Using association plot" via
 \code{vignette("using-association-plot", package = "teal.modules.general")}.
 }
 \examples{
-# general data exapmle
 library(teal.widgets)
 
+# general data example
 data <- teal_data()
 data <- within(data, {
   require(nestcolor)
@@ -111,8 +114,6 @@ if (interactive()) {
 }
 
 # CDISC data example
-library(teal.widgets)
-
 data <- teal_data()
 data <- within(data, {
   require(nestcolor)

From 446ce562eff5b8ed70b67b01cfdf3074e717e662 Mon Sep 17 00:00:00 2001
From: kartikeya kirar <kirar.kartikeya1@gmail.com>
Date: Tue, 27 Feb 2024 13:43:54 +0530
Subject: [PATCH 37/62] pre-release `tm_g_distribution` document update (#669)

part of
https://github.com/insightsengineering/teal.modules.general/issues/624

---------

Signed-off-by: kartikeya kirar <kirar.kartikeya1@gmail.com>
Co-authored-by: Vedha Viyash <49812166+vedhav@users.noreply.github.com>
---
 R/tm_g_distribution.R    | 34 +++++++++++++++++-----------------
 man/tm_g_distribution.Rd | 33 ++++++++++++++++-----------------
 2 files changed, 33 insertions(+), 34 deletions(-)

diff --git a/R/tm_g_distribution.R b/R/tm_g_distribution.R
index f8edf3f1b..94bf69999 100644
--- a/R/tm_g_distribution.R
+++ b/R/tm_g_distribution.R
@@ -1,33 +1,33 @@
-#' Distribution Module
-#' @md
+#' Distribution analysis module
 #'
-#' @details
-#' Module to analyze and explore univariate variable distribution
+#' Module is designed to explore the distribution of a single variable within a given dataset.
+#' It offers several tools, such as histograms, Q-Q plots, and various statistical tests to
+#' visually and statistically analyze the variable's distribution.
 #'
 #' @inheritParams teal::module
 #' @inheritParams teal.widgets::standard_layout
 #' @inheritParams shared_params
 #'
 #' @param dist_var (`data_extract_spec` or `list` of multiple `data_extract_spec`)
-#'  Variable to consider for the distribution analysis.
+#' Variable(s) for which the distribution will be analyzed.
 #' @param strata_var (`data_extract_spec` or `list` of multiple `data_extract_spec`)
-#'   Categorical variable to split the selected distribution variable on.
-#' @param group_var  optional, (`data_extract_spec` or `list` of multiple `data_extract_spec`)
-#'   Which data columns to use for faceting rows.
-#' @param freq optional, (`logical`) Whether to display frequency (`TRUE`) or density (`FALSE`).
-#'   Defaults to density (`FALSE`).
-#' @param bins optional, (`integer(1)` or `integer(3)`) If scalar then the histogram bins will have a fixed size.
-#'   If a slider should be presented to adjust the number of histogram bins dynamically then it can be a
-#'   vector of length three with `c(value, min, max)`.
-#'   Defaults to `c(30L, 1L, 100L)`.
+#' Categorical variable used to split the distribution analysis.
+#' @param group_var (`data_extract_spec` or `list` of multiple `data_extract_spec`)
+#' Variable used for faceting plot into multiple panels.
+#' @param freq (`logical`, optional) Whether to display frequency (`TRUE`) or density (`FALSE`).
+#' Defaults to density (`FALSE`).
+#' @param bins (`integer(1)` or `integer(3)`, optional)  Determines the number of bins for the histogram.
+#' - When the length of `bins` is one: The histogram bins will have a fixed size based on the `bins` provided.
+#' - When the length of `bins` is three: The histogram bins are dynamically adjusted based on vector of `value`, `min`, and `max`.
+#' Defaults to `c(30L, 1L, 100L)`.
 #'
 #' @templateVar ggnames "Histogram", "QQplot"
 #' @template ggplot2_args_multi
 #'
 #' @examples
-#' # general data example
 #' library(teal.widgets)
 #'
+#' # general data example
 #' data <- teal_data()
 #' data <- within(data, {
 #'   iris <- iris
@@ -53,8 +53,6 @@
 #' }
 #'
 #' # CDISC data example
-#' library(teal.widgets)
-#'
 #' data <- teal_data()
 #' data <- within(data, {
 #'   ADSL <- rADSL
@@ -172,6 +170,7 @@ tm_g_distribution <- function(label = "Distribution Module",
   )
 }
 
+# UI function for the distribution module
 ui_distribution <- function(id, ...) {
   args <- list(...)
   ns <- NS(id)
@@ -317,6 +316,7 @@ ui_distribution <- function(id, ...) {
   )
 }
 
+# Server function for the distribution module
 srv_distribution <- function(id,
                              data,
                              reporter,
diff --git a/man/tm_g_distribution.Rd b/man/tm_g_distribution.Rd
index a28ed628a..f23f44b2f 100644
--- a/man/tm_g_distribution.Rd
+++ b/man/tm_g_distribution.Rd
@@ -2,7 +2,7 @@
 % Please edit documentation in R/tm_g_distribution.R
 \name{tm_g_distribution}
 \alias{tm_g_distribution}
-\title{Distribution Module}
+\title{Distribution analysis module}
 \usage{
 tm_g_distribution(
   label = "Distribution Module",
@@ -24,15 +24,15 @@ tm_g_distribution(
 For \code{modules()} defaults to \code{"root"}. See \code{Details}.}
 
 \item{dist_var}{(\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec})
-Variable to consider for the distribution analysis.}
+Variable(s) for which the distribution will be analyzed.}
 
 \item{strata_var}{(\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec})
-Categorical variable to split the selected distribution variable on.}
+Categorical variable used to split the distribution analysis.}
 
-\item{group_var}{optional, (\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec})
-Which data columns to use for faceting rows.}
+\item{group_var}{(\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec})
+Variable used for faceting plot into multiple panels.}
 
-\item{freq}{optional, (\code{logical}) Whether to display frequency (\code{TRUE}) or density (\code{FALSE}).
+\item{freq}{(\code{logical}, optional) Whether to display frequency (\code{TRUE}) or density (\code{FALSE}).
 Defaults to density (\code{FALSE}).}
 
 \item{ggtheme}{optional, (\code{character}) \code{ggplot2} theme to be used by default. Defaults to \code{"gray"}.}
@@ -45,10 +45,12 @@ List names should match the following: \code{c("default", "Histogram", "QQplot")
 
 For more details see the vignette: \code{vignette("custom-ggplot2-arguments", package = "teal.widgets")}.}
 
-\item{bins}{optional, (\code{integer(1)} or \code{integer(3)}) If scalar then the histogram bins will have a fixed size.
-If a slider should be presented to adjust the number of histogram bins dynamically then it can be a
-vector of length three with \code{c(value, min, max)}.
-Defaults to \code{c(30L, 1L, 100L)}.}
+\item{bins}{(\code{integer(1)} or \code{integer(3)}, optional)  Determines the number of bins for the histogram.
+\itemize{
+\item When the length of \code{bins} is one: The histogram bins will have a fixed size based on the \code{bins} provided.
+\item When the length of \code{bins} is three: The histogram bins are dynamically adjusted based on vector of \code{value}, \code{min}, and \code{max}.
+Defaults to \code{c(30L, 1L, 100L)}.
+}}
 
 \item{plot_height}{optional, (\code{numeric}) Specifies the plot height as a three-element vector of
 \code{value}, \code{min}, and \code{max} intended for use with a slider UI element.}
@@ -63,15 +65,14 @@ with text placed before the output to put the output into context. For example a
 into context. For example the \code{\link[shiny:helpText]{shiny::helpText()}} elements are useful.}
 }
 \description{
-Distribution Module
-}
-\details{
-Module to analyze and explore univariate variable distribution
+Module is designed to explore the distribution of a single variable within a given dataset.
+It offers several tools, such as histograms, Q-Q plots, and various statistical tests to
+visually and statistically analyze the variable's distribution.
 }
 \examples{
-# general data example
 library(teal.widgets)
 
+# general data example
 data <- teal_data()
 data <- within(data, {
   iris <- iris
@@ -97,8 +98,6 @@ if (interactive()) {
 }
 
 # CDISC data example
-library(teal.widgets)
-
 data <- teal_data()
 data <- within(data, {
   ADSL <- rADSL

From f0976772c2bf5d2599b101ba7b636fa543af96fa Mon Sep 17 00:00:00 2001
From: kartikeya kirar <kirar.kartikeya1@gmail.com>
Date: Tue, 27 Feb 2024 14:18:53 +0530
Subject: [PATCH 38/62] pre-release `tm_a_regression` document update (#655)

part of
https://github.com/insightsengineering/teal.modules.general/issues/624

---------

Co-authored-by: github-actions <41898282+github-actions[bot]@users.noreply.github.com>
---
 R/tm_a_regression.R    | 39 +++++++++++++++++++++++----------------
 man/tm_a_regression.Rd | 29 +++++++++++++++++++----------
 2 files changed, 42 insertions(+), 26 deletions(-)

diff --git a/R/tm_a_regression.R b/R/tm_a_regression.R
index 26f3180ba..e3dd0bfd3 100644
--- a/R/tm_a_regression.R
+++ b/R/tm_a_regression.R
@@ -1,20 +1,29 @@
-#' Scatterplot and Regression Model
-#' @md
+#' Scatterplot and regression model
+#'
+#' Module for visualizing regression analysis, including scatterplots and
+#' various regression diagnostics plots.
+#' It allows users to explore the relationship between a set of regressors and a response variable,
+#' visualize residuals, and identify outliers.
+#'
+#' @note For more examples, please see the vignette "Using regression plots" via
+#' `vignette("using-regression-plots", package = "teal.modules.general")`.
 #'
 #' @inheritParams teal::module
 #' @inheritParams shared_params
 #' @param regressor (`data_extract_spec` or `list` of multiple `data_extract_spec`)
-#'  Regressor variables from an incoming dataset with filtering and selecting.
+#' Regressor variables from an incoming dataset with filtering and selecting.
 #' @param response (`data_extract_spec` or `list` of multiple `data_extract_spec`)
-#'  Response variables from an incoming dataset with filtering and selecting.
-#' @param alpha optional, (`numeric`) If scalar then the plot points will have a fixed opacity. If a
-#'   slider should be presented to adjust the plot point opacity dynamically then it can be a vector of
-#'   length three with `c(value, min, max)`.
-#' @param size optional, (`numeric`) If scalar then the plot point sizes will have a fixed size
-#'   If a slider should be presented to adjust the plot point sizes dynamically then it can be a
-#'   vector of length three with `c(value, min, max)`.
-#' @param default_outlier_label optional, (`character`) The default column selected to label outliers.
-#' @param default_plot_type optional, (`numeric`) Defaults to Response vs Regressor.
+#' Response variables from an incoming dataset with filtering and selecting.
+#' @param alpha (`integer(1)` or `integer(3)`, optional) Specifies point opacity.
+#' - When the length of `alpha` is one: the plot points will have a fixed opacity.
+#' - When the length of `alpha` is three: the plot points opacity are dynamically adjusted based on
+#' vector of `value`, `min`, and `max`.
+#' @param size (`integer(1)` or `integer(3)`, optional) Specifies point size.
+#' - When the length of `size` is one: the plot point sizes will have a fixed size.
+#' - When the length of `size` is three: the plot points size are dynamically adjusted based on
+#' vector of `value`, `min`, and `max`.
+#' @param default_outlier_label (`character`, optional) The default column selected to label outliers.
+#' @param default_plot_type (`numeric`, optional) Defaults to Response vs Regressor.
 #' 1. Response vs Regressor
 #' 2. Residuals vs Fitted
 #' 3. Normal Q-Q
@@ -26,9 +35,6 @@
 #' @templateVar ggnames `r regression_names`
 #' @template ggplot2_args_multi
 #'
-#' @note For more examples, please see the vignette "Using regression plots" via
-#'   `vignette("using-regression-plots", package = "teal.modules.general")`.
-#'
 #' @examples
 #' # general data example
 #' library(teal.widgets)
@@ -189,6 +195,7 @@ tm_a_regression <- function(label = "Regression Analysis",
   )
 }
 
+# UI function for the regression module
 ui_a_regression <- function(id, ...) {
   ns <- NS(id)
   args <- list(...)
@@ -276,7 +283,7 @@ ui_a_regression <- function(id, ...) {
   )
 }
 
-
+# Server function for the regression module
 srv_a_regression <- function(id,
                              data,
                              reporter,
diff --git a/man/tm_a_regression.Rd b/man/tm_a_regression.Rd
index 100cdaeab..5d539d163 100644
--- a/man/tm_a_regression.Rd
+++ b/man/tm_a_regression.Rd
@@ -2,7 +2,7 @@
 % Please edit documentation in R/tm_a_regression.R
 \name{tm_a_regression}
 \alias{tm_a_regression}
-\title{Scatterplot and Regression Model}
+\title{Scatterplot and regression model}
 \usage{
 tm_a_regression(
   label = "Regression Analysis",
@@ -36,13 +36,19 @@ Response variables from an incoming dataset with filtering and selecting.}
 \item{plot_width}{optional, (\code{numeric}) Specifies the plot width as a three-element vector of
 \code{value}, \code{min}, and \code{max} for a slider encoding the plot width.}
 
-\item{alpha}{optional, (\code{numeric}) If scalar then the plot points will have a fixed opacity. If a
-slider should be presented to adjust the plot point opacity dynamically then it can be a vector of
-length three with \code{c(value, min, max)}.}
+\item{alpha}{(\code{integer(1)} or \code{integer(3)}, optional) Specifies point opacity.
+\itemize{
+\item When the length of \code{alpha} is one: the plot points will have a fixed opacity.
+\item When the length of \code{alpha} is three: the plot points opacity are dynamically adjusted based on
+vector of \code{value}, \code{min}, and \code{max}.
+}}
 
-\item{size}{optional, (\code{numeric}) If scalar then the plot point sizes will have a fixed size
-If a slider should be presented to adjust the plot point sizes dynamically then it can be a
-vector of length three with \code{c(value, min, max)}.}
+\item{size}{(\code{integer(1)} or \code{integer(3)}, optional) Specifies point size.
+\itemize{
+\item When the length of \code{size} is one: the plot point sizes will have a fixed size.
+\item When the length of \code{size} is three: the plot points size are dynamically adjusted based on
+vector of \code{value}, \code{min}, and \code{max}.
+}}
 
 \item{ggtheme}{optional, (\code{character}) \code{ggplot2} theme to be used by default. Defaults to \code{"gray"}.}
 
@@ -61,7 +67,7 @@ with text placed before the output to put the output into context. For example a
 \item{post_output}{(\code{shiny.tag}, optional) Text or UI element to be displayed after the module's output,
 adding context or further instructions. Elements like \code{shiny::helpText()} are useful.}
 
-\item{default_plot_type}{optional, (\code{numeric}) Defaults to Response vs Regressor.
+\item{default_plot_type}{(\code{numeric}, optional) Defaults to Response vs Regressor.
 \enumerate{
 \item Response vs Regressor
 \item Residuals vs Fitted
@@ -72,10 +78,13 @@ adding context or further instructions. Elements like \code{shiny::helpText()} a
 \item Cook's dist vs Leverage
 }}
 
-\item{default_outlier_label}{optional, (\code{character}) The default column selected to label outliers.}
+\item{default_outlier_label}{(\code{character}, optional) The default column selected to label outliers.}
 }
 \description{
-Scatterplot and Regression Model
+Module for visualizing regression analysis, including scatterplots and
+various regression diagnostics plots.
+It allows users to explore the relationship between a set of regressors and a response variable,
+visualize residuals, and identify outliers.
 }
 \note{
 For more examples, please see the vignette "Using regression plots" via

From 882a8d06dea2e8f7da8672d14bba565075ef4ea7 Mon Sep 17 00:00:00 2001
From: m7pr <marcin.kosinski.mk1@roche.com>
Date: Tue, 27 Feb 2024 10:21:26 +0100
Subject: [PATCH 39/62] lintr issues

---
 R/tm_g_distribution.R    | 3 ++-
 man/tm_g_distribution.Rd | 3 ++-
 2 files changed, 4 insertions(+), 2 deletions(-)

diff --git a/R/tm_g_distribution.R b/R/tm_g_distribution.R
index 94bf69999..a60d6465f 100644
--- a/R/tm_g_distribution.R
+++ b/R/tm_g_distribution.R
@@ -18,7 +18,8 @@
 #' Defaults to density (`FALSE`).
 #' @param bins (`integer(1)` or `integer(3)`, optional)  Determines the number of bins for the histogram.
 #' - When the length of `bins` is one: The histogram bins will have a fixed size based on the `bins` provided.
-#' - When the length of `bins` is three: The histogram bins are dynamically adjusted based on vector of `value`, `min`, and `max`.
+#' - When the length of `bins` is three: The histogram bins are dynamically adjusted based on vector of `value`, `min`,
+#' and `max`.
 #' Defaults to `c(30L, 1L, 100L)`.
 #'
 #' @templateVar ggnames "Histogram", "QQplot"
diff --git a/man/tm_g_distribution.Rd b/man/tm_g_distribution.Rd
index f23f44b2f..a04c07016 100644
--- a/man/tm_g_distribution.Rd
+++ b/man/tm_g_distribution.Rd
@@ -48,7 +48,8 @@ For more details see the vignette: \code{vignette("custom-ggplot2-arguments", pa
 \item{bins}{(\code{integer(1)} or \code{integer(3)}, optional)  Determines the number of bins for the histogram.
 \itemize{
 \item When the length of \code{bins} is one: The histogram bins will have a fixed size based on the \code{bins} provided.
-\item When the length of \code{bins} is three: The histogram bins are dynamically adjusted based on vector of \code{value}, \code{min}, and \code{max}.
+\item When the length of \code{bins} is three: The histogram bins are dynamically adjusted based on vector of \code{value}, \code{min},
+and \code{max}.
 Defaults to \code{c(30L, 1L, 100L)}.
 }}
 

From 5fe302b9deb694226c48a1c696408bad3531d461 Mon Sep 17 00:00:00 2001
From: Vedha Viyash <49812166+vedhav@users.noreply.github.com>
Date: Tue, 27 Feb 2024 19:51:27 +0530
Subject: [PATCH 40/62] Standardise function titles similar to what we have in
 tmc (#691)

Closes #684

Changes:

Titles now follow this format:
```
`teal` module: Function title
```

Additionally, moved the function params `alpha` and `size` to
`shared_params` as they were used in 3 places.
Note that the `tm_g_bivariate()` uses `size` param with a different
meaning. We might want to think about function arg standardization in
the future.
---
 R/tm_a_pca.R                  |  8 +-------
 R/tm_a_regression.R           | 10 +---------
 R/tm_data_table.R             |  2 +-
 R/tm_file_viewer.R            |  2 +-
 R/tm_front_page.R             |  2 +-
 R/tm_g_association.R          |  2 +-
 R/tm_g_bivariate.R            |  2 +-
 R/tm_g_distribution.R         |  2 +-
 R/tm_g_response.R             |  2 +-
 R/tm_g_scatterplot.R          |  8 +-------
 R/tm_g_scatterplotmatrix.R    |  2 +-
 R/tm_missing_data.R           |  2 +-
 R/tm_outliers.R               |  2 +-
 R/tm_t_crosstable.R           |  2 +-
 R/tm_variable_browser.R       |  2 +-
 R/utils.R                     |  9 +++++++++
 man/shared_params.Rd          | 14 ++++++++++++++
 man/tm_a_pca.Rd               | 16 +++++++++-------
 man/tm_a_regression.Rd        |  2 +-
 man/tm_data_table.Rd          |  2 +-
 man/tm_file_viewer.Rd         |  2 +-
 man/tm_front_page.Rd          |  2 +-
 man/tm_g_association.Rd       |  2 +-
 man/tm_g_bivariate.Rd         |  2 +-
 man/tm_g_distribution.Rd      |  2 +-
 man/tm_g_response.Rd          |  2 +-
 man/tm_g_scatterplot.Rd       | 16 +++++++++-------
 man/tm_g_scatterplotmatrix.Rd |  2 +-
 man/tm_missing_data.Rd        |  2 +-
 man/tm_outliers.Rd            |  2 +-
 man/tm_t_crosstable.Rd        |  2 +-
 man/tm_variable_browser.Rd    |  2 +-
 32 files changed, 69 insertions(+), 62 deletions(-)

diff --git a/R/tm_a_pca.R b/R/tm_a_pca.R
index f5cf694ff..28d180151 100644
--- a/R/tm_a_pca.R
+++ b/R/tm_a_pca.R
@@ -1,4 +1,4 @@
-#' Principal component analysis module
+#' `teal` module: Principal component analysis
 #'
 #' Module conducts principal component analysis (PCA) on a given dataset and offers different
 #' ways of visualizing the outcomes, including elbow plot, circle plot, biplot, and eigenvector plot.
@@ -9,12 +9,6 @@
 #' @inheritParams shared_params
 #' @param dat (`data_extract_spec` or `list` of multiple `data_extract_spec`)
 #'   specifying columns used to compute PCA.
-#' @param alpha (`numeric`, optional) Specifies point opacity.
-#' - If vector of `length == 1` then the plot points will have a fixed opacity.
-#' - while vector of `value`, `min`, and `max` allows dynamic adjustment.
-#' @param size (`numeric`, optional) Specifies point size.
-#' - If vector of `length == 1` then the plot point sizes will have a fixed size
-#' - while vector of `value`, `min`, and `max` allows dynamic adjustment.
 #' @param font_size (`numeric`, optional) Specifies font size.
 #' It controls the font size for plot titles, axis labels, and legends.
 #' - If vector of `length == 1` then the font sizes will have a fixed size.
diff --git a/R/tm_a_regression.R b/R/tm_a_regression.R
index e3dd0bfd3..b46514798 100644
--- a/R/tm_a_regression.R
+++ b/R/tm_a_regression.R
@@ -1,4 +1,4 @@
-#' Scatterplot and regression model
+#' `teal` module: Scatterplot and regression analysis
 #'
 #' Module for visualizing regression analysis, including scatterplots and
 #' various regression diagnostics plots.
@@ -14,14 +14,6 @@
 #' Regressor variables from an incoming dataset with filtering and selecting.
 #' @param response (`data_extract_spec` or `list` of multiple `data_extract_spec`)
 #' Response variables from an incoming dataset with filtering and selecting.
-#' @param alpha (`integer(1)` or `integer(3)`, optional) Specifies point opacity.
-#' - When the length of `alpha` is one: the plot points will have a fixed opacity.
-#' - When the length of `alpha` is three: the plot points opacity are dynamically adjusted based on
-#' vector of `value`, `min`, and `max`.
-#' @param size (`integer(1)` or `integer(3)`, optional) Specifies point size.
-#' - When the length of `size` is one: the plot point sizes will have a fixed size.
-#' - When the length of `size` is three: the plot points size are dynamically adjusted based on
-#' vector of `value`, `min`, and `max`.
 #' @param default_outlier_label (`character`, optional) The default column selected to label outliers.
 #' @param default_plot_type (`numeric`, optional) Defaults to Response vs Regressor.
 #' 1. Response vs Regressor
diff --git a/R/tm_data_table.R b/R/tm_data_table.R
index 9d6cd866c..d95342d9e 100644
--- a/R/tm_data_table.R
+++ b/R/tm_data_table.R
@@ -1,4 +1,4 @@
-#' Data table viewer module
+#' `teal` module: Data table viewer
 #'
 #' Module provides a dynamic and interactive way to view `data.frame`s in a `teal` application.
 #' It uses the `DT` package to display data tables in a paginated, searchable, and sortable format,
diff --git a/R/tm_file_viewer.R b/R/tm_file_viewer.R
index 8be167330..ad6111657 100644
--- a/R/tm_file_viewer.R
+++ b/R/tm_file_viewer.R
@@ -1,4 +1,4 @@
-#' File viewer module
+#' `teal` module: File viewer
 #'
 #' The file viewer module provides a tool to view static files.
 #' Supported formats include text formats, `PDF`, `PNG` `APNG`,
diff --git a/R/tm_front_page.R b/R/tm_front_page.R
index c10ef2bd0..028bc4673 100644
--- a/R/tm_front_page.R
+++ b/R/tm_front_page.R
@@ -1,4 +1,4 @@
-#' Front page module
+#' `teal` module: Front page
 #'
 #' Creates a simple front page for `teal` applications, displaying
 #' introductory text, tables, additional `html` or `shiny` tags, and footnotes.
diff --git a/R/tm_g_association.R b/R/tm_g_association.R
index 1ee28d45a..7697a16e9 100644
--- a/R/tm_g_association.R
+++ b/R/tm_g_association.R
@@ -1,4 +1,4 @@
-#' Stack plots of variables and show association with reference variable
+#' `teal` module: Stack plots of variables and show association with reference variable
 #'
 #' Module provides functionality for visualizing the distribution of variables and
 #' their association with a reference variable.
diff --git a/R/tm_g_bivariate.R b/R/tm_g_bivariate.R
index 99fa167f4..1abad45c2 100644
--- a/R/tm_g_bivariate.R
+++ b/R/tm_g_bivariate.R
@@ -1,4 +1,4 @@
-#' Univariate and bivariate visualizations module
+#' `teal` module: Univariate and bivariate visualizations
 #'
 #' Module enables the creation of univariate and bivariate plots,
 #' facilitating the exploration of data distributions and relationships between two variables.
diff --git a/R/tm_g_distribution.R b/R/tm_g_distribution.R
index a60d6465f..0436df5df 100644
--- a/R/tm_g_distribution.R
+++ b/R/tm_g_distribution.R
@@ -1,4 +1,4 @@
-#' Distribution analysis module
+#' `teal` module: Distribution analysis
 #'
 #' Module is designed to explore the distribution of a single variable within a given dataset.
 #' It offers several tools, such as histograms, Q-Q plots, and various statistical tests to
diff --git a/R/tm_g_response.R b/R/tm_g_response.R
index 52c221e7e..5d2b40dc1 100644
--- a/R/tm_g_response.R
+++ b/R/tm_g_response.R
@@ -1,4 +1,4 @@
-#' Response plot module
+#' `teal` module: Response plot
 #'
 #' Generates a response plot for a given `response` and `x` variables.
 #' This module allows users customize and add annotations to the plot depending
diff --git a/R/tm_g_scatterplot.R b/R/tm_g_scatterplot.R
index 2bed23a61..5c36051eb 100644
--- a/R/tm_g_scatterplot.R
+++ b/R/tm_g_scatterplot.R
@@ -1,4 +1,4 @@
-#' Scatterplot module
+#' `teal` module: Scatterplot
 #'
 #' Generates a customizable scatterplot using `ggplot2`.
 #' This module allows users to select variables for the x and y axes,
@@ -22,12 +22,6 @@
 #' Specifies the variable(s) for faceting rows.
 #' @param col_facet (`data_extract_spec` or `list` of multiple `data_extract_spec`, optional)
 #' Specifies the variable(s) for faceting columns.
-#' @param alpha (`numeric`, optional) Specifies point opacity.
-#' - If vector of `length == 1` then the plot points will have a fixed opacity.
-#' - while vector of `value`, `min`, and `max` allows dynamic adjustment.
-#' @param size (`numeric`, optional) Specifies point size.
-#' - If vector of `length == 1` then the plot point sizes will have a fixed size
-#' - while vector of `value`, `min`, and `max` allows dynamic adjustment.
 #' @param shape (`character`, optional) A character vector with the names of the
 #' shape, e.g. `c("triangle", "square", "circle")`. It defaults to `shape_names`. This is a complete list from
 #' `vignette("ggplot2-specs", package="ggplot2")`.
diff --git a/R/tm_g_scatterplotmatrix.R b/R/tm_g_scatterplotmatrix.R
index a334686cd..96b99998e 100644
--- a/R/tm_g_scatterplotmatrix.R
+++ b/R/tm_g_scatterplotmatrix.R
@@ -1,4 +1,4 @@
-#' Scatterplot matrix module
+#' `teal` module: Scatterplot matrix
 #'
 #' Generates a scatterplot matrix from selected `variables` from datasets.
 #' Each plot within the matrix represents the relationship between two variables,
diff --git a/R/tm_missing_data.R b/R/tm_missing_data.R
index ce4240ded..7273fd471 100644
--- a/R/tm_missing_data.R
+++ b/R/tm_missing_data.R
@@ -1,4 +1,4 @@
-#' Missing data analysis module
+#' `teal` module: Missing data analysis
 #'
 #' Module analyzes missing data in `data.frame`s to help users explore missing observations and
 #' gain insights into the completeness of their data.
diff --git a/R/tm_outliers.R b/R/tm_outliers.R
index 34cccf2b2..3c17565a5 100644
--- a/R/tm_outliers.R
+++ b/R/tm_outliers.R
@@ -1,4 +1,4 @@
-#' Outliers module
+#' `teal` module: Outliers analysis
 #'
 #' Module to analyze and identify outliers using different methods
 #' such as IQR, Z-score, and Percentiles, and offers visualizations including
diff --git a/R/tm_t_crosstable.R b/R/tm_t_crosstable.R
index 8fdc090e6..102c93176 100644
--- a/R/tm_t_crosstable.R
+++ b/R/tm_t_crosstable.R
@@ -1,4 +1,4 @@
-#' Cross-table module
+#' `teal` module: Cross-table
 #'
 #' Generates a simple cross-table of two variables from a dataset with custom
 #' options for showing percentages and sub-totals.
diff --git a/R/tm_variable_browser.R b/R/tm_variable_browser.R
index bc8bd03d7..384d9fb6f 100644
--- a/R/tm_variable_browser.R
+++ b/R/tm_variable_browser.R
@@ -1,4 +1,4 @@
-#' Variable browser `teal` module
+#' `teal` module: Variable browser
 #'
 #' Module provides provides a detailed summary and visualization of variable distributions
 #' for `data.frame` objects, with interactive features to customize analysis.
diff --git a/R/utils.R b/R/utils.R
index cdcb4ece7..1b78f47e7 100644
--- a/R/utils.R
+++ b/R/utils.R
@@ -26,6 +26,15 @@
 #' @param post_output (`shiny.tag`, optional) Text or UI element to be displayed after the module's output,
 #' adding context or further instructions. Elements like `shiny::helpText()` are useful.
 #'
+#' @param alpha (`integer(1)` or `integer(3)`, optional) Specifies point opacity.
+#' - When the length of `alpha` is one: the plot points will have a fixed opacity.
+#' - When the length of `alpha` is three: the plot points opacity are dynamically adjusted based on
+#' vector of `value`, `min`, and `max`.
+#' @param size (`integer(1)` or `integer(3)`, optional) Specifies point size.
+#' - When the length of `size` is one: the plot point sizes will have a fixed size.
+#' - When the length of `size` is three: the plot points size are dynamically adjusted based on
+#' vector of `value`, `min`, and `max`.
+#'
 #' @return Object of class `teal_module` to be used in `teal` applications.
 #'
 #' @name shared_params
diff --git a/man/shared_params.Rd b/man/shared_params.Rd
index 22c4ee66a..a31e7e22f 100644
--- a/man/shared_params.Rd
+++ b/man/shared_params.Rd
@@ -33,6 +33,20 @@ with text placed before the output to put the output into context. For example a
 
 \item{post_output}{(\code{shiny.tag}, optional) Text or UI element to be displayed after the module's output,
 adding context or further instructions. Elements like \code{shiny::helpText()} are useful.}
+
+\item{alpha}{(\code{integer(1)} or \code{integer(3)}, optional) Specifies point opacity.
+\itemize{
+\item When the length of \code{alpha} is one: the plot points will have a fixed opacity.
+\item When the length of \code{alpha} is three: the plot points opacity are dynamically adjusted based on
+vector of \code{value}, \code{min}, and \code{max}.
+}}
+
+\item{size}{(\code{integer(1)} or \code{integer(3)}, optional) Specifies point size.
+\itemize{
+\item When the length of \code{size} is one: the plot point sizes will have a fixed size.
+\item When the length of \code{size} is three: the plot points size are dynamically adjusted based on
+vector of \code{value}, \code{min}, and \code{max}.
+}}
 }
 \value{
 Object of class \code{teal_module} to be used in \code{teal} applications.
diff --git a/man/tm_a_pca.Rd b/man/tm_a_pca.Rd
index fd9a063e7..45161c7cf 100644
--- a/man/tm_a_pca.Rd
+++ b/man/tm_a_pca.Rd
@@ -2,7 +2,7 @@
 % Please edit documentation in R/tm_a_pca.R
 \name{tm_a_pca}
 \alias{tm_a_pca}
-\title{Principal component analysis module}
+\title{\code{teal} module: Principal component analysis}
 \usage{
 tm_a_pca(
   label = "Principal Component Analysis",
@@ -52,16 +52,18 @@ It controls the font size for plot titles, axis labels, and legends.
 \item while vector of \code{value}, \code{min}, and \code{max} allows dynamic adjustment.
 }}
 
-\item{alpha}{(\code{numeric}, optional) Specifies point opacity.
+\item{alpha}{(\code{integer(1)} or \code{integer(3)}, optional) Specifies point opacity.
 \itemize{
-\item If vector of \code{length == 1} then the plot points will have a fixed opacity.
-\item while vector of \code{value}, \code{min}, and \code{max} allows dynamic adjustment.
+\item When the length of \code{alpha} is one: the plot points will have a fixed opacity.
+\item When the length of \code{alpha} is three: the plot points opacity are dynamically adjusted based on
+vector of \code{value}, \code{min}, and \code{max}.
 }}
 
-\item{size}{(\code{numeric}, optional) Specifies point size.
+\item{size}{(\code{integer(1)} or \code{integer(3)}, optional) Specifies point size.
 \itemize{
-\item If vector of \code{length == 1} then the plot point sizes will have a fixed size
-\item while vector of \code{value}, \code{min}, and \code{max} allows dynamic adjustment.
+\item When the length of \code{size} is one: the plot point sizes will have a fixed size.
+\item When the length of \code{size} is three: the plot points size are dynamically adjusted based on
+vector of \code{value}, \code{min}, and \code{max}.
 }}
 
 \item{pre_output}{(\code{shiny.tag}, optional) Text or UI element to be displayed before the module's output,
diff --git a/man/tm_a_regression.Rd b/man/tm_a_regression.Rd
index 5d539d163..01689738f 100644
--- a/man/tm_a_regression.Rd
+++ b/man/tm_a_regression.Rd
@@ -2,7 +2,7 @@
 % Please edit documentation in R/tm_a_regression.R
 \name{tm_a_regression}
 \alias{tm_a_regression}
-\title{Scatterplot and regression model}
+\title{\code{teal} module: Scatterplot and regression analysis}
 \usage{
 tm_a_regression(
   label = "Regression Analysis",
diff --git a/man/tm_data_table.Rd b/man/tm_data_table.Rd
index 40bf5e54b..bf3c62851 100644
--- a/man/tm_data_table.Rd
+++ b/man/tm_data_table.Rd
@@ -2,7 +2,7 @@
 % Please edit documentation in R/tm_data_table.R
 \name{tm_data_table}
 \alias{tm_data_table}
-\title{Data table viewer module}
+\title{\code{teal} module: Data table viewer}
 \usage{
 tm_data_table(
   label = "Data Table",
diff --git a/man/tm_file_viewer.Rd b/man/tm_file_viewer.Rd
index 79a3476f3..8386b5917 100644
--- a/man/tm_file_viewer.Rd
+++ b/man/tm_file_viewer.Rd
@@ -2,7 +2,7 @@
 % Please edit documentation in R/tm_file_viewer.R
 \name{tm_file_viewer}
 \alias{tm_file_viewer}
-\title{File viewer module}
+\title{\code{teal} module: File viewer}
 \usage{
 tm_file_viewer(
   label = "File Viewer Module",
diff --git a/man/tm_front_page.Rd b/man/tm_front_page.Rd
index e8ca98d77..8043dc80a 100644
--- a/man/tm_front_page.Rd
+++ b/man/tm_front_page.Rd
@@ -2,7 +2,7 @@
 % Please edit documentation in R/tm_front_page.R
 \name{tm_front_page}
 \alias{tm_front_page}
-\title{Front page module}
+\title{\code{teal} module: Front page}
 \usage{
 tm_front_page(
   label = "Front page",
diff --git a/man/tm_g_association.Rd b/man/tm_g_association.Rd
index aa851556a..f7b62f3c8 100644
--- a/man/tm_g_association.Rd
+++ b/man/tm_g_association.Rd
@@ -2,7 +2,7 @@
 % Please edit documentation in R/tm_g_association.R
 \name{tm_g_association}
 \alias{tm_g_association}
-\title{Stack plots of variables and show association with reference variable}
+\title{\code{teal} module: Stack plots of variables and show association with reference variable}
 \usage{
 tm_g_association(
   label = "Association",
diff --git a/man/tm_g_bivariate.Rd b/man/tm_g_bivariate.Rd
index 6993e682b..419f965c3 100644
--- a/man/tm_g_bivariate.Rd
+++ b/man/tm_g_bivariate.Rd
@@ -2,7 +2,7 @@
 % Please edit documentation in R/tm_g_bivariate.R
 \name{tm_g_bivariate}
 \alias{tm_g_bivariate}
-\title{Univariate and bivariate visualizations module}
+\title{\code{teal} module: Univariate and bivariate visualizations}
 \usage{
 tm_g_bivariate(
   label = "Bivariate Plots",
diff --git a/man/tm_g_distribution.Rd b/man/tm_g_distribution.Rd
index a04c07016..a13227224 100644
--- a/man/tm_g_distribution.Rd
+++ b/man/tm_g_distribution.Rd
@@ -2,7 +2,7 @@
 % Please edit documentation in R/tm_g_distribution.R
 \name{tm_g_distribution}
 \alias{tm_g_distribution}
-\title{Distribution analysis module}
+\title{\code{teal} module: Distribution analysis}
 \usage{
 tm_g_distribution(
   label = "Distribution Module",
diff --git a/man/tm_g_response.Rd b/man/tm_g_response.Rd
index 51c737d52..772736fad 100644
--- a/man/tm_g_response.Rd
+++ b/man/tm_g_response.Rd
@@ -2,7 +2,7 @@
 % Please edit documentation in R/tm_g_response.R
 \name{tm_g_response}
 \alias{tm_g_response}
-\title{Response plot module}
+\title{\code{teal} module: Response plot}
 \usage{
 tm_g_response(
   label = "Response Plot",
diff --git a/man/tm_g_scatterplot.Rd b/man/tm_g_scatterplot.Rd
index 3dc11cac4..4ff8705bd 100644
--- a/man/tm_g_scatterplot.Rd
+++ b/man/tm_g_scatterplot.Rd
@@ -2,7 +2,7 @@
 % Please edit documentation in R/tm_g_scatterplot.R
 \name{tm_g_scatterplot}
 \alias{tm_g_scatterplot}
-\title{Scatterplot module}
+\title{\code{teal} module: Scatterplot}
 \usage{
 tm_g_scatterplot(
   label = "Scatterplot",
@@ -54,20 +54,22 @@ Specifies the variable(s) for faceting columns.}
 \item{plot_width}{optional, (\code{numeric}) Specifies the plot width as a three-element vector of
 \code{value}, \code{min}, and \code{max} for a slider encoding the plot width.}
 
-\item{alpha}{(\code{numeric}, optional) Specifies point opacity.
+\item{alpha}{(\code{integer(1)} or \code{integer(3)}, optional) Specifies point opacity.
 \itemize{
-\item If vector of \code{length == 1} then the plot points will have a fixed opacity.
-\item while vector of \code{value}, \code{min}, and \code{max} allows dynamic adjustment.
+\item When the length of \code{alpha} is one: the plot points will have a fixed opacity.
+\item When the length of \code{alpha} is three: the plot points opacity are dynamically adjusted based on
+vector of \code{value}, \code{min}, and \code{max}.
 }}
 
 \item{shape}{(\code{character}, optional) A character vector with the names of the
 shape, e.g. \code{c("triangle", "square", "circle")}. It defaults to \code{shape_names}. This is a complete list from
 \code{vignette("ggplot2-specs", package="ggplot2")}.}
 
-\item{size}{(\code{numeric}, optional) Specifies point size.
+\item{size}{(\code{integer(1)} or \code{integer(3)}, optional) Specifies point size.
 \itemize{
-\item If vector of \code{length == 1} then the plot point sizes will have a fixed size
-\item while vector of \code{value}, \code{min}, and \code{max} allows dynamic adjustment.
+\item When the length of \code{size} is one: the plot point sizes will have a fixed size.
+\item When the length of \code{size} is three: the plot points size are dynamically adjusted based on
+vector of \code{value}, \code{min}, and \code{max}.
 }}
 
 \item{max_deg}{(\code{integer}, optional) The maximum degree for the polynomial trend line. Must not be less than 1.}
diff --git a/man/tm_g_scatterplotmatrix.Rd b/man/tm_g_scatterplotmatrix.Rd
index 4b9ca755d..829fe01a4 100644
--- a/man/tm_g_scatterplotmatrix.Rd
+++ b/man/tm_g_scatterplotmatrix.Rd
@@ -2,7 +2,7 @@
 % Please edit documentation in R/tm_g_scatterplotmatrix.R
 \name{tm_g_scatterplotmatrix}
 \alias{tm_g_scatterplotmatrix}
-\title{Scatterplot matrix module}
+\title{\code{teal} module: Scatterplot matrix}
 \usage{
 tm_g_scatterplotmatrix(
   label = "Scatterplot Matrix",
diff --git a/man/tm_missing_data.Rd b/man/tm_missing_data.Rd
index e94ed9dfe..0ef2b28c9 100644
--- a/man/tm_missing_data.Rd
+++ b/man/tm_missing_data.Rd
@@ -2,7 +2,7 @@
 % Please edit documentation in R/tm_missing_data.R
 \name{tm_missing_data}
 \alias{tm_missing_data}
-\title{Missing data analysis module}
+\title{\code{teal} module: Missing data analysis}
 \usage{
 tm_missing_data(
   label = "Missing data",
diff --git a/man/tm_outliers.Rd b/man/tm_outliers.Rd
index 9bda163f3..2e39076a1 100644
--- a/man/tm_outliers.Rd
+++ b/man/tm_outliers.Rd
@@ -2,7 +2,7 @@
 % Please edit documentation in R/tm_outliers.R
 \name{tm_outliers}
 \alias{tm_outliers}
-\title{Outliers module}
+\title{\code{teal} module: Outliers analysis}
 \usage{
 tm_outliers(
   label = "Outliers Module",
diff --git a/man/tm_t_crosstable.Rd b/man/tm_t_crosstable.Rd
index dcbc021a9..4bc8a68a9 100644
--- a/man/tm_t_crosstable.Rd
+++ b/man/tm_t_crosstable.Rd
@@ -2,7 +2,7 @@
 % Please edit documentation in R/tm_t_crosstable.R
 \name{tm_t_crosstable}
 \alias{tm_t_crosstable}
-\title{Cross-table module}
+\title{\code{teal} module: Cross-table}
 \usage{
 tm_t_crosstable(
   label = "Cross Table",
diff --git a/man/tm_variable_browser.Rd b/man/tm_variable_browser.Rd
index c5b6d81a7..7acf170ab 100644
--- a/man/tm_variable_browser.Rd
+++ b/man/tm_variable_browser.Rd
@@ -2,7 +2,7 @@
 % Please edit documentation in R/tm_variable_browser.R
 \name{tm_variable_browser}
 \alias{tm_variable_browser}
-\title{Variable browser \code{teal} module}
+\title{\code{teal} module: Variable browser}
 \usage{
 tm_variable_browser(
   label = "Variable Browser",

From 39170940cc8ea6b84dc8a2a007922e73ad9eec89 Mon Sep 17 00:00:00 2001
From: "27856297+dependabot-preview[bot]@users.noreply.github.com"
 <27856297+dependabot-preview[bot]@users.noreply.github.com>
Date: Tue, 27 Feb 2024 15:32:20 +0000
Subject: [PATCH 41/62] [skip roxygen] [skip vbump] Roxygen Man Pages Auto
 Update

---
 man/tm_a_regression.Rd | 4 ----
 1 file changed, 4 deletions(-)

diff --git a/man/tm_a_regression.Rd b/man/tm_a_regression.Rd
index beff226a3..627734540 100644
--- a/man/tm_a_regression.Rd
+++ b/man/tm_a_regression.Rd
@@ -79,10 +79,7 @@ adding context or further instructions. Elements like \code{shiny::helpText()} a
 \item Cook's dist vs Leverage
 }}
 
-<<<<<<< HEAD
 \item{default_outlier_label}{(\code{character}, optional) The default column selected to label outliers.}
-=======
-\item{default_outlier_label}{optional, (\code{character}) The default column selected to label outliers.}
 
 \item{label_segment_threshold}{(\code{numeric(1)} or \code{numeric(3)})
 Minimum distance between label and point on the plot that triggers the creation of
@@ -99,7 +96,6 @@ It can take the following forms:
 It takes the form of \code{c(value, min, max)} and it is passed to the \code{value_min_max}
 argument in \code{teal.widgets::optionalSliderInputValMinMax}.
 }}
->>>>>>> main
 }
 \description{
 Module for visualizing regression analysis, including scatterplots and

From 804d79af0437ec2ef2f7eb442e0586d58552a74f Mon Sep 17 00:00:00 2001
From: kartikeya kirar <kirar.kartikeya1@gmail.com>
Date: Wed, 28 Feb 2024 13:03:25 +0530
Subject: [PATCH 42/62] pre-release vignettes review (#681)

PR to
https://github.com/insightsengineering/teal.modules.general/issues/640

---------

Signed-off-by: Vedha Viyash <49812166+vedhav@users.noreply.github.com>
Co-authored-by: kartikeya <kartikeya.kirar@unicle.life>
Co-authored-by: Vedha Viyash <49812166+vedhav@users.noreply.github.com>
---
 .lintr                                        |    3 +-
 R/tm_g_response.R                             |    2 -
 vignettes/images/app-teal-modules-general.png |  Bin 0 -> 490652 bytes
 .../images/app-using-association-plot.png     |  Bin 0 -> 551054 bytes
 vignettes/images/app-using-bivariate-plot.png |  Bin 0 -> 471513 bytes
 vignettes/images/app-using-cross-table.png    |  Bin 0 -> 338710 bytes
 vignettes/images/app-using-data-table.png     |  Bin 0 -> 804818 bytes
 .../images/app-using-outliers-module.png      |  Bin 0 -> 678958 bytes
 .../images/app-using-regression-plots.png     |  Bin 0 -> 755551 bytes
 vignettes/images/app-using-response-plot.png  |  Bin 0 -> 419004 bytes
 .../images/app-using-scatterplot-matrix.png   |  Bin 0 -> 614467 bytes
 vignettes/images/app-using-scatterplot.png    |  Bin 0 -> 649724 bytes
 vignettes/teal-modules-general.Rmd            |   99 +-
 vignettes/using-association-plot.Rmd          |  506 ++++----
 vignettes/using-bivariate-plot.Rmd            | 1116 +++++++++--------
 vignettes/using-cross-table.Rmd               |  163 +--
 vignettes/using-data-table.Rmd                |  119 +-
 vignettes/using-outliers-module.Rmd           |  272 ++--
 vignettes/using-regression-plots.Rmd          |  421 ++++---
 vignettes/using-response-plot.Rmd             |  635 +++++-----
 vignettes/using-scatterplot-matrix.Rmd        |  231 ++--
 vignettes/using-scatterplot.Rmd               |  620 ++++-----
 22 files changed, 2109 insertions(+), 2078 deletions(-)
 create mode 100644 vignettes/images/app-teal-modules-general.png
 create mode 100644 vignettes/images/app-using-association-plot.png
 create mode 100644 vignettes/images/app-using-bivariate-plot.png
 create mode 100644 vignettes/images/app-using-cross-table.png
 create mode 100644 vignettes/images/app-using-data-table.png
 create mode 100644 vignettes/images/app-using-outliers-module.png
 create mode 100644 vignettes/images/app-using-regression-plots.png
 create mode 100644 vignettes/images/app-using-response-plot.png
 create mode 100644 vignettes/images/app-using-scatterplot-matrix.png
 create mode 100644 vignettes/images/app-using-scatterplot.png

diff --git a/.lintr b/.lintr
index 34473d273..fff479777 100644
--- a/.lintr
+++ b/.lintr
@@ -1,5 +1,6 @@
 linters: linters_with_defaults(
   line_length_linter = line_length_linter(120),
   cyclocomp_linter = NULL,
-  object_usage_linter = NULL
+  object_usage_linter = NULL,
+  object_name_linter = object_name_linter(styles = c("snake_case", "symbols"), regexes = c(ANL = "^ANL_?[0-9]*$", ADaM = "^r?AD[A-Z]{2,3}_?[0-9]*$"))
   )
diff --git a/R/tm_g_response.R b/R/tm_g_response.R
index 5d2b40dc1..3abba6266 100644
--- a/R/tm_g_response.R
+++ b/R/tm_g_response.R
@@ -413,7 +413,6 @@ srv_g_response <- function(id,
           env = list(resp_var = resp_var)
         )
       ) %>%
-        # nolint start
         # rowf and colf will be a NULL if not set by a user
         teal.code::eval_code(
           substitute(
@@ -433,7 +432,6 @@ srv_g_response <- function(id,
             env = list(x_cl = x_cl, rowf = rowf, colf = colf)
           )
         )
-      # nolint end
 
       plot_call <- substitute(
         expr = ggplot(ANL2, aes(x = x_cl, y = ns)) +
diff --git a/vignettes/images/app-teal-modules-general.png b/vignettes/images/app-teal-modules-general.png
new file mode 100644
index 0000000000000000000000000000000000000000..e48bcc98941d265f248e456770e4f3bacff425b3
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diff --git a/vignettes/teal-modules-general.Rmd b/vignettes/teal-modules-general.Rmd
index b125e653c..594475b0c 100644
--- a/vignettes/teal-modules-general.Rmd
+++ b/vignettes/teal-modules-general.Rmd
@@ -10,25 +10,25 @@ vignette: >
 
 ### Introduction
 
-`teal` is a package that extends the `shiny` framework to build interactive GUI applications using the R programming
-language. `shiny`, and hence `teal`, are implemented to allow the building of large applications by combining small,
-decoupled modules. `teal.modules.general` is a package consisting of a set of modules that are used to build `teal`
-applications. It is "general" in the sense that the intended functions of these modules are more fundamental. This is
-in contrast to the intended functions of its sister package, `teal.modules.clinical`, which is more specialized around
-clinical data. The modules of `teal.modules.general` can be combined with modules of `teal.modules.clinical` and / or
+`teal` extends the `shiny` framework, enabling the creation of interactive GUI applications using the `R`. 
+`shiny`, and `teal`facilitate the development of extensive applications through combining small, decoupled modules. 
+The `teal.modules.general` package consist of collection of modules  essential for developing `teal` applications. 
+It is "general" in the sense that the intended functions of these modules are more fundamental. This contrasts with the more specialized focus on clinical data found in the `teal.modules.clinical` package. 
+The modules from `teal.modules.general`  can be used in conjunction with modules from `teal.modules.clinical` and / or
 other `shiny` modules to build a large `teal` / `shiny` app.
 
+
 The concepts presented here require knowledge about the core features of `teal`, specifically on how to launch a `teal`
 application and how to pass data into it. Therefore, it is highly recommended to refer to the [`README`](https://insightsengineering.github.io/teal/index.html) file and 
 the introductory [vignette](https://insightsengineering.github.io/teal/latest-tag/articles/teal.html) of the `teal` package.
 
-See also `teal.modules.clinical's` [`README`](https://insightsengineering.github.io/teal.modules.clinical/latest-tag/index.html).
+See also `teal.modules.clinical`'s [`README`](https://insightsengineering.github.io/teal.modules.clinical/latest-tag/index.html).
 
 ### Main features
 
 There are five areas of data science that `teal.modules.general` provides tools and solutions (modules) for:
 
-- viewing data in tabular form
+- viewing data in tabular formats
 - visualizing data in plots and graphs
 - viewing data and files in a directory
 - examining missing and extreme values in data
@@ -38,11 +38,13 @@ See [package functions / modules](https://insightsengineering.github.io/teal.mod
 
 ### Example application
 
-A simple application including a `tm_variable_browser` module could look like this:
+A simple application featuring the `tm_variable_browser()` module:
 ```{r, message = FALSE, results = "hide"}
+# load libraries
 library(teal.modules.general)
+library(teal.widgets)
 
-# nolint start
+# teal_data object
 data <- teal_data()
 data <- within(data, {
   ADSL <- teal.modules.general::rADSL
@@ -51,40 +53,42 @@ data <- within(data, {
 datanames <- c("ADSL", "ADTTE")
 datanames(data) <- datanames
 join_keys(data) <- default_cdisc_join_keys[datanames]
-# nolint end
 
-app <- teal::init(
-  data = data,
-  modules = teal::modules(
-    tm_variable_browser(
-      label = "Variable browser",
-      ggplot2_args = teal.widgets::ggplot2_args(
-        labs = list(subtitle = "Plot generated by Variable Browser Module")
-      ),
-    )
+# tm_variable_browser module
+tm_variable_browser_module <- tm_variable_browser(
+  label = "Variable browser",
+  ggplot2_args = ggplot2_args(
+    labs = list(subtitle = "Plot generated by Variable Browser Module")
   )
 )
+
+# initialize the app
+app <- init(
+  data = data,
+  modules = modules(tm_variable_browser_module)
+)
 ```
 
 ```{r, eval = FALSE}
 shinyApp(app$ui, app$server)
 ```
 
+<img src="images/app-teal-modules-general.png" style = "display: block; margin: 0px; width: 100%"/>
+
 Let's break the above app into pieces:
+
+1: Load the necessary libraries and data.
 ```r
 library(teal.modules.general)
+library(teal.widgets)
 ```
-The line mentioned above imports the library required for this example and loads data from within that library.
+2: Construct a `teal_data` object containing that will serve as the source of data for the `teal` app. `teal_data` not only encapsulates the data for the app, but it also houses the code required to create the data to maintain reproducibility.
 
-Now, we are building a `teal_data` object that will serve as the source of data for the teal app.
-`teal_data` not only encapsulates the data for the app, but it also houses the code required to create the data to maintain reproducibility.
-To do this, we create an empty `teal_data` object and evaluate code to produce the data within the `teal_data` object,
-so both the code and data are stored together.
+To do this, we create an empty `teal_data` object and evaluate code to produce the data within the `teal_data` object, so both the code and data are stored together.
 
 Following this, we set the `datanames` and `join_keys`.
 
 ```r
-# nolint start
 data <- teal_data()
 data <- within(data, {
   ADSL <- teal.modules.general::rADSL
@@ -93,49 +97,40 @@ data <- within(data, {
 datanames <- c("ADSL", "ADTTE")
 datanames(data) <- datanames
 join_keys(data) <- default_cdisc_join_keys[datanames]
-# nolint end
 ```
 
-There is no need to load `teal` as `teal.modules.general` already depends on it.
+3: Initialize a `teal` application with specified data and modules, in this case, the module: `tm_variable_browser`, datasets:`ADSL` and `ADTTE`.
 
-In the next step, we use `teal` to create `shiny` `ui` and `server` functions so we can launch using `shiny`. The `data`
-argument tells `teal` about the input data - the two datasets `ADSL` and `ADTTE` - and the `modules`
-argument indicates the modules included in the application. Here, we include only one - `tm_variable_browser`.
+`shiny::shinyApp()` use the `ui` and `server` component to initialize the `teal` app.
 
-```{r, results = "hide"}
-app <- teal::init(
-  data = data,
-  modules = teal::modules(
-    tm_variable_browser(
-      # module name to display in the GUI
-      label = "Variable browser",
-      # this argument takes a set of arguments to pass to ggplot2.
-      # the arguments must have the same names as its ggplot2 counterpart, e.g. `subtitle`
-      ggplot2_args = teal.widgets::ggplot2_args(
-        labs = list(subtitle = "Plot generated by Variable Browser Module")
-      ),
-    )
+
+```r
+tm_variable_browser_module <- tm_variable_browser(
+  # module name to display in the GUI
+  label = "Variable browser",
+  # this argument takes a set of arguments to pass to ggplot2.
+  # the arguments must have the same names as its ggplot2 counterpart, e.g. `subtitle`
+  ggplot2_args = ggplot2_args(
+    labs = list(subtitle = "Plot generated by Variable Browser Module")
   )
 )
-```
 
-The `shiny` function `shinyApp` used the `ui` and `server` objects to initialize the `teal` app.
+app <- init(
+  data = data,
+  modules = modules(tm_variable_browser_module)
+)
 
-```{r, eval = FALSE}
-shiny::shinyApp(app$ui, app$server)
+shinyApp(app$ui, app$server)
 ```
 
 In a `teal` app, data and modules are decoupled. In the app above:
 
 - The app developer specified the data and assigned it to the `data` argument.
 - The app developer specified the module and assigned it to the `modules` argument.
-- The `init` function took these arguments and returned a list, which can be demonstrated by running:
+- The `init` function took these arguments and returned a list containing `ui` and `server` object, which can be demonstrated by running:
 
 ```{r, indent = "     "}
 class(app)
-```
-This list contains two R objects named `ui` and `server`.
-```{r, indent = "     "}
 names(app)
 ```
 
diff --git a/vignettes/using-association-plot.Rmd b/vignettes/using-association-plot.Rmd
index 5df6c154d..c1f439e69 100644
--- a/vignettes/using-association-plot.Rmd
+++ b/vignettes/using-association-plot.Rmd
@@ -11,60 +11,33 @@ vignette: >
 
 # `teal` application to use association plot with various datasets types
 
-This vignette will guide you through 4 parts to create a teal application using
-various types of datasets inside an association plot module:
+This vignette will guide you through the four parts to create a `teal` application using various types of datasets using the association plot module `tm_g_association()`:
 
-1. Load Libraries
-2. Create data sets
-3. Create an `app` variable
-4. Run the App
+1.  Load libraries
+2.  Create data sets
+3.  Create an `app` variable
+4.  Run the app
 
-## Loading libraries
+## 1 - Load libraries
 
 ```{r echo=TRUE, message=FALSE, warning=FALSE, results="hide"}
 library(teal.modules.general) # used to create the app
 library(dplyr) # used to modify data sets
 ```
 
-## Create data sets
+## 2 - Create data sets
 
-Inside this app 5 datasets will be used
+Inside this app 4 datasets will be used
 
-1. `ADSL` A wide data set with subject data
-2. `ADSL2` A wide data set with subject data
-3. `ADRS` A long data set with response data for subjects at different time points of the study
-4. `ADTTE` A long data set with time to event data
-5. `ADLB` A long data set with lab measurements for each subject
+1.  `ADSL` A wide data set with subject data
+2.  `ADRS` A long data set with response data for subjects at different time points of the study
+3.  `ADTTE` A long data set with time to event data
+4.  `ADLB` A long data set with lab measurements for each subject
 
 ```{r echo=TRUE, message=FALSE, warning=FALSE, results="hide"}
-# nolint start
-ADSL <- teal.modules.general::rADSL
-ADSL2 <- teal.modules.general::rADSL %>%
-  mutate(TRTDUR = round(as.numeric(TRTEDTM - TRTSDTM), 1))
-ADRS <- teal.modules.general::rADRS
-ADTTE <- teal.modules.general::rADTTE
-ADLB <- teal.modules.general::rADLB %>%
-  mutate(CHGC = as.factor(case_when(
-    CHG < 1 ~ "N",
-    CHG > 1 ~ "P",
-    TRUE ~ "-"
-  )))
-# nolint end
-```
-
-## Initialize an app
-
-This is the most important section. We will use the [`teal::init`](https://insightsengineering.github.io/teal/latest-tag/reference/init) function to
-create an app. The data will be handed over using [`teal.data::cdisc_data`](https://insightsengineering.github.io/teal.data/latest-tag/reference/cdisc_data). The app
-itself will be constructed by multiple calls of `tm_g_association` using different
-combinations of data sets.
-
-```{r echo=TRUE, message=FALSE, warning=FALSE, results="hide"}
-# nolint start
 data <- teal_data()
 data <- within(data, {
-  ADSL <- teal.modules.general::rADSL
-  ADSL2 <- ADSL %>%
+  ADSL <- teal.modules.general::rADSL %>%
     mutate(TRTDUR = round(as.numeric(TRTEDTM - TRTSDTM), 1))
   ADRS <- teal.modules.general::rADRS
   ADTTE <- teal.modules.general::rADTTE
@@ -75,238 +48,257 @@ data <- within(data, {
       TRUE ~ "-"
     )))
 })
-datanames <- c("ADSL", "ADSL2", "ADRS", "ADTTE", "ADLB")
+datanames <- c("ADSL", "ADRS", "ADTTE", "ADLB")
 datanames(data) <- datanames
-jk <- default_cdisc_join_keys[datanames]
-jk_adsl2 <- jk
-names(jk_adsl2)[names(jk_adsl2) == "ADSL"] <- "ADSL2"
-jk <- c(jk, jk_adsl2)
-jk["ADSL2", "ADSL"] <- c("USUBJID", "STUDYID")
+join_keys(data) <- default_cdisc_join_keys[datanames]
+```
 
-# nolint end
+## 3 - Create an `app` variable
 
-app <- teal::init(
-  data = data,
-  modules = teal::modules(
-    # tm_g_association ----
-    modules(
-      label = "Association plot",
-      tm_g_association(
-        label = "Single wide dataset",
-        ref = teal.transform::data_extract_spec(
-          dataname = "ADSL",
-          select = select_spec(
-            label = "Select variable:",
-            choices = variable_choices(data[["ADSL"]]),
-            selected = "AGE",
-            fixed = FALSE
-          )
-        ),
-        vars = teal.transform::data_extract_spec(
-          dataname = "ADSL",
-          select = select_spec(
-            label = "Select variables:",
-            choices = variable_choices(data[["ADSL"]]),
-            selected = "BMRKR1",
-            multiple = TRUE,
-            fixed = FALSE
-          )
-        )
-      ),
-      tm_g_association(
-        label = "Two wide datasets",
-        ref = teal.transform::data_extract_spec(
-          dataname = "ADSL",
-          select = select_spec(
-            label = "Select variable:",
-            choices = variable_choices(data[["ADSL"]], c("AGE", "SEX", "STRATA1", "RACE")),
-            selected = "STRATA1",
-            multiple = FALSE,
-            fixed = FALSE
-          )
-        ),
-        vars = teal.transform::data_extract_spec(
-          dataname = "ADSL2",
-          select = select_spec(
-            label = "Select variables:",
-            choices = variable_choices(data[["ADSL2"]], c("AGE", "SEX", "RACE", "COUNTRY")),
-            selected = c("AGE", "COUNTRY", "RACE"),
-            multiple = TRUE,
-            fixed = FALSE
-          )
-        )
+This is the most important section. We will use the `teal::init()` function to create an app. The data will be handed over using `teal.data::teal_data()`. The app itself will be constructed by multiple calls of `tm_g_association()` using different combinations of data sets.
+
+```{r echo=TRUE, message=FALSE, warning=FALSE, results="hide"}
+# configuration for a single wide dataset
+mod1 <- tm_g_association(
+  label = "Single wide dataset",
+  ref = data_extract_spec(
+    dataname = "ADSL",
+    select = select_spec(
+      label = "Select variable:",
+      choices = variable_choices(data[["ADSL"]]),
+      selected = "AGE",
+      fixed = FALSE
+    )
+  ),
+  vars = data_extract_spec(
+    dataname = "ADSL",
+    select = select_spec(
+      label = "Select variables:",
+      choices = variable_choices(data[["ADSL"]]),
+      selected = "BMRKR1",
+      multiple = TRUE,
+      fixed = FALSE
+    )
+  )
+)
+
+# configuration for two wide datasets
+mod2 <- tm_g_association(
+  label = "Two wide datasets",
+  ref = data_extract_spec(
+    dataname = "ADSL",
+    select = select_spec(
+      label = "Select variable:",
+      choices = variable_choices(data[["ADSL"]], c("AGE", "SEX", "STRATA1", "RACE")),
+      selected = "STRATA1",
+      multiple = FALSE,
+      fixed = FALSE
+    )
+  ),
+  vars = data_extract_spec(
+    dataname = "ADSL",
+    select = select_spec(
+      label = "Select variables:",
+      choices = variable_choices(data[["ADSL"]], c("AGE", "SEX", "RACE", "COUNTRY")),
+      selected = c("AGE", "COUNTRY", "RACE"),
+      multiple = TRUE,
+      fixed = FALSE
+    )
+  )
+)
+
+# configuration for multiple long datasets
+mod3 <- tm_g_association(
+  label = "Multiple different long datasets",
+  ref = data_extract_spec(
+    dataname = "ADTTE",
+    select = select_spec(
+      label = "Select variables:",
+      choices = variable_choices(data[["ADTTE"]]),
+      selected = "AVAL",
+      multiple = FALSE,
+      fixed = FALSE
+    ),
+    filter = filter_spec(
+      label = "Select endpoint:",
+      vars = "PARAMCD",
+      choices = value_choices(data[["ADTTE"]], "PARAMCD", "PARAM"),
+      selected = c("PFS", "EFS"),
+      multiple = TRUE
+    )
+  ),
+  vars = data_extract_spec(
+    dataname = "ADRS",
+    reshape = TRUE,
+    select = select_spec(
+      label = "Select variable:",
+      choices = variable_choices(data[["ADRS"]], c("AVALC", "BMRKR1", "BMRKR2", "ARM")),
+      selected = "AVALC",
+      multiple = TRUE,
+      fixed = FALSE
+    ),
+    filter = list(
+      filter_spec(
+        label = "Select endpoints:",
+        vars = "PARAMCD",
+        choices = value_choices(data[["ADRS"]], "PARAMCD", "PARAM"),
+        selected = "BESRSPI",
+        multiple = TRUE
       ),
-      tm_g_association(
-        label = "Multiple different long datasets",
-        ref = teal.transform::data_extract_spec(
-          dataname = "ADTTE",
-          select = select_spec(
-            label = "Select variables:",
-            choices = variable_choices(data[["ADTTE"]]),
-            selected = "AVAL",
-            multiple = FALSE,
-            fixed = FALSE
-          ),
-          filter = teal.transform::filter_spec(
-            label = "Select endpoint:",
-            vars = "PARAMCD",
-            choices = value_choices(data[["ADTTE"]], "PARAMCD", "PARAM"),
-            selected = c("PFS", "EFS"),
-            multiple = TRUE
-          )
-        ),
-        vars = teal.transform::data_extract_spec(
-          dataname = "ADRS",
-          reshape = TRUE,
-          select = select_spec(
-            label = "Select variable:",
-            choices = variable_choices(data[["ADRS"]], c("AVALC", "BMRKR1", "BMRKR2", "ARM")),
-            selected = "AVALC",
-            multiple = TRUE,
-            fixed = FALSE
-          ),
-          filter = list(
-            filter_spec(
-              label = "Select endpoints:",
-              vars = "PARAMCD",
-              choices = value_choices(data[["ADRS"]], "PARAMCD", "PARAM"),
-              selected = "BESRSPI",
-              multiple = TRUE
-            ),
-            filter_spec(
-              label = "Select endpoints:",
-              vars = "AVISIT",
-              choices = levels(data[["ADRS"]]$AVISIT),
-              selected = "SCREENING",
-              multiple = TRUE
-            )
-          )
-        )
+      filter_spec(
+        label = "Select endpoints:",
+        vars = "AVISIT",
+        choices = levels(data[["ADRS"]]$AVISIT),
+        selected = "SCREENING",
+        multiple = TRUE
+      )
+    )
+  )
+)
+
+# configuration for wide and long datasets
+mod4 <- tm_g_association(
+  label = "Wide and long datasets",
+  ref = data_extract_spec(
+    dataname = "ADRS",
+    select = select_spec(
+      choices = variable_choices(data[["ADRS"]], c("AVAL", "AVALC")),
+      selected = "AVALC",
+      multiple = FALSE,
+      fixed = FALSE,
+      label = "Selected variable:"
+    ),
+    filter = list(
+      filter_spec(
+        vars = "PARAMCD",
+        choices = value_choices(data[["ADRS"]], "PARAMCD", "PARAM"),
+        selected = levels(data[["ADRS"]]$PARAMCD),
+        multiple = TRUE,
+        label = "Select response"
       ),
-      tm_g_association(
-        label = "Wide and long datasets",
-        ref = teal.transform::data_extract_spec(
-          dataname = "ADRS",
-          select = select_spec(
-            choices = variable_choices(data[["ADRS"]], c("AVAL", "AVALC")),
-            selected = "AVALC",
-            multiple = FALSE,
-            fixed = FALSE,
-            label = "Selected variable:"
-          ),
-          filter = list(
-            filter_spec(
-              vars = "PARAMCD",
-              choices = value_choices(data[["ADRS"]], "PARAMCD", "PARAM"),
-              selected = levels(data[["ADRS"]]$PARAMCD),
-              multiple = TRUE,
-              label = "Select response"
-            ),
-            filter_spec(
-              vars = "AVISIT",
-              choices = levels(data[["ADRS"]]$AVISIT),
-              selected = levels(data[["ADRS"]]$AVISIT),
-              multiple = TRUE,
-              label = "Select visit:"
-            )
-          )
-        ),
-        vars = teal.transform::data_extract_spec(
-          dataname = "ADSL",
-          select = select_spec(
-            choices = variable_choices(data[["ADSL"]], c("SEX", "AGE", "RACE", "COUNTRY", "BMRKR1", "STRATA1", "ARM")),
-            selected = "AGE",
-            multiple = TRUE,
-            fixed = FALSE,
-            label = "Select variable:"
-          )
-        )
+      filter_spec(
+        vars = "AVISIT",
+        choices = levels(data[["ADRS"]]$AVISIT),
+        selected = levels(data[["ADRS"]]$AVISIT),
+        multiple = TRUE,
+        label = "Select visit:"
+      )
+    )
+  ),
+  vars = data_extract_spec(
+    dataname = "ADSL",
+    select = select_spec(
+      choices = variable_choices(data[["ADSL"]], c("SEX", "AGE", "RACE", "COUNTRY", "BMRKR1", "STRATA1", "ARM")),
+      selected = "AGE",
+      multiple = TRUE,
+      fixed = FALSE,
+      label = "Select variable:"
+    )
+  )
+)
+
+# configuration for the same long dataset (same subsets)
+mod5 <- tm_g_association(
+  label = "Same long datasets (same subsets)",
+  ref = data_extract_spec(
+    dataname = "ADRS",
+    select = select_spec(
+      choices = variable_choices(data[["ADRS"]]),
+      selected = "AVALC",
+      multiple = FALSE,
+      fixed = FALSE,
+      label = "Select variable:"
+    )
+  ),
+  vars = data_extract_spec(
+    dataname = "ADRS",
+    select = select_spec(
+      choices = variable_choices(data[["ADRS"]]),
+      selected = "PARAMCD",
+      multiple = TRUE,
+      fixed = FALSE,
+      label = "Select variable:"
+    )
+  )
+)
+
+# configuration for the same long dataset (different subsets)
+mod6 <- tm_g_association(
+  label = "Same long datasets (different subsets)",
+  ref = data_extract_spec(
+    dataname = "ADLB",
+    filter = list(
+      filter_spec(
+        vars = "PARAMCD",
+        choices = value_choices(data[["ADLB"]], "PARAMCD", "PARAM"),
+        selected = levels(data[["ADLB"]]$PARAMCD)[1],
+        multiple = FALSE,
+        label = "Select lab:"
       ),
-      tm_g_association(
-        label = "Same long datasets (same subsets)",
-        ref = teal.transform::data_extract_spec(
-          dataname = "ADRS",
-          select = select_spec(
-            choices = variable_choices(data[["ADRS"]]),
-            selected = "AVALC",
-            multiple = FALSE,
-            fixed = FALSE,
-            label = "Select variable:"
-          )
-        ),
-        vars = teal.transform::data_extract_spec(
-          dataname = "ADRS",
-          select = select_spec(
-            choices = variable_choices(data[["ADRS"]]),
-            selected = "PARAMCD",
-            multiple = TRUE,
-            fixed = FALSE,
-            label = "Select variable:"
-          )
-        )
+      filter_spec(
+        vars = "AVISIT",
+        choices = levels(data[["ADLB"]]$AVISIT),
+        selected = levels(data[["ADLB"]]$AVISIT)[1],
+        multiple = FALSE,
+        label = "Select visit:"
+      )
+    ),
+    select = select_spec(
+      choices = variable_choices(data[["ADLB"]], c("AVAL", "CHG2", "PCHG2")),
+      selected = "AVAL",
+      multiple = FALSE
+    )
+  ),
+  vars = data_extract_spec(
+    dataname = "ADLB",
+    filter = list(
+      filter_spec(
+        vars = "PARAMCD",
+        choices = value_choices(data[["ADLB"]], "PARAMCD", "PARAM"),
+        selected = levels(data[["ADLB"]]$PARAMCD)[1],
+        multiple = FALSE,
+        label = "Select labs:"
       ),
-      tm_g_association(
-        label = "Same long datasets (different subsets)",
-        ref = teal.transform::data_extract_spec(
-          dataname = "ADLB",
-          filter = list(
-            filter_spec(
-              vars = "PARAMCD",
-              choices = value_choices(data[["ADLB"]], "PARAMCD", "PARAM"),
-              selected = levels(data[["ADLB"]]$PARAMCD)[1],
-              multiple = FALSE,
-              label = "Select lab:"
-            ),
-            filter_spec(
-              vars = "AVISIT",
-              choices = levels(data[["ADLB"]]$AVISIT),
-              selected = levels(data[["ADLB"]]$AVISIT)[1],
-              multiple = FALSE,
-              label = "Select visit:"
-            )
-          ),
-          select = select_spec(
-            choices = variable_choices(data[["ADLB"]], c("AVAL", "CHG2", "PCHG2")),
-            selected = "AVAL",
-            multiple = FALSE
-          )
-        ),
-        vars = teal.transform::data_extract_spec(
-          dataname = "ADLB",
-          filter = list(
-            filter_spec(
-              vars = "PARAMCD",
-              choices = value_choices(data[["ADLB"]], "PARAMCD", "PARAM"),
-              selected = levels(data[["ADLB"]]$PARAMCD)[1],
-              multiple = FALSE,
-              label = "Select labs:"
-            ),
-            filter_spec(
-              vars = "AVISIT",
-              choices = levels(data[["ADLB"]]$AVISIT),
-              selected = levels(data[["ADLB"]]$AVISIT)[1],
-              multiple = FALSE,
-              label = "Select visit:"
-            )
-          ),
-          select = select_spec(
-            choices = variable_choices(data[["ADLB"]]),
-            selected = "STRATA1",
-            multiple = TRUE
-          )
-        )
+      filter_spec(
+        vars = "AVISIT",
+        choices = levels(data[["ADLB"]]$AVISIT),
+        selected = levels(data[["ADLB"]]$AVISIT)[1],
+        multiple = FALSE,
+        label = "Select visit:"
       )
+    ),
+    select = select_spec(
+      choices = variable_choices(data[["ADLB"]]),
+      selected = "STRATA1",
+      multiple = TRUE
+    )
+  )
+)
+
+# initialize the app
+app <- init(
+  data = data,
+  modules = modules(
+    # tm_g_association ----
+    modules(
+      label = "Association plot",
+      mod1,
+      mod2,
+      mod3,
+      mod4,
+      mod5,
+      mod6
     )
   )
 )
 ```
 
-## Run the app
+## 4 - Run the app
 
-A simple `shiny::shinyApp` call will let you run the app. 
-Note that app is only displayed when running this code inside an R session.  
+A simple `shiny::shinyApp()` call will let you run the app. Note that app is only displayed when running this code inside an `R` session.
 
-```{r echo=TRUE}
+```{r, echo=TRUE, results="hide"}
 shinyApp(app$ui, app$server, options = list(height = 1024, width = 1024))
 ```
 
+<img src="images/app-teal-modules-general.png" style="display: block; margin: 0px; width: 100%"/>
diff --git a/vignettes/using-bivariate-plot.Rmd b/vignettes/using-bivariate-plot.Rmd
index 74cee6e7f..3c94cd857 100644
--- a/vignettes/using-bivariate-plot.Rmd
+++ b/vignettes/using-bivariate-plot.Rmd
@@ -11,17 +11,15 @@ vignette: >
 
 # `teal` application to use bivariate plot with various datasets types
 
-This vignette will guide you through 4 parts to create a teal application using
-various types of datasets inside an bivariate plot module:
+This vignette will guide you through the four parts to create a `teal` application using
+various types of datasets using the bivariate plot module `tm_g_bivariate()`:
 
-1. Load Libraries
+1. Load libraries
 2. Create data sets
 3. Create an `app` variable
-4. Run the App
+4. Run the app
 
-
-
-## Loading libraries
+## 1 - Load libraries
 
 ```{r echo=TRUE, message=FALSE, warning=FALSE, results="hide"}
 library(teal.modules.general) # used to create the app
@@ -29,22 +27,19 @@ library(dplyr) # used to modify data sets
 ```
 
 
-## Create data sets
+## 2 - Create data sets
 
-Inside this app 5 datasets will be used
+Inside this app 4 datasets will be used
 
 1. `ADSL` A wide data set with subject data
-2. `ADSL2` A wide data set with subject data
-3. `ADRS` A long data set with response data for subjects at different time points of the study
-4. `ADTTE` A long data set with time to event data
-5. `ADLB` A long data set with lab measurements for each subject
+2. `ADRS` A long data set with response data for subjects at different time points of the study
+3. `ADTTE` A long data set with time to event data
+4. `ADLB` A long data set with lab measurements for each subject
 
 ```{r echo=TRUE, message=FALSE, warning=FALSE, results="hide"}
-# nolint start
 data <- teal_data()
 data <- within(data, {
-  ADSL <- teal.modules.general::rADSL
-  ADSL2 <- teal.modules.general::rADSL %>%
+  ADSL <- teal.modules.general::rADSL %>%
     mutate(TRTDUR = round(as.numeric(TRTEDTM - TRTSDTM), 1))
   ADRS <- teal.modules.general::rADRS
   ADTTE <- teal.modules.general::rADTTE
@@ -55,562 +50,581 @@ data <- within(data, {
       TRUE ~ "-"
     )))
 })
-datanames <- c("ADSL", "ADSL2", "ADRS", "ADTTE", "ADLB")
+datanames <- c("ADSL", "ADRS", "ADTTE", "ADLB")
 datanames(data) <- datanames
-jk <- default_cdisc_join_keys[datanames]
-jk_adsl2 <- jk
-names(jk_adsl2)[names(jk_adsl2) == "ADSL"] <- "ADSL2"
-jk <- c(jk, jk_adsl2)
-jk["ADSL2", "ADSL"] <- c("USUBJID", "STUDYID")
-# nolint end
+join_keys(data) <- default_cdisc_join_keys[datanames]
 ```
 
-## Create an `app` variable
+## 3 - Create an `app` variable
 
-This is the most important section. We will use the [`teal::init`](https://insightsengineering.github.io/teal/latest-tag/reference/init) function to
-create an app. The data will be handed over using [`teal.data::cdisc_data`](https://insightsengineering.github.io/teal.data/latest-tag/reference/cdisc_data). The app
-itself will be constructed by multiple calls of `tm_g_bivariate` using different
+This is the most important section. We will use the `teal::init()` function to
+create an app. The data will be handed over using `teal.data::teal_data()`. The app
+itself will be constructed by multiple calls of `tm_g_bivariate()` using different
 combinations of data sets.
 
 ```{r echo=TRUE, message=FALSE, warning=FALSE, results="hide"}
-app <- teal::init(
-  data = data,
-  modules = teal::modules(
-    # tm_g_bivariate ------
-    modules(
-      label = "Bivariate plot",
-      tm_g_bivariate(
-        label = "Single wide dataset",
-        x = teal.transform::data_extract_spec(
-          dataname = "ADSL",
-          select = select_spec(
-            label = "Select variable:",
-            choices = variable_choices(data[["ADSL"]]),
-            selected = "BMRKR1",
-            fixed = FALSE
-          )
-        ),
-        y = teal.transform::data_extract_spec(
-          dataname = "ADSL",
-          select = select_spec(
-            label = "Select variable:",
-            choices = variable_choices(data[["ADSL"]]),
-            selected = "SEX",
-            multiple = FALSE,
-            fixed = FALSE
-          )
-        ),
-        row_facet = teal.transform::data_extract_spec(
-          dataname = "ADSL",
-          select = select_spec(
-            label = "Select variables:",
-            choices = variable_choices(data[["ADSL"]]),
-            selected = NULL,
-            multiple = FALSE,
-            fixed = FALSE
-          )
-        ),
-        col_facet = teal.transform::data_extract_spec(
-          dataname = "ADSL",
-          select = select_spec(
-            label = "Select variables:",
-            choices = variable_choices(data[["ADSL"]]),
-            selected = NULL,
-            multiple = FALSE,
-            fixed = FALSE
-          )
-        )
+# configuration for the single wide dataset
+mod1 <- tm_g_bivariate(
+  label = "Single wide dataset",
+  x = data_extract_spec(
+    dataname = "ADSL",
+    select = select_spec(
+      label = "Select variable:",
+      choices = variable_choices(data[["ADSL"]]),
+      selected = "BMRKR1",
+      fixed = FALSE
+    )
+  ),
+  y = data_extract_spec(
+    dataname = "ADSL",
+    select = select_spec(
+      label = "Select variable:",
+      choices = variable_choices(data[["ADSL"]]),
+      selected = "SEX",
+      multiple = FALSE,
+      fixed = FALSE
+    )
+  ),
+  row_facet = data_extract_spec(
+    dataname = "ADSL",
+    select = select_spec(
+      label = "Select variables:",
+      choices = variable_choices(data[["ADSL"]]),
+      selected = NULL,
+      multiple = FALSE,
+      fixed = FALSE
+    )
+  ),
+  col_facet = data_extract_spec(
+    dataname = "ADSL",
+    select = select_spec(
+      label = "Select variables:",
+      choices = variable_choices(data[["ADSL"]]),
+      selected = NULL,
+      multiple = FALSE,
+      fixed = FALSE
+    )
+  )
+)
+
+# configuration for the two wide datasets
+mod2 <- tm_g_bivariate(
+  label = "Two wide datasets",
+  x = data_extract_spec(
+    dataname = "ADSL",
+    select = select_spec(
+      label = "Select variable:",
+      choices = variable_choices(data[["ADSL"]], c("BMRKR1", "AGE", "SEX", "STRATA1", "RACE")),
+      selected = c("BMRKR1"),
+      multiple = FALSE
+    )
+  ),
+  y = data_extract_spec(
+    dataname = "ADSL",
+    select = select_spec(
+      label = "Select variables:",
+      choices = variable_choices(data[["ADSL"]], c("COUNTRY", "AGE", "RACE")),
+      selected = "RACE",
+      multiple = FALSE
+    )
+  ),
+  row_facet = data_extract_spec(
+    dataname = "ADSL",
+    select = select_spec(
+      label = "Select variable:",
+      choices = variable_choices(data[["ADSL"]]),
+      selected = NULL,
+      multiple = FALSE,
+      fixed = FALSE
+    )
+  ),
+  col_facet = data_extract_spec(
+    dataname = "ADSL",
+    select = select_spec(
+      label = "Select variables:",
+      choices = variable_choices(data[["ADSL"]]),
+      selected = NULL,
+      multiple = FALSE,
+      fixed = FALSE
+    )
+  )
+)
+
+# configuration for the multiple different long datasets
+mod3 <- tm_g_bivariate(
+  label = "Multiple different long datasets",
+  x = data_extract_spec(
+    dataname = "ADRS",
+    filter = filter_spec(
+      label = "Select endpoints:",
+      vars = c("PARAMCD", "AVISIT"),
+      choices = value_choices(data[["ADRS"]], c("PARAMCD", "AVISIT"), c("PARAM", "AVISIT")),
+      selected = "OVRINV - END OF INDUCTION",
+      multiple = TRUE
+    ),
+    select = select_spec(
+      choices = variable_choices(data[["ADRS"]], c("AVALC", "AVAL")),
+      selected = "AVALC",
+      multiple = FALSE
+    )
+  ),
+  y = data_extract_spec(
+    dataname = "ADTTE",
+    select = select_spec(
+      label = "Select variable:",
+      choices = variable_choices(data[["ADTTE"]], c("AVAL", "CNSR")),
+      selected = "AVAL",
+      multiple = FALSE,
+      fixed = FALSE
+    ),
+    filter = filter_spec(
+      label = "Select endpoint:",
+      vars = c("PARAMCD"),
+      choices = value_choices(data[["ADTTE"]], "PARAMCD", "PARAM"),
+      selected = "OS",
+      multiple = FALSE
+    )
+  ),
+  row_facet = data_extract_spec(
+    dataname = "ADRS",
+    filter = filter_spec(
+      label = "Select endpoints:",
+      vars = c("PARAMCD", "AVISIT"),
+      choices = value_choices(data[["ADRS"]], c("PARAMCD", "AVISIT"), c("PARAM", "AVISIT")),
+      selected = "OVRINV - SCREENING",
+      multiple = TRUE
+    ),
+    select = select_spec(
+      label = "Select variable:",
+      choices = variable_choices(data[["ADRS"]], c("SEX", "RACE", "COUNTRY", "ARM", "PARAMCD", "AVISIT")),
+      selected = "SEX",
+      multiple = FALSE,
+      fixed = FALSE
+    )
+  ),
+  col_facet = data_extract_spec(
+    dataname = "ADSL",
+    select = select_spec(
+      label = "Select variables:",
+      choices = variable_choices(data[["ADSL"]], c("SEX", "RACE")),
+      selected = NULL,
+      multiple = FALSE,
+      fixed = FALSE
+    )
+  ),
+  color_settings = TRUE,
+  color = data_extract_spec(
+    dataname = "ADSL",
+    select = select_spec(
+      choices = variable_choices(data[["ADSL"]], c("SEX", "RACE", "COUNTRY")),
+      selected = NULL,
+      multiple = FALSE,
+      fixed = FALSE,
+      label = "Select variable:"
+    )
+  ),
+  fill = data_extract_spec(
+    dataname = "ADSL",
+    select = select_spec(
+      choices = variable_choices(data[["ADSL"]], c("SEX", "RACE", "COUNTRY")),
+      selected = NULL,
+      multiple = FALSE,
+      fixed = FALSE,
+      label = "Select variable:"
+    )
+  ),
+  size = data_extract_spec(
+    dataname = "ADSL",
+    select = select_spec(
+      choices = variable_choices(data[["ADSL"]], c("AGE", "BMRKR1")),
+      selected = NULL,
+      multiple = FALSE,
+      fixed = FALSE,
+      label = "Select variable:"
+    )
+  ),
+  plot_height = c(600, 200, 2000),
+  ggtheme = "gray"
+)
+
+# configuration for the wide and long datasets
+mod4 <- tm_g_bivariate(
+  label = "Wide and long datasets",
+  x = data_extract_spec(
+    dataname = "ADRS",
+    filter = list(
+      filter_spec(
+        vars = "PARAMCD",
+        choices = value_choices(data[["ADRS"]], "PARAMCD", "PARAM"),
+        selected = levels(data[["ADRS"]]$PARAMCD)[1],
+        multiple = FALSE,
+        label = "Select response:"
       ),
-      tm_g_bivariate(
-        label = "Two wide datasets",
-        x = teal.transform::data_extract_spec(
-          dataname = "ADSL",
-          select = select_spec(
-            label = "Select variable:",
-            choices = variable_choices(data[["ADSL"]], c("BMRKR1", "AGE", "SEX", "STRATA1", "RACE")),
-            selected = c("BMRKR1"),
-            multiple = FALSE
-          )
-        ),
-        y = teal.transform::data_extract_spec(
-          dataname = "ADSL2",
-          select = select_spec(
-            label = "Select variables:",
-            choices = variable_choices(data[["ADSL2"]], c("COUNTRY", "AGE", "RACE")),
-            selected = "RACE",
-            multiple = FALSE
-          )
-        ),
-        row_facet = teal.transform::data_extract_spec(
-          dataname = "ADSL",
-          select = select_spec(
-            label = "Select variable:",
-            choices = variable_choices(data[["ADSL"]]),
-            selected = NULL,
-            multiple = FALSE,
-            fixed = FALSE
-          )
-        ),
-        col_facet = teal.transform::data_extract_spec(
-          dataname = "ADSL2",
-          select = select_spec(
-            label = "Select variables:",
-            choices = variable_choices(data[["ADSL2"]]),
-            selected = NULL,
-            multiple = FALSE,
-            fixed = FALSE
-          )
-        )
+      filter_spec(
+        vars = "AVISIT",
+        choices = levels(data[["ADRS"]]$AVISIT),
+        selected = levels(data[["ADRS"]]$AVISIT)[1],
+        multiple = FALSE,
+        label = "Select visit:"
+      )
+    ),
+    select = select_spec(
+      choices = variable_choices(data[["ADRS"]], c("AVALC", "AVAL")),
+      selected = "AVALC",
+      multiple = FALSE,
+      label = "Select variable:"
+    )
+  ),
+  y = data_extract_spec(
+    dataname = "ADSL",
+    select = select_spec(
+      choices = variable_choices(data[["ADSL"]], c("BMRKR1", "SEX", "AGE", "RACE", "COUNTRY")),
+      selected = "BMRKR1",
+      multiple = FALSE,
+      label = "Select variable:",
+      fixed = FALSE
+    )
+  ),
+  row_facet = data_extract_spec(
+    dataname = "ADRS",
+    select = select_spec(
+      choices = variable_choices(data[["ADRS"]], c("SEX", "RACE", "ARMCD", "PARAMCD")),
+      selected = "SEX",
+      multiple = FALSE,
+      label = "Select variable:"
+    )
+  ),
+  col_facet = data_extract_spec(
+    dataname = "ADRS",
+    select = select_spec(
+      choices = variable_choices(data[["ADRS"]], c("SEX", "RACE", "ARMCD", "PARAMCD", "AVISIT")),
+      selected = "ARMCD",
+      multiple = FALSE,
+      fixed = FALSE,
+      label = "Select variable:"
+    )
+  )
+)
+
+# configuration for the wide and multiple long datasets
+mod5 <- tm_g_bivariate(
+  label = "Wide and multiple long datasets",
+  x = data_extract_spec(
+    dataname = "ADRS",
+    filter = list(
+      filter_spec(
+        vars = "PARAMCD",
+        choices = value_choices(data[["ADRS"]], "PARAMCD", "PARAM"),
+        selected = levels(data[["ADRS"]]$PARAMCD)[1],
+        multiple = FALSE,
+        label = "Select response:"
       ),
-      tm_g_bivariate(
-        label = "Multiple different long datasets",
-        x = teal.transform::data_extract_spec(
-          dataname = "ADRS",
-          filter = teal.transform::filter_spec(
-            label = "Select endpoints:",
-            vars = c("PARAMCD", "AVISIT"),
-            choices = value_choices(data[["ADRS"]], c("PARAMCD", "AVISIT"), c("PARAM", "AVISIT")),
-            selected = "OVRINV - END OF INDUCTION",
-            multiple = TRUE
-          ),
-          select = select_spec(
-            choices = variable_choices(data[["ADRS"]], c("AVALC", "AVAL")),
-            selected = "AVALC",
-            multiple = FALSE
-          )
-        ),
-        y = teal.transform::data_extract_spec(
-          dataname = "ADTTE",
-          select = select_spec(
-            label = "Select variable:",
-            choices = variable_choices(data[["ADTTE"]], c("AVAL", "CNSR")),
-            selected = "AVAL",
-            multiple = FALSE,
-            fixed = FALSE
-          ),
-          filter = teal.transform::filter_spec(
-            label = "Select endpoint:",
-            vars = c("PARAMCD"),
-            choices = value_choices(data[["ADTTE"]], "PARAMCD", "PARAM"),
-            selected = "OS",
-            multiple = FALSE
-          )
-        ),
-        row_facet = teal.transform::data_extract_spec(
-          dataname = "ADRS",
-          filter = teal.transform::filter_spec(
-            label = "Select endpoints:",
-            vars = c("PARAMCD", "AVISIT"),
-            choices = value_choices(data[["ADRS"]], c("PARAMCD", "AVISIT"), c("PARAM", "AVISIT")),
-            selected = "OVRINV - SCREENING",
-            multiple = TRUE
-          ),
-          select = select_spec(
-            label = "Select variable:",
-            choices = variable_choices(data[["ADRS"]], c("SEX", "RACE", "COUNTRY", "ARM", "PARAMCD", "AVISIT")),
-            selected = "SEX",
-            multiple = FALSE,
-            fixed = FALSE
-          )
-        ),
-        col_facet = teal.transform::data_extract_spec(
-          dataname = "ADSL",
-          select = select_spec(
-            label = "Select variables:",
-            choices = variable_choices(data[["ADSL"]], c("SEX", "RACE")),
-            selected = NULL,
-            multiple = FALSE,
-            fixed = FALSE
-          )
-        ),
-        color_settings = TRUE,
-        color = teal.transform::data_extract_spec(
-          dataname = "ADSL",
-          select = select_spec(
-            choices = variable_choices(data[["ADSL"]], c("SEX", "RACE", "COUNTRY")),
-            selected = NULL,
-            multiple = FALSE,
-            fixed = FALSE,
-            label = "Select variable:"
-          )
-        ),
-        fill = teal.transform::data_extract_spec(
-          dataname = "ADSL",
-          select = select_spec(
-            choices = variable_choices(data[["ADSL"]], c("SEX", "RACE", "COUNTRY")),
-            selected = NULL,
-            multiple = FALSE,
-            fixed = FALSE,
-            label = "Select variable:"
-          )
-        ),
-        size = teal.transform::data_extract_spec(
-          dataname = "ADSL",
-          select = select_spec(
-            choices = variable_choices(data[["ADSL"]], c("AGE", "BMRKR1")),
-            selected = NULL,
-            multiple = FALSE,
-            fixed = FALSE,
-            label = "Select variable:"
-          )
-        ),
-        plot_height = c(600, 200, 2000),
-        ggtheme = "gray"
+      filter_spec(
+        vars = "AVISIT",
+        choices = levels(data[["ADRS"]]$AVISIT),
+        selected = levels(data[["ADRS"]]$AVISIT)[1],
+        multiple = FALSE,
+        label = "Select visit:"
+      )
+    ),
+    select = select_spec(
+      choices = variable_choices(data[["ADRS"]], c("AVALC", "AVAL")),
+      selected = "AVALC",
+      multiple = FALSE,
+      label = "Select variable:"
+    )
+  ),
+  y = data_extract_spec(
+    dataname = "ADSL",
+    select = select_spec(
+      choices = variable_choices(data[["ADSL"]], c("BMRKR1", "SEX", "AGE", "RACE", "COUNTRY")),
+      selected = "BMRKR1",
+      multiple = FALSE,
+      fixed = FALSE
+    )
+  ),
+  row_facet = data_extract_spec(
+    dataname = "ADLB",
+    filter = list(
+      filter_spec(
+        vars = "PARAMCD",
+        choices = value_choices(data[["ADLB"]], "PARAMCD", "PARAM"),
+        selected = levels(data[["ADLB"]]$PARAMCD)[1],
+        multiple = FALSE,
+        label = "Select measurement:"
+      ),
+      filter_spec(
+        vars = "AVISIT",
+        choices = levels(data[["ADLB"]]$AVISIT),
+        selected = levels(data[["ADLB"]]$AVISIT)[1],
+        multiple = FALSE,
+        label = "Select visit:"
+      )
+    ),
+    select = select_spec(
+      choices = "ARMCD",
+      selected = NULL,
+      multiple = FALSE,
+      fixed = FALSE,
+      label = "Select variable:"
+    )
+  ),
+  col_facet = data_extract_spec(
+    dataname = "ADSL",
+    select = select_spec(
+      choices = variable_choices(data[["ADSL"]], c("SEX", "AGE", "RACE", "COUNTRY")),
+      selected = NULL,
+      multiple = FALSE,
+      fixed = FALSE,
+      label = "Select variable:"
+    )
+  ),
+  color_settings = TRUE,
+  color = data_extract_spec(
+    dataname = "ADSL",
+    select = select_spec(
+      choices = variable_choices(data[["ADSL"]], c("SEX", "RACE", "COUNTRY")),
+      selected = NULL,
+      multiple = FALSE,
+      fixed = FALSE,
+      label = "Select variable:"
+    )
+  ),
+  fill = data_extract_spec(
+    dataname = "ADSL",
+    select = select_spec(
+      choices = variable_choices(data[["ADSL"]], c("SEX", "RACE", "COUNTRY")),
+      selected = NULL,
+      multiple = FALSE,
+      fixed = FALSE,
+      label = "Select variable:"
+    )
+  ),
+  size = data_extract_spec(
+    dataname = "ADSL",
+    select = select_spec(
+      choices = variable_choices(data[["ADSL"]], c("AGE", "BMRKR1")),
+      selected = NULL,
+      multiple = FALSE,
+      fixed = FALSE,
+      label = "Select variable:"
+    )
+  ),
+  plot_height = c(600, 200, 2000),
+  ggtheme = "gray"
+)
+
+# Configuration for the same long datasets (same subset)
+mod6 <- tm_g_bivariate(
+  label = "Same long datasets (same subset)",
+  x = data_extract_spec(
+    dataname = "ADRS",
+    select = select_spec(
+      choices = variable_choices(data[["ADRS"]], c("AVALC", "AVAL")),
+      selected = "AVALC",
+      multiple = FALSE,
+      fixed = FALSE,
+      label = "Select variable:"
+    )
+  ),
+  y = data_extract_spec(
+    dataname = "ADRS",
+    select = select_spec(
+      choices = variable_choices(data[["ADRS"]], c("SEX", "RACE", "COUNTRY", "ARMCD", "BMRKR1", "BMRKR2")),
+      selected = "BMRKR1",
+      multiple = FALSE,
+      fixed = FALSE,
+      label = "Select variable:"
+    )
+  ),
+  row_facet = data_extract_spec(
+    dataname = "ADRS",
+    select = select_spec(
+      choices = variable_choices(data[["ADRS"]], c("AVISIT", "PARAMCD")),
+      selected = "PARAMCD",
+      multiple = FALSE,
+      label = "Select variables:"
+    )
+  ),
+  col_facet = data_extract_spec(
+    dataname = "ADRS",
+    select = select_spec(
+      choices = variable_choices(data[["ADRS"]], c("AVISIT", "PARAMCD")),
+      selected = "AVISIT",
+      multiple = FALSE,
+      label = "Select variables:"
+    )
+  )
+)
+
+# Configuration for the same datasets (different subsets)
+mod7 <- tm_g_bivariate(
+  label = "Same datasets (different subsets)",
+  x = data_extract_spec(
+    dataname = "ADLB",
+    filter = list(
+      filter_spec(
+        vars = "PARAMCD",
+        choices = value_choices(data[["ADLB"]], "PARAMCD", "PARAM"),
+        selected = levels(data[["ADLB"]]$PARAMCD)[1],
+        multiple = FALSE,
+        label = "Select lab:"
       ),
-      tm_g_bivariate(
-        label = "Wide and long datasets",
-        x = teal.transform::data_extract_spec(
-          dataname = "ADRS",
-          filter = list(
-            filter_spec(
-              vars = "PARAMCD",
-              choices = value_choices(data[["ADRS"]], "PARAMCD", "PARAM"),
-              selected = levels(data[["ADRS"]]$PARAMCD)[1],
-              multiple = FALSE,
-              label = "Select response:"
-            ),
-            filter_spec(
-              vars = "AVISIT",
-              choices = levels(data[["ADRS"]]$AVISIT),
-              selected = levels(data[["ADRS"]]$AVISIT)[1],
-              multiple = FALSE,
-              label = "Select visit:"
-            )
-          ),
-          select = select_spec(
-            choices = variable_choices(data[["ADRS"]], c("AVALC", "AVAL")),
-            selected = "AVALC",
-            multiple = FALSE,
-            label = "Select variable:"
-          )
-        ),
-        y = teal.transform::data_extract_spec(
-          dataname = "ADSL",
-          select = select_spec(
-            choices = variable_choices(data[["ADSL"]], c("BMRKR1", "SEX", "AGE", "RACE", "COUNTRY")),
-            selected = "BMRKR1",
-            multiple = FALSE,
-            label = "Select variable:",
-            fixed = FALSE
-          )
-        ),
-        row_facet = teal.transform::data_extract_spec(
-          dataname = "ADRS",
-          select = select_spec(
-            choices = variable_choices(data[["ADRS"]], c("SEX", "RACE", "ARMCD", "PARAMCD")),
-            selected = "SEX",
-            multiple = FALSE,
-            label = "Select variable:"
-          )
-        ),
-        col_facet = teal.transform::data_extract_spec(
-          dataname = "ADRS",
-          select = select_spec(
-            choices = variable_choices(data[["ADRS"]], c("SEX", "RACE", "ARMCD", "PARAMCD", "AVISIT")),
-            selected = "ARMCD",
-            multiple = FALSE,
-            fixed = FALSE,
-            label = "Select variable:"
-          )
-        )
+      filter_spec(
+        vars = "AVISIT",
+        choices = levels(data[["ADLB"]]$AVISIT),
+        selected = levels(data[["ADLB"]]$AVISIT)[1],
+        multiple = FALSE,
+        label = "Select visit:"
+      )
+    ),
+    select = select_spec(
+      choices = "AVAL",
+      selected = "AVAL",
+      multiple = FALSE,
+      fixed = TRUE
+    )
+  ),
+  y = data_extract_spec(
+    dataname = "ADLB",
+    filter = list(
+      filter_spec(
+        vars = "PARAMCD",
+        choices = value_choices(data[["ADLB"]], "PARAMCD", "PARAM"),
+        selected = levels(data[["ADLB"]]$PARAMCD)[1],
+        multiple = FALSE,
+        label = "Select lab:"
       ),
-      tm_g_bivariate(
-        label = "Wide and multiple long datasets",
-        x = teal.transform::data_extract_spec(
-          dataname = "ADRS",
-          filter = list(
-            filter_spec(
-              vars = "PARAMCD",
-              choices = value_choices(data[["ADRS"]], "PARAMCD", "PARAM"),
-              selected = levels(data[["ADRS"]]$PARAMCD)[1],
-              multiple = FALSE,
-              label = "Select response:"
-            ),
-            filter_spec(
-              vars = "AVISIT",
-              choices = levels(data[["ADRS"]]$AVISIT),
-              selected = levels(data[["ADRS"]]$AVISIT)[1],
-              multiple = FALSE,
-              label = "Select visit:"
-            )
-          ),
-          select = select_spec(
-            choices = variable_choices(data[["ADRS"]], c("AVALC", "AVAL")),
-            selected = "AVALC",
-            multiple = FALSE,
-            label = "Select variable:"
-          )
-        ),
-        y = teal.transform::data_extract_spec(
-          dataname = "ADSL",
-          select = select_spec(
-            choices = variable_choices(data[["ADSL"]], c("BMRKR1", "SEX", "AGE", "RACE", "COUNTRY")),
-            selected = "BMRKR1",
-            multiple = FALSE,
-            fixed = FALSE
-          )
-        ),
-        row_facet = teal.transform::data_extract_spec(
-          dataname = "ADLB",
-          filter = list(
-            filter_spec(
-              vars = "PARAMCD",
-              choices = value_choices(data[["ADLB"]], "PARAMCD", "PARAM"),
-              selected = levels(data[["ADLB"]]$PARAMCD)[1],
-              multiple = FALSE,
-              label = "Select measurement:"
-            ),
-            filter_spec(
-              vars = "AVISIT",
-              choices = levels(data[["ADLB"]]$AVISIT),
-              selected = levels(data[["ADLB"]]$AVISIT)[1],
-              multiple = FALSE,
-              label = "Select visit:"
-            )
-          ),
-          select = select_spec(
-            choices = "ARMCD",
-            selected = NULL,
-            multiple = FALSE,
-            fixed = FALSE,
-            label = "Select variable:"
-          )
-        ),
-        col_facet = teal.transform::data_extract_spec(
-          dataname = "ADSL",
-          select = select_spec(
-            choices = variable_choices(data[["ADSL"]], c("SEX", "AGE", "RACE", "COUNTRY")),
-            selected = NULL,
-            multiple = FALSE,
-            fixed = FALSE,
-            label = "Select variable:"
-          )
-        ),
-        color_settings = TRUE,
-        color = teal.transform::data_extract_spec(
-          dataname = "ADSL",
-          select = select_spec(
-            choices = variable_choices(data[["ADSL"]], c("SEX", "RACE", "COUNTRY")),
-            selected = NULL,
-            multiple = FALSE,
-            fixed = FALSE,
-            label = "Select variable:"
-          )
-        ),
-        fill = teal.transform::data_extract_spec(
-          dataname = "ADSL",
-          select = select_spec(
-            choices = variable_choices(data[["ADSL"]], c("SEX", "RACE", "COUNTRY")),
-            selected = NULL,
-            multiple = FALSE,
-            fixed = FALSE,
-            label = "Select variable:"
-          )
-        ),
-        size = teal.transform::data_extract_spec(
-          dataname = "ADSL",
-          select = select_spec(
-            choices = variable_choices(data[["ADSL"]], c("AGE", "BMRKR1")),
-            selected = NULL,
-            multiple = FALSE,
-            fixed = FALSE,
-            label = "Select variable:"
-          )
-        ),
-        plot_height = c(600, 200, 2000),
-        ggtheme = "gray"
+      filter_spec(
+        vars = "AVISIT",
+        choices = levels(data[["ADLB"]]$AVISIT),
+        selected = levels(data[["ADLB"]]$AVISIT)[1],
+        multiple = FALSE,
+        label = "Select visit:"
+      )
+    ),
+    select = select_spec(
+      choices = "AVAL",
+      selected = "AVAL",
+      multiple = FALSE,
+      fixed = TRUE
+    )
+  ),
+  use_density = FALSE,
+  row_facet = data_extract_spec(
+    dataname = "ADLB",
+    filter = list(
+      filter_spec(
+        vars = "PARAMCD",
+        choices = value_choices(data[["ADLB"]], "PARAMCD", "PARAM"),
+        selected = levels(data[["ADLB"]]$PARAMCD)[1],
+        multiple = FALSE,
+        label = "Select lab:"
       ),
-      tm_g_bivariate(
-        label = "Same long datasets (same subset)",
-        x = teal.transform::data_extract_spec(
-          dataname = "ADRS",
-          select = select_spec(
-            choices = variable_choices(data[["ADRS"]], c("AVALC", "AVAL")),
-            selected = "AVALC",
-            multiple = FALSE,
-            fixed = FALSE,
-            label = "Select variable:"
-          )
-        ),
-        y = teal.transform::data_extract_spec(
-          dataname = "ADRS",
-          select = select_spec(
-            choices = variable_choices(data[["ADRS"]], c("SEX", "RACE", "COUNTRY", "ARMCD", "BMRKR1", "BMRKR2")),
-            selected = "BMRKR1",
-            multiple = FALSE,
-            fixed = FALSE,
-            label = "Select variable:"
-          )
-        ),
-        row_facet = teal.transform::data_extract_spec(
-          dataname = "ADRS",
-          select = select_spec(
-            choices = variable_choices(data[["ADRS"]], c("AVISIT", "PARAMCD")),
-            selected = "PARAMCD",
-            multiple = FALSE,
-            label = "Select variables:"
-          )
-        ),
-        col_facet = teal.transform::data_extract_spec(
-          dataname = "ADRS",
-          select = select_spec(
-            choices = variable_choices(data[["ADRS"]], c("AVISIT", "PARAMCD")),
-            selected = "AVISIT",
-            multiple = FALSE,
-            label = "Select variables:"
-          )
-        )
+      filter_spec(
+        vars = "AVISIT",
+        choices = levels(data[["ADLB"]]$AVISIT),
+        selected = levels(data[["ADLB"]]$AVISIT)[1],
+        multiple = FALSE,
+        label = "Select category:"
+      )
+    ),
+    select = select_spec(
+      choices = variable_choices(data[["ADLB"]], c("RACE", "SEX", "ARMCD", "ACTARMCD")),
+      selected = NULL,
+      multiple = FALSE,
+      fixed = FALSE,
+      label = "Select variable:"
+    )
+  ),
+  col_facet = data_extract_spec(
+    dataname = "ADLB",
+    filter = list(
+      filter_spec(
+        vars = "PARAMCD",
+        choices = value_choices(data[["ADLB"]], "PARAMCD", "PARAM"),
+        selected = levels(data[["ADLB"]]$PARAMCD)[1],
+        multiple = FALSE,
+        label = "Select lab:"
       ),
-      tm_g_bivariate(
-        label = "Same datasets (different subsets)",
-        x = teal.transform::data_extract_spec(
-          dataname = "ADLB",
-          filter = list(
-            filter_spec(
-              vars = "PARAMCD",
-              choices = value_choices(data[["ADLB"]], "PARAMCD", "PARAM"),
-              selected = levels(data[["ADLB"]]$PARAMCD)[1],
-              multiple = FALSE,
-              label = "Select lab:"
-            ),
-            filter_spec(
-              vars = "AVISIT",
-              choices = levels(data[["ADLB"]]$AVISIT),
-              selected = levels(data[["ADLB"]]$AVISIT)[1],
-              multiple = FALSE,
-              label = "Select visit:"
-            )
-          ),
-          select = select_spec(
-            choices = "AVAL",
-            selected = "AVAL",
-            multiple = FALSE,
-            fixed = TRUE
-          )
-        ),
-        y = teal.transform::data_extract_spec(
-          dataname = "ADLB",
-          filter = list(
-            filter_spec(
-              vars = "PARAMCD",
-              choices = value_choices(data[["ADLB"]], "PARAMCD", "PARAM"),
-              selected = levels(data[["ADLB"]]$PARAMCD)[1],
-              multiple = FALSE,
-              label = "Select lab:"
-            ),
-            filter_spec(
-              vars = "AVISIT",
-              choices = levels(data[["ADLB"]]$AVISIT),
-              selected = levels(data[["ADLB"]]$AVISIT)[1],
-              multiple = FALSE,
-              label = "Select visit:"
-            )
-          ),
-          select = select_spec(
-            choices = "AVAL",
-            selected = "AVAL",
-            multiple = FALSE,
-            fixed = TRUE
-          )
-        ),
-        use_density = FALSE,
-        row_facet = teal.transform::data_extract_spec(
-          dataname = "ADLB",
-          filter = list(
-            filter_spec(
-              vars = "PARAMCD",
-              choices = value_choices(data[["ADLB"]], "PARAMCD", "PARAM"),
-              selected = levels(data[["ADLB"]]$PARAMCD)[1],
-              multiple = FALSE,
-              label = "Select lab:"
-            ),
-            filter_spec(
-              vars = "AVISIT",
-              choices = levels(data[["ADLB"]]$AVISIT),
-              selected = levels(data[["ADLB"]]$AVISIT)[1],
-              multiple = FALSE,
-              label = "Select category:"
-            )
-          ),
-          select = select_spec(
-            choices = variable_choices(data[["ADLB"]], c("RACE", "SEX", "ARMCD", "ACTARMCD")),
-            selected = NULL,
-            multiple = FALSE,
-            fixed = FALSE,
-            label = "Select variable:"
-          )
-        ),
-        col_facet = teal.transform::data_extract_spec(
-          dataname = "ADLB",
-          filter = list(
-            filter_spec(
-              vars = "PARAMCD",
-              choices = value_choices(data[["ADLB"]], "PARAMCD", "PARAM"),
-              selected = levels(data[["ADLB"]]$PARAMCD)[1],
-              multiple = FALSE,
-              label = "Select lab:"
-            ),
-            filter_spec(
-              vars = "AVISIT",
-              choices = levels(data[["ADLB"]]$AVISIT),
-              selected = levels(data[["ADLB"]]$AVISIT)[1],
-              multiple = FALSE,
-              label = "Select category:"
-            )
-          ),
-          select = select_spec(
-            choices = variable_choices(data[["ADLB"]], c("RACE", "SEX", "ARMCD", "ACTARMCD")),
-            selected = "ARMCD",
-            multiple = FALSE,
-            fixed = FALSE,
-            label = "Select variables:"
-          )
-        ),
-        color_settings = TRUE,
-        color = teal.transform::data_extract_spec(
-          dataname = "ADSL",
-          select = select_spec(
-            choices = variable_choices(data[["ADSL"]], c("SEX", "RACE", "COUNTRY")),
-            selected = NULL,
-            multiple = FALSE,
-            fixed = FALSE,
-            label = "Select variable:"
-          )
-        ),
-        fill = teal.transform::data_extract_spec(
-          dataname = "ADSL",
-          select = select_spec(
-            choices = variable_choices(data[["ADSL"]], c("SEX", "RACE", "COUNTRY")),
-            selected = NULL,
-            multiple = FALSE,
-            fixed = FALSE,
-            label = "Select variable:"
-          )
-        ),
-        size = teal.transform::data_extract_spec(
-          dataname = "ADSL",
-          select = select_spec(
-            choices = variable_choices(data[["ADSL"]], c("AGE", "BMRKR1")),
-            selected = NULL,
-            multiple = FALSE,
-            fixed = FALSE,
-            label = "Select variable:"
-          )
-        ),
-        plot_height = c(600, 200, 2000),
-        ggtheme = "gray"
+      filter_spec(
+        vars = "AVISIT",
+        choices = levels(data[["ADLB"]]$AVISIT),
+        selected = levels(data[["ADLB"]]$AVISIT)[1],
+        multiple = FALSE,
+        label = "Select category:"
       )
+    ),
+    select = select_spec(
+      choices = variable_choices(data[["ADLB"]], c("RACE", "SEX", "ARMCD", "ACTARMCD")),
+      selected = "ARMCD",
+      multiple = FALSE,
+      fixed = FALSE,
+      label = "Select variables:"
+    )
+  ),
+  color_settings = TRUE,
+  color = data_extract_spec(
+    dataname = "ADSL",
+    select = select_spec(
+      choices = variable_choices(data[["ADSL"]], c("SEX", "RACE", "COUNTRY")),
+      selected = NULL,
+      multiple = FALSE,
+      fixed = FALSE,
+      label = "Select variable:"
+    )
+  ),
+  fill = data_extract_spec(
+    dataname = "ADSL",
+    select = select_spec(
+      choices = variable_choices(data[["ADSL"]], c("SEX", "RACE", "COUNTRY")),
+      selected = NULL,
+      multiple = FALSE,
+      fixed = FALSE,
+      label = "Select variable:"
+    )
+  ),
+  size = data_extract_spec(
+    dataname = "ADSL",
+    select = select_spec(
+      choices = variable_choices(data[["ADSL"]], c("AGE", "BMRKR1")),
+      selected = NULL,
+      multiple = FALSE,
+      fixed = FALSE,
+      label = "Select variable:"
+    )
+  ),
+  plot_height = c(600, 200, 2000),
+  ggtheme = "gray"
+)
+
+# initialize the app
+app <- init(
+  data = data,
+  modules = modules(
+    # tm_g_bivariate ------
+    modules(
+      label = "Bivariate plot",
+      mod1,
+      mod2,
+      mod3,
+      mod4,
+      mod5,
+      mod6,
+      mod7
     )
   )
 )
 ```
 
 
-## Run the app
+## 4 - Run the app
 
-A simple `shiny::shinyApp` call will let you run the app.
-Note that app is only displayed when running this code inside an R session.
+A simple `shiny::shinyApp()` call will let you run the app.
+Note that app is only displayed when running this code inside an `R` session.
 
-```{r echo=TRUE}
+```{r, echo=TRUE, results="hide"}
 shinyApp(app$ui, app$server, options = list(height = 1024, width = 1024))
 ```
+
+<img src="images/app-using-bivariate-plot.png" style = "display: block; margin: 0px; width: 100%"/>
diff --git a/vignettes/using-cross-table.Rmd b/vignettes/using-cross-table.Rmd
index 86307941a..ab21b88c0 100644
--- a/vignettes/using-cross-table.Rmd
+++ b/vignettes/using-cross-table.Rmd
@@ -11,22 +11,22 @@ vignette: >
 
 # `teal` application to use cross table with various datasets types
 
-This vignette will guide you through 4 parts to create a teal application using
-various types of datasets inside an cross table module:
+This vignette will guide you through the four parts to create a `teal` application using
+various types of datasets using the cross table module `tm_t_crosstable()`:
 
-1. Load Libraries
+1. Load libraries
 2. Create data sets
 3. Create an `app` variable
-4. Run the App
+4. Run the app
 
-## Loading libraries
+## 1 - Load libraries
 
 ```{r echo=TRUE, message=FALSE, warning=FALSE, results="hide"}
 library(teal.modules.general) # used to create the app
 library(dplyr) # used to modify data sets
 ```
 
-## Create data sets
+## 2 - Create data sets
 
 Inside this app 2 datasets will be used
 
@@ -34,7 +34,6 @@ Inside this app 2 datasets will be used
 2. `ADLB` A long data set with lab measurements for each subject
 
 ```{r echo=TRUE, message=FALSE, warning=FALSE, results="hide", echo=2:6}
-# nolint start
 data <- teal_data()
 data <- within(data, {
   ADSL <- teal.modules.general::rADSL
@@ -48,92 +47,100 @@ data <- within(data, {
 datanames <- c("ADSL", "ADLB")
 datanames(data) <- datanames
 join_keys(data) <- default_cdisc_join_keys[datanames]
-# nolint end
 ```
 
-## Create an `app` variable
+## 3 - Create an `app` variable
 
-This is the most important section. We will use the [`teal::init`](https://insightsengineering.github.io/teal/latest-tag/reference/init) function to
-create an app. The data will be handed over using [`teal.data::cdisc_data`](https://insightsengineering.github.io/teal.data/latest-tag/reference/cdisc_data). The app
-itself will be constructed by multiple calls of `tm_t_crosstable` using different
+This is the most important section. We will use the `teal::init()` function to
+create an app. The data will be handed over using `teal.data::teal_data()`. The app
+itself will be constructed by multiple calls of `tm_t_crosstable()` using different
 combinations of data sets.
 
 ```{r echo=TRUE, message=FALSE, warning=FALSE, results="hide"}
-app <- teal::init(
+# configuration for the single wide dataset
+mod1 <- tm_t_crosstable(
+  label = "Single wide dataset",
+  x = data_extract_spec(
+    "ADSL",
+    select = select_spec(
+      label = "Select variable:",
+      choices = variable_choices(data[["ADSL"]]),
+      selected = names(data[["ADSL"]])[5],
+      multiple = TRUE,
+      fixed = FALSE,
+      ordered = TRUE
+    )
+  ),
+  y = data_extract_spec(
+    "ADSL",
+    select = select_spec(
+      label = "Select variable:",
+      choices = variable_choices(data[["ADSL"]]),
+      selected = names(data[["ADSL"]])[6],
+      multiple = FALSE,
+      fixed = FALSE
+    )
+  )
+)
+
+# configuration for the same long datasets (different subsets)
+mod2 <- tm_t_crosstable(
+  label = "Same long datasets (different subsets)",
+  x = data_extract_spec(
+    dataname = "ADLB",
+    filter = filter_spec(
+      vars = "PARAMCD",
+      choices = value_choices(data[["ADLB"]], "PARAMCD", "PARAM"),
+      selected = levels(data[["ADLB"]]$PARAMCD)[1],
+      multiple = FALSE
+    ),
+    select = select_spec(
+      choices = variable_choices(data[["ADLB"]]),
+      selected = "AVISIT",
+      multiple = TRUE,
+      fixed = FALSE,
+      ordered = TRUE,
+      label = "Select variable:"
+    )
+  ),
+  y = data_extract_spec(
+    dataname = "ADLB",
+    filter = filter_spec(
+      vars = "PARAMCD",
+      choices = value_choices(data[["ADLB"]], "PARAMCD", "PARAM"),
+      selected = levels(data[["ADLB"]]$PARAMCD)[1],
+      multiple = FALSE
+    ),
+    select = select_spec(
+      choices = variable_choices(data[["ADLB"]]),
+      selected = "LOQFL",
+      multiple = FALSE,
+      fixed = FALSE,
+      label = "Select variable:"
+    )
+  )
+)
+
+# initialize the app
+app <- init(
   data = data,
-  modules = teal::modules(
+  modules = modules(
     modules(
       label = "Cross table",
-      tm_t_crosstable(
-        label = "Single wide dataset",
-        x = teal.transform::data_extract_spec(
-          "ADSL",
-          select = select_spec(
-            label = "Select variable:",
-            choices = variable_choices(data[["ADSL"]]),
-            selected = names(data[["ADSL"]])[5],
-            multiple = TRUE,
-            fixed = FALSE,
-            ordered = TRUE
-          )
-        ),
-        y = teal.transform::data_extract_spec(
-          "ADSL",
-          select = select_spec(
-            label = "Select variable:",
-            choices = variable_choices(data[["ADSL"]]),
-            selected = names(data[["ADSL"]])[6],
-            multiple = FALSE,
-            fixed = FALSE
-          )
-        )
-      ),
-      tm_t_crosstable(
-        label = "Same long datasets (different subsets)",
-        x = teal.transform::data_extract_spec(
-          dataname = "ADLB",
-          filter = teal.transform::filter_spec(
-            vars = "PARAMCD",
-            choices = value_choices(data[["ADLB"]], "PARAMCD", "PARAM"),
-            selected = levels(data[["ADLB"]]$PARAMCD)[1],
-            multiple = FALSE
-          ),
-          select = select_spec(
-            choices = variable_choices(data[["ADLB"]]),
-            selected = "AVISIT",
-            multiple = TRUE,
-            fixed = FALSE,
-            ordered = TRUE,
-            label = "Select variable:"
-          )
-        ),
-        y = teal.transform::data_extract_spec(
-          dataname = "ADLB",
-          filter = teal.transform::filter_spec(
-            vars = "PARAMCD",
-            choices = value_choices(data[["ADLB"]], "PARAMCD", "PARAM"),
-            selected = levels(data[["ADLB"]]$PARAMCD)[1],
-            multiple = FALSE
-          ),
-          select = select_spec(
-            choices = variable_choices(data[["ADLB"]]),
-            selected = "LOQFL",
-            multiple = FALSE,
-            fixed = FALSE,
-            label = "Select variable:"
-          )
-        )
-      )
+      mod1,
+      mod2
     )
   )
 )
 ```
 
-## Run the app
+## 4 - Run the app
 
-A simple `shiny::shinyApp` call will let you run the app.
-Note that app is only displayed when running this code inside an R session.
+A simple `shiny::shinyApp()` call will let you run the app.
+Note that app is only displayed when running this code inside an `R` session.
 
-```{r echo=TRUE}
+```{r, echo=TRUE, results="hide"}
 shinyApp(app$ui, app$server, options = list(height = 1024, width = 1024))
 ```
+
+<img src="images/app-using-cross-table.png" style = "display: block; margin: 0px; width: 100%"/>
diff --git a/vignettes/using-data-table.Rmd b/vignettes/using-data-table.Rmd
index 1ec5b9eac..3d0cc2516 100644
--- a/vignettes/using-data-table.Rmd
+++ b/vignettes/using-data-table.Rmd
@@ -9,23 +9,23 @@ vignette: >
   %\VignetteEncoding{UTF-8}
 ---
 
-# `teal` application to use association plot with various datasets types
+# `teal` application to display data table with various datasets types
 
-This vignette will guide you through 4 parts to create a teal application using
-various types of datasets inside a data table module:
+This vignette will guide you through the four parts to create a `teal` application using
+various types of datasets using the data table module `tm_data_table()`:
 
-1. Load Libraries
+1. Load libraries
 2. Create data sets
 3. Create an `app` variable
-4. Run the App
+4. Run the app
 
-## Loading libraries
+## 1 - Load libraries
 
 ```{r echo=TRUE, message=FALSE, warning=FALSE, results="hide"}
 library(teal.modules.general) # used to create the app
 ```
 
-## Create data sets
+## 2 - Create data sets
 
 Inside this app 3 datasets will be used
 
@@ -34,7 +34,6 @@ Inside this app 3 datasets will be used
 3. `ADLB` A long data set with lab measurements for each subject
 
 ```{r echo=TRUE, message=FALSE, warning=FALSE, results="hide"}
-# nolint start
 data <- teal_data()
 data <- within(data, {
   ADSL <- teal.modules.general::rADSL
@@ -44,67 +43,75 @@ data <- within(data, {
 datanames <- c("ADSL", "ADTTE", "ADLB")
 datanames(data) <- datanames
 join_keys(data) <- default_cdisc_join_keys[datanames]
-# nolint end
 ```
 
-## Create an `app` variable
+## 3 - Create an `app` variable
 
-This is the most important section. We will use the [`teal::init`](https://insightsengineering.github.io/teal/latest-tag/reference/init) function to
-create an app. The data will be handed over using [`teal.data::cdisc_data`](https://insightsengineering.github.io/teal.data/latest-tag/reference/cdisc_data). The app itself will be constructed by multiple calls of `tm_data_table` using different
+This is the most important section. We will use the `teal::init()` function to
+create an app. The data will be handed over using `teal.data::teal_data()`.
+The app itself will be constructed by multiple calls of `tm_data_table()` using different
 combinations of data sets.
 
 ```{r echo=TRUE, message=FALSE, warning=FALSE, results="hide"}
-app <- teal::init(
-  data = data,
-  modules = teal::modules(
-    # two-datasets example
-    tm_data_table(
-      label = "Two datasets",
-      variables_selected = list(
-        ADSL = c("STUDYID", "USUBJID", "SUBJID", "SITEID", "AGE", "SEX"),
-        ADTTE = c(
-          "STUDYID", "USUBJID", "SUBJID", "SITEID",
-          "PARAM", "PARAMCD", "ARM", "ARMCD", "AVAL", "CNSR"
-        )
-      )
-    ),
-    # subsetting or changing order of datasets
-    tm_data_table(
-      label = "Datasets order",
-      variables_selected = list(
-        ADSL = c("STUDYID", "USUBJID", "SUBJID", "SITEID", "AGE", "SEX"),
-        ADLB = c(
-          "STUDYID", "USUBJID", "SUBJID", "SITEID",
-          "PARAM", "PARAMCD", "AVISIT", "AVISITN", "AVAL", "CHG"
-        )
-      ),
-      datasets_selected = c("ADTTE", "ADLB", "ADSL")
-    ),
-    # advanced usage of DT options and extensions
-    tm_data_table(
-      label = "Advanced DT usage",
-      dt_args = list(extensions = c("Buttons", "ColReorder", "FixedHeader")),
-      dt_options = list(
-        searching = FALSE,
-        pageLength = 30,
-        lengthMenu = c(5, 15, 25, 50, 100),
-        scrollX = FALSE,
-        dom = "lBrtip",
-        buttons = c("copy", "csv", "excel", "pdf", "print"),
-        colReorder = TRUE,
-        fixedHeader = TRUE
-      )
+# configuration for the two-datasets example
+mod1 <- tm_data_table(
+  label = "Two datasets",
+  variables_selected = list(
+    ADSL = c("STUDYID", "USUBJID", "SUBJID", "SITEID", "AGE", "SEX"),
+    ADTTE = c(
+      "STUDYID", "USUBJID", "SUBJID", "SITEID",
+      "PARAM", "PARAMCD", "ARM", "ARMCD", "AVAL", "CNSR"
+    )
+  )
+)
+
+# configuration for the subsetting or changing order of datasets
+mod2 <- tm_data_table(
+  label = "Datasets order",
+  variables_selected = list(
+    ADSL = c("STUDYID", "USUBJID", "SUBJID", "SITEID", "AGE", "SEX"),
+    ADLB = c(
+      "STUDYID", "USUBJID", "SUBJID", "SITEID",
+      "PARAM", "PARAMCD", "AVISIT", "AVISITN", "AVAL", "CHG"
     )
+  ),
+  datasets_selected = c("ADTTE", "ADLB", "ADSL")
+)
+
+# configuration for the advanced usage of DT options and extensions
+mod3 <- tm_data_table(
+  label = "Advanced DT usage",
+  dt_args = list(extensions = c("Buttons", "ColReorder", "FixedHeader")),
+  dt_options = list(
+    searching = FALSE,
+    pageLength = 30,
+    lengthMenu = c(5, 15, 25, 50, 100),
+    scrollX = FALSE,
+    dom = "lBrtip",
+    buttons = c("copy", "csv", "excel", "pdf", "print"),
+    colReorder = TRUE,
+    fixedHeader = TRUE
+  )
+)
+
+# initialize the app
+app <- init(
+  data = data,
+  modules = modules(
+    mod1,
+    mod2,
+    mod3
   )
 )
 ```
 
-## Run the app
+## 4 - Run the app
 
-A simple `shiny::shinyApp` call will let you run the app. 
-Note that app is only displayed when running this code inside an R session.  
+A simple `shiny::shinyApp()` call will let you run the app. 
+Note that app is only displayed when running this code inside an `R` session.  
 
-```{r echo=TRUE}
+```{r, echo=TRUE, results="hide"}
 shinyApp(app$ui, app$server, options = list(height = 1024, width = 1024))
 ```
 
+<img src="images/app-using-data-table.png" style = "display: block; margin: 0px; width: 100%"/>
diff --git a/vignettes/using-outliers-module.Rmd b/vignettes/using-outliers-module.Rmd
index 151797aa6..59e745bde 100644
--- a/vignettes/using-outliers-module.Rmd
+++ b/vignettes/using-outliers-module.Rmd
@@ -11,31 +11,30 @@ vignette: >
 
 # `teal` application to analyze and report outliers with various datasets types.
 
-This vignette will guide you through 4 parts to create a teal application using
-various types of datasets inside the outliers module:
+This vignette will guide you through the four parts to create a `teal` application using
+various types of datasets using the outliers module `tm_outliers()`:
 
-1. Load Libraries
+1. Load libraries
 2. Create data sets
 3. Create an `app` variable
-4. Run the App
+4. Run the app
 
-## Loading libraries
+## 1 - Load libraries
 
 ```{r echo=TRUE, message=FALSE, warning=FALSE, results="hide"}
 library(teal.modules.general) # used to create the app
 library(dplyr) # used to modify data sets
 ```
 
-## Create data sets
+## 2 - Create data sets
 
-Inside this app 5 datasets will be used
+Inside this app 3 datasets will be used
 
 1. `ADSL` A wide data set with subject data
 2. `ADRS` A long data set with response data for subjects at different time points of the study
 3. `ADLB` A long data set with lab measurements for each subject
 
 ```{r echo=TRUE, message=FALSE, warning=FALSE, results="hide"}
-# nolint start
 data <- teal_data()
 data <- within(data, {
   ADSL <- teal.modules.general::rADSL
@@ -45,144 +44,155 @@ data <- within(data, {
 datanames <- c("ADSL", "ADRS", "ADLB")
 datanames(data) <- datanames
 join_keys(data) <- default_cdisc_join_keys[datanames]
-# nolint end
 ```
 
-## Create an `app` variable
+## 3 - Create an `app` variable
 
-This is the most important section. We will use the [`teal::init`](https://insightsengineering.github.io/teal/latest-tag/reference/init) function to
-create an app. The data will be handed over using [`teal.data::cdisc_data`](https://insightsengineering.github.io/teal.data/latest-tag/reference/cdisc_data). The app
-itself will be constructed by multiple calls of `tm_outliers` using different
+This is the most important section. We will use the `teal::init()` function to
+create an app. The data will be handed over using `teal.data::teal_data()`. The app
+itself will be constructed by multiple calls of `tm_outliers()` using different
 combinations of data sets.
 
 ```{r echo=TRUE, message=FALSE, warning=FALSE, results="hide"}
-app <- teal::init(
-  data = data,
-  modules = teal::modules(
-    # tm_outliers ----
-    modules(
-      label = "Outliers module",
-      tm_outliers(
-        label = "Single wide dataset",
-        outlier_var = teal.transform::data_extract_spec(
-          dataname = "ADSL",
-          select = select_spec(
-            label = "Select variable:",
-            choices = variable_choices(data[["ADSL"]], c("AGE", "BMRKR1")),
-            selected = "AGE",
-            fixed = FALSE
-          )
-        ),
-        categorical_var = teal.transform::data_extract_spec(
-          dataname = "ADSL",
-          select = select_spec(
-            label = "Select variables:",
-            choices = variable_choices(
-              data[["ADSL"]],
-              subset = names(Filter(isTRUE, sapply(data[["ADSL"]], is.factor)))
-            ),
-            selected = "RACE",
-            multiple = FALSE,
-            fixed = FALSE
-          )
-        )
+# configuration for the single wide dataset
+mod1 <- tm_outliers(
+  label = "Single wide dataset",
+  outlier_var = data_extract_spec(
+    dataname = "ADSL",
+    select = select_spec(
+      label = "Select variable:",
+      choices = variable_choices(data[["ADSL"]], c("AGE", "BMRKR1")),
+      selected = "AGE",
+      fixed = FALSE
+    )
+  ),
+  categorical_var = data_extract_spec(
+    dataname = "ADSL",
+    select = select_spec(
+      label = "Select variables:",
+      choices = variable_choices(
+        data[["ADSL"]],
+        subset = names(Filter(isTRUE, sapply(data[["ADSL"]], is.factor)))
       ),
-      tm_outliers(
-        label = "Wide and long datasets",
-        outlier_var = list(
-          teal.transform::data_extract_spec(
-            dataname = "ADSL",
-            select = select_spec(
-              label = "Select variable:",
-              choices = variable_choices(data[["ADSL"]], c("AGE", "BMRKR1")),
-              selected = "AGE",
-              fixed = FALSE
-            )
-          ),
-          teal.transform::data_extract_spec(
-            dataname = "ADLB",
-            select = select_spec(
-              label = "Select variable:",
-              choices = variable_choices(data[["ADLB"]], c("AVAL", "CHG2")),
-              selected = "AVAL",
-              multiple = FALSE,
-              fixed = FALSE
-            )
-          )
+      selected = "RACE",
+      multiple = FALSE,
+      fixed = FALSE
+    )
+  )
+)
+
+# configuration for the wide and long datasets
+mod2 <- tm_outliers(
+  label = "Wide and long datasets",
+  outlier_var = list(
+    data_extract_spec(
+      dataname = "ADSL",
+      select = select_spec(
+        label = "Select variable:",
+        choices = variable_choices(data[["ADSL"]], c("AGE", "BMRKR1")),
+        selected = "AGE",
+        fixed = FALSE
+      )
+    ),
+    data_extract_spec(
+      dataname = "ADLB",
+      select = select_spec(
+        label = "Select variable:",
+        choices = variable_choices(data[["ADLB"]], c("AVAL", "CHG2")),
+        selected = "AVAL",
+        multiple = FALSE,
+        fixed = FALSE
+      )
+    )
+  ),
+  categorical_var =
+    data_extract_spec(
+      dataname = "ADSL",
+      select = select_spec(
+        label = "Select variables:",
+        choices = variable_choices(
+          data[["ADSL"]],
+          subset = names(Filter(isTRUE, sapply(data[["ADSL"]], is.factor)))
         ),
-        categorical_var =
-          teal.transform::data_extract_spec(
-            dataname = "ADSL",
-            select = select_spec(
-              label = "Select variables:",
-              choices = variable_choices(
-                data[["ADSL"]],
-                subset = names(Filter(isTRUE, sapply(data[["ADSL"]], is.factor)))
-              ),
-              selected = "RACE",
-              multiple = FALSE,
-              fixed = FALSE
-            )
-          )
-      ),
-      tm_outliers(
-        label = "Multiple long datasets",
-        outlier_var = list(
-          teal.transform::data_extract_spec(
-            dataname = "ADRS",
-            select = select_spec(
-              label = "Select variable:",
-              choices = variable_choices(data[["ADRS"]], c("ADY", "EOSDY")),
-              selected = "ADY",
-              fixed = FALSE
-            )
-          ),
-          teal.transform::data_extract_spec(
-            dataname = "ADLB",
-            select = select_spec(
-              label = "Select variable:",
-              choices = variable_choices(data[["ADLB"]], c("AVAL", "CHG2")),
-              selected = "AVAL",
-              multiple = FALSE,
-              fixed = FALSE
-            )
-          )
+        selected = "RACE",
+        multiple = FALSE,
+        fixed = FALSE
+      )
+    )
+)
+
+# configuration for the multiple long datasets
+mod3 <- tm_outliers(
+  label = "Multiple long datasets",
+  outlier_var = list(
+    data_extract_spec(
+      dataname = "ADRS",
+      select = select_spec(
+        label = "Select variable:",
+        choices = variable_choices(data[["ADRS"]], c("ADY", "EOSDY")),
+        selected = "ADY",
+        fixed = FALSE
+      )
+    ),
+    data_extract_spec(
+      dataname = "ADLB",
+      select = select_spec(
+        label = "Select variable:",
+        choices = variable_choices(data[["ADLB"]], c("AVAL", "CHG2")),
+        selected = "AVAL",
+        multiple = FALSE,
+        fixed = FALSE
+      )
+    )
+  ),
+  categorical_var = list(
+    data_extract_spec(
+      dataname = "ADRS",
+      select = select_spec(
+        label = "Select variables:",
+        choices = variable_choices(data[["ADRS"]], c("ARM", "ACTARM")),
+        selected = "ARM",
+        multiple = FALSE,
+        fixed = FALSE
+      )
+    ),
+    data_extract_spec(
+      dataname = "ADLB",
+      select = select_spec(
+        label = "Select variables:",
+        choices = variable_choices(
+          data[["ADLB"]],
+          subset = names(Filter(isTRUE, sapply(data[["ADLB"]], is.factor)))
         ),
-        categorical_var = list(
-          teal.transform::data_extract_spec(
-            dataname = "ADRS",
-            select = select_spec(
-              label = "Select variables:",
-              choices = variable_choices(data[["ADRS"]], c("ARM", "ACTARM")),
-              selected = "ARM",
-              multiple = FALSE,
-              fixed = FALSE
-            )
-          ),
-          teal.transform::data_extract_spec(
-            dataname = "ADLB",
-            select = select_spec(
-              label = "Select variables:",
-              choices = variable_choices(
-                data[["ADLB"]],
-                subset = names(Filter(isTRUE, sapply(data[["ADLB"]], is.factor)))
-              ),
-              selected = "RACE",
-              multiple = FALSE,
-              fixed = FALSE
-            )
-          )
-        )
+        selected = "RACE",
+        multiple = FALSE,
+        fixed = FALSE
       )
     )
   )
 )
+
+# initialize the app
+app <- init(
+  data = data,
+  modules = modules(
+    # tm_outliers ----
+    modules(
+      label = "Outliers module",
+      mod1,
+      mod2,
+      mod3
+    )
+  )
+)
 ```
-## Run the app
+## 4 - Run the app
 
-A simple `shiny::shinyApp` call will let you run the app. 
-Note that app is only displayed when running this code inside an R session.  
+A simple `shiny::shinyApp()` call will let you run the app. 
+Note that app is only displayed when running this code inside an `R` session.  
 
-```{r echo=TRUE}
+```{r, echo=TRUE, results="hide"}
 shinyApp(app$ui, app$server, options = list(height = 1024, width = 1024))
 ```
+
+<img src="images/app-using-outliers-module.png" style = "display: block; margin: 0px; width: 100%"/>
diff --git a/vignettes/using-regression-plots.Rmd b/vignettes/using-regression-plots.Rmd
index 18fbed914..ea17dcee5 100644
--- a/vignettes/using-regression-plots.Rmd
+++ b/vignettes/using-regression-plots.Rmd
@@ -12,37 +12,34 @@ vignette: >
 
 # `teal` application to use regression plot with various datasets types
 
-This vignette will guide you through 4 parts to create a teal application using
-various types of datasets inside an regression plot module:
+This vignette will guide you through the four parts to create a `teal` application using
+various types of datasets using the regression plot module `tm_a_regression()`:
 
-1. Load Libraries
+1. Load libraries
 2. Create data sets
 3. Create an `app` variable
-4. Run the App
+4. Run the app
 
-## Loading libraries
+## 1 - Load libraries
 
 ```{r echo=TRUE, message=FALSE, warning=FALSE, results="hide"}
 library(teal.modules.general) # used to create the app
 library(dplyr) # used to modify data sets
 ```
 
-## Create data sets
+## 2 - Create data sets
 
-Inside this app 5 datasets will be used
+Inside this app 4 datasets will be used
 
 1. `ADSL` A wide data set with subject data
-2. `ADSL2` A wide data set with subject data
-3. `ADRS` A long data set with response data for subjects at different time points of the study
-4. `ADTTE` A long data set with time to event data
-5. `ADLB` A long data set with lab measurements for each subject
+2. `ADRS` A long data set with response data for subjects at different time points of the study
+3. `ADTTE` A long data set with time to event data
+4. `ADLB` A long data set with lab measurements for each subject
 
 ```{r echo=TRUE, message=FALSE, warning=FALSE, results="hide"}
-# nolint start
 data <- teal_data()
 data <- within(data, {
-  ADSL <- teal.modules.general::rADSL
-  ADSL2 <- teal.modules.general::rADSL %>%
+  ADSL <- teal.modules.general::rADSL %>%
     mutate(TRTDUR = round(as.numeric(TRTEDTM - TRTSDTM), 1))
   ADRS <- teal.modules.general::rADRS
   ADTTE <- teal.modules.general::rADTTE
@@ -53,216 +50,228 @@ data <- within(data, {
       TRUE ~ "-"
     )))
 })
-datanames <- c("ADSL", "ADSL2", "ADRS", "ADTTE", "ADLB")
+datanames <- c("ADSL", "ADRS", "ADTTE", "ADLB")
 datanames(data) <- datanames
-jk <- default_cdisc_join_keys[datanames]
-jk_adsl2 <- jk
-names(jk_adsl2)[names(jk_adsl2) == "ADSL"] <- "ADSL2"
-jk <- c(jk, jk_adsl2)
-jk["ADSL2", "ADSL"] <- c("USUBJID", "STUDYID")
-# nolint end
+join_keys(data) <- default_cdisc_join_keys[datanames]
 ```
 
-## Create an `app` variable
+## 3 - Create an `app` variable
 
-This is the most important section. We will use the [`teal::init`](https://insightsengineering.github.io/teal/latest-tag/reference/init) function to
-create an app. The data will be handed over using [`teal.data::cdisc_data`](https://insightsengineering.github.io/teal.data/latest-tag/reference/cdisc_data). The app
-itself will be constructed by multiple calls of `tm_a_regression` using different
+This is the most important section. We will use the `teal::init()` function to
+create an app. The data will be handed over using `teal.data::teal_data()`. The app
+itself will be constructed by multiple calls of `tm_a_regression()` using different
 combinations of data sets.
 
 ```{r echo=TRUE, message=FALSE, warning=FALSE, results="hide"}
-app <- teal::init(
-  data = data,
-  modules = teal::modules(
-    modules(
-      label = "Regression plots",
-      tm_a_regression(
-        label = "Single wide dataset",
-        response = teal.transform::data_extract_spec(
-          dataname = "ADSL",
-          select = select_spec(
-            label = "Select variable:",
-            choices = variable_choices(data[["ADSL"]], c("BMRKR1", "BMRKR2")),
-            selected = "BMRKR1",
-            multiple = FALSE,
-            fixed = FALSE
-          )
-        ),
-        regressor = teal.transform::data_extract_spec(
-          dataname = "ADSL",
-          select = select_spec(
-            label = "Select variables:",
-            choices = variable_choices(data[["ADSL"]], c("AGE", "SEX", "RACE")),
-            selected = "AGE",
-            multiple = TRUE,
-            fixed = FALSE
-          )
-        )
-      ),
-      tm_a_regression(
-        label = "Two wide datasets",
-        default_plot_type = 2,
-        response = teal.transform::data_extract_spec(
-          dataname = "ADSL",
-          select = select_spec(
-            label = "Select variable:",
-            choices = variable_choices(data[["ADSL"]], c("BMRKR1", "BMRKR2")),
-            selected = "BMRKR1",
-            multiple = FALSE,
-            fixed = FALSE
-          )
-        ),
-        regressor = teal.transform::data_extract_spec(
-          dataname = "ADSL2",
-          select = select_spec(
-            label = "Select variables:",
-            choices = variable_choices(data[["ADSL2"]], c("AGE", "SEX", "RACE")),
-            selected = c("AGE", "RACE"),
-            multiple = TRUE,
-            fixed = FALSE
-          )
-        )
+# configuration for the single wide dataset
+mod1 <- tm_a_regression(
+  label = "Single wide dataset",
+  response = data_extract_spec(
+    dataname = "ADSL",
+    select = select_spec(
+      label = "Select variable:",
+      choices = variable_choices(data[["ADSL"]], c("BMRKR1", "BMRKR2")),
+      selected = "BMRKR1",
+      multiple = FALSE,
+      fixed = FALSE
+    )
+  ),
+  regressor = data_extract_spec(
+    dataname = "ADSL",
+    select = select_spec(
+      label = "Select variables:",
+      choices = variable_choices(data[["ADSL"]], c("AGE", "SEX", "RACE")),
+      selected = "AGE",
+      multiple = TRUE,
+      fixed = FALSE
+    )
+  )
+)
+
+# configuration for the two wide datasets
+mod2 <- tm_a_regression(
+  label = "Two wide datasets",
+  default_plot_type = 2,
+  response = data_extract_spec(
+    dataname = "ADSL",
+    select = select_spec(
+      label = "Select variable:",
+      choices = variable_choices(data[["ADSL"]], c("BMRKR1", "BMRKR2")),
+      selected = "BMRKR1",
+      multiple = FALSE,
+      fixed = FALSE
+    )
+  ),
+  regressor = data_extract_spec(
+    dataname = "ADSL",
+    select = select_spec(
+      label = "Select variables:",
+      choices = variable_choices(data[["ADSL"]], c("AGE", "SEX", "RACE")),
+      selected = c("AGE", "RACE"),
+      multiple = TRUE,
+      fixed = FALSE
+    )
+  )
+)
+
+# configuration for the same long datasets (same subset)
+mod3 <- tm_a_regression(
+  label = "Same long datasets (same subset)",
+  default_plot_type = 2,
+  response = data_extract_spec(
+    dataname = "ADTTE",
+    select = select_spec(
+      label = "Select variable:",
+      choices = variable_choices(data[["ADTTE"]], c("AVAL", "CNSR")),
+      selected = "AVAL",
+      multiple = FALSE,
+      fixed = FALSE
+    ),
+    filter = filter_spec(
+      label = "Select parameter:",
+      vars = "PARAMCD",
+      choices = value_choices(data[["ADTTE"]], "PARAMCD", "PARAM"),
+      selected = "PFS",
+      multiple = FALSE
+    )
+  ),
+  regressor = data_extract_spec(
+    dataname = "ADTTE",
+    select = select_spec(
+      label = "Select variable:",
+      choices = variable_choices(data[["ADTTE"]], c("AGE", "CNSR", "SEX")),
+      selected = c("AGE", "CNSR", "SEX"),
+      multiple = TRUE
+    ),
+    filter = filter_spec(
+      label = "Select parameter:",
+      vars = "PARAMCD",
+      choices = value_choices(data[["ADTTE"]], "PARAMCD", "PARAM"),
+      selected = "PFS",
+      multiple = FALSE
+    )
+  )
+)
+
+# configuration for the wide and long datasets
+mod4 <- tm_a_regression(
+  label = "Wide and long datasets",
+  response = data_extract_spec(
+    dataname = "ADLB",
+    filter = list(
+      filter_spec(
+        vars = "PARAMCD",
+        choices = value_choices(data[["ADLB"]], "PARAMCD", "PARAM"),
+        selected = levels(data[["ADLB"]]$PARAMCD)[2],
+        multiple = TRUE,
+        label = "Select measurement:"
       ),
-      tm_a_regression(
-        label = "Same long datasets (same subset)",
-        default_plot_type = 2,
-        response = teal.transform::data_extract_spec(
-          dataname = "ADTTE",
-          select = select_spec(
-            label = "Select variable:",
-            choices = variable_choices(data[["ADTTE"]], c("AVAL", "CNSR")),
-            selected = "AVAL",
-            multiple = FALSE,
-            fixed = FALSE
-          ),
-          filter = teal.transform::filter_spec(
-            label = "Select parameter:",
-            vars = "PARAMCD",
-            choices = value_choices(data[["ADTTE"]], "PARAMCD", "PARAM"),
-            selected = "PFS",
-            multiple = FALSE
-          )
-        ),
-        regressor = teal.transform::data_extract_spec(
-          dataname = "ADTTE",
-          select = select_spec(
-            label = "Select variable:",
-            choices = variable_choices(data[["ADTTE"]], c("AGE", "CNSR", "SEX")),
-            selected = c("AGE", "CNSR", "SEX"),
-            multiple = TRUE
-          ),
-          filter = teal.transform::filter_spec(
-            label = "Select parameter:",
-            vars = "PARAMCD",
-            choices = value_choices(data[["ADTTE"]], "PARAMCD", "PARAM"),
-            selected = "PFS",
-            multiple = FALSE
-          )
-        )
+      filter_spec(
+        vars = "AVISIT",
+        choices = levels(data[["ADLB"]]$AVISIT),
+        selected = levels(data[["ADLB"]]$AVISIT)[2],
+        multiple = TRUE,
+        label = "Select visit:"
+      )
+    ),
+    select = select_spec(
+      label = "Select variable:",
+      choices = "AVAL",
+      selected = "AVAL",
+      multiple = FALSE,
+      fixed = TRUE
+    )
+  ),
+  regressor = data_extract_spec(
+    dataname = "ADSL",
+    select = select_spec(
+      label = "Select variables:",
+      choices = variable_choices(data[["ADSL"]], c("BMRKR1", "BMRKR2", "AGE")),
+      selected = "AGE",
+      multiple = TRUE,
+      fixed = FALSE
+    )
+  )
+)
+
+# configuration for the same long datasets (different subsets)
+mod5 <- tm_a_regression(
+  label = "Same long datasets (different subsets)",
+  default_plot_type = 2,
+  response = data_extract_spec(
+    dataname = "ADLB",
+    filter = list(
+      filter_spec(
+        vars = "PARAMCD",
+        choices = value_choices(data[["ADLB"]], "PARAMCD", "PARAM"),
+        selected = levels(data[["ADLB"]]$PARAMCD)[1],
+        multiple = TRUE,
+        label = "Select lab:"
       ),
-      tm_a_regression(
-        label = "Wide and long datasets",
-        response = teal.transform::data_extract_spec(
-          dataname = "ADLB",
-          filter = list(
-            filter_spec(
-              vars = "PARAMCD",
-              choices = value_choices(data[["ADLB"]], "PARAMCD", "PARAM"),
-              selected = levels(data[["ADLB"]]$PARAMCD)[2],
-              multiple = TRUE,
-              label = "Select measurement:"
-            ),
-            filter_spec(
-              vars = "AVISIT",
-              choices = levels(data[["ADLB"]]$AVISIT),
-              selected = levels(data[["ADLB"]]$AVISIT)[2],
-              multiple = TRUE,
-              label = "Select visit:"
-            )
-          ),
-          select = select_spec(
-            label = "Select variable:",
-            choices = "AVAL",
-            selected = "AVAL",
-            multiple = FALSE,
-            fixed = TRUE
-          )
-        ),
-        regressor = teal.transform::data_extract_spec(
-          dataname = "ADSL",
-          select = select_spec(
-            label = "Select variables:",
-            choices = variable_choices(data[["ADSL"]], c("BMRKR1", "BMRKR2", "AGE")),
-            selected = "AGE",
-            multiple = TRUE,
-            fixed = FALSE
-          )
-        )
+      filter_spec(
+        vars = "AVISIT",
+        choices = levels(data[["ADLB"]]$AVISIT),
+        selected = levels(data[["ADLB"]]$AVISIT)[1],
+        multiple = TRUE,
+        label = "Select visit:"
+      )
+    ),
+    select = select_spec(
+      choices = "AVAL",
+      selected = "AVAL",
+      multiple = FALSE,
+      fixed = TRUE
+    )
+  ),
+  regressor = data_extract_spec(
+    dataname = "ADLB",
+    filter = list(
+      filter_spec(
+        vars = "PARAMCD",
+        choices = value_choices(data[["ADLB"]], "PARAMCD", "PARAM"),
+        selected = levels(data[["ADLB"]]$PARAMCD)[1],
+        multiple = FALSE,
+        label = "Select labs:"
       ),
-      tm_a_regression(
-        label = "Same long datasets (different subsets)",
-        default_plot_type = 2,
-        response = teal.transform::data_extract_spec(
-          dataname = "ADLB",
-          filter = list(
-            filter_spec(
-              vars = "PARAMCD",
-              choices = value_choices(data[["ADLB"]], "PARAMCD", "PARAM"),
-              selected = levels(data[["ADLB"]]$PARAMCD)[1],
-              multiple = TRUE,
-              label = "Select lab:"
-            ),
-            filter_spec(
-              vars = "AVISIT",
-              choices = levels(data[["ADLB"]]$AVISIT),
-              selected = levels(data[["ADLB"]]$AVISIT)[1],
-              multiple = TRUE,
-              label = "Select visit:"
-            )
-          ),
-          select = select_spec(
-            choices = "AVAL",
-            selected = "AVAL",
-            multiple = FALSE,
-            fixed = TRUE
-          )
-        ),
-        regressor = teal.transform::data_extract_spec(
-          dataname = "ADLB",
-          filter = list(
-            filter_spec(
-              vars = "PARAMCD",
-              choices = value_choices(data[["ADLB"]], "PARAMCD", "PARAM"),
-              selected = levels(data[["ADLB"]]$PARAMCD)[1],
-              multiple = FALSE,
-              label = "Select labs:"
-            ),
-            filter_spec(
-              vars = "AVISIT",
-              choices = levels(data[["ADLB"]]$AVISIT),
-              selected = levels(data[["ADLB"]]$AVISIT)[1],
-              multiple = FALSE,
-              label = "Select visit:"
-            )
-          ),
-          select = select_spec(
-            choices = variable_choices(data[["ADLB"]], c("AVAL", "AGE", "BMRKR1", "BMRKR2", "SEX", "ARM")),
-            selected = c("AVAL", "BMRKR1"),
-            multiple = TRUE
-          )
-        )
+      filter_spec(
+        vars = "AVISIT",
+        choices = levels(data[["ADLB"]]$AVISIT),
+        selected = levels(data[["ADLB"]]$AVISIT)[1],
+        multiple = FALSE,
+        label = "Select visit:"
       )
+    ),
+    select = select_spec(
+      choices = variable_choices(data[["ADLB"]], c("AVAL", "AGE", "BMRKR1", "BMRKR2", "SEX", "ARM")),
+      selected = c("AVAL", "BMRKR1"),
+      multiple = TRUE
+    )
+  )
+)
+
+# initialize the app
+app <- init(
+  data = data,
+  modules = modules(
+    modules(
+      label = "Regression plots",
+      mod1,
+      mod2,
+      mod3,
+      mod4,
+      mod5
     )
   )
 )
 ```
 
-## Run the app
+## 4 - Run the app
 
-A simple `shiny::shinyApp` call will let you run the app.
-Note that app is only displayed when running this code inside an R session.
+A simple `shiny::shinyApp()` call will let you run the app.
+Note that app is only displayed when running this code inside an `R` session.
 
-```{r echo=TRUE}
+```{r, echo=TRUE, results="hide"}
 shinyApp(app$ui, app$server, options = list(height = 1024, width = 1024))
 ```
 
+<img src="images/app-using-regression-plots.png" style = "display: block; margin: 0px; width: 100%"/>
diff --git a/vignettes/using-response-plot.Rmd b/vignettes/using-response-plot.Rmd
index e9af17c4b..7eef800d9 100644
--- a/vignettes/using-response-plot.Rmd
+++ b/vignettes/using-response-plot.Rmd
@@ -11,37 +11,34 @@ vignette: >
 
 # `teal` application to use response plot with various datasets types
 
-This vignette will guide you through 4 parts to create a teal application using
-various types of datasets inside an response plot module:
+This vignette will guide you through the four parts to create a `teal` application using
+various types of datasets using the response plot module `tm_g_response()`:
 
-1. Load Libraries
+1. Load libraries
 2. Create data sets
 3. Create an `app` variable
-4. Run the App
+4. Run the app
 
-## Loading libraries
+## 1 - Load libraries
 
 ```{r echo=TRUE, message=FALSE, warning=FALSE, results="hide"}
 library(teal.modules.general) # used to create the app
 library(dplyr) # used to modify data sets
 ```
 
-## Create data sets
+## 2 - Create data sets
 
-Inside this app 5 datasets will be used
+Inside this app 4 datasets will be used
 
 1. `ADSL` A wide data set with subject data
-2. `ADSL2` A wide data set with subject data
-3. `ADRS` A long data set with response data for subjects at different time points of the study
-4. `ADTTE` A long data set with time to event data
-5. `ADLB` A long data set with lab measurements for each subject
+2. `ADRS` A long data set with response data for subjects at different time points of the study
+3. `ADTTE` A long data set with time to event data
+4. `ADLB` A long data set with lab measurements for each subject
 
 ```{r echo=TRUE, message=FALSE, warning=FALSE, results="hide"}
-# nolint start
 data <- teal_data()
 data <- within(data, {
-  ADSL <- teal.modules.general::rADSL
-  ADSL2 <- teal.modules.general::rADSL %>%
+  ADSL <- teal.modules.general::rADSL %>%
     mutate(TRTDUR = round(as.numeric(TRTEDTM - TRTSDTM), 1))
   ADRS <- teal.modules.general::rADRS
   ADTTE <- teal.modules.general::rADTTE
@@ -52,324 +49,338 @@ data <- within(data, {
       TRUE ~ "-"
     )))
 })
-datanames <- c("ADSL", "ADSL2", "ADRS", "ADTTE", "ADLB")
+datanames <- c("ADSL", "ADRS", "ADTTE", "ADLB")
 datanames(data) <- datanames
-jk <- default_cdisc_join_keys[datanames]
-jk_adsl2 <- jk
-names(jk_adsl2)[names(jk_adsl2) == "ADSL"] <- "ADSL2"
-jk <- c(jk, jk_adsl2)
-jk["ADSL2", "ADSL"] <- c("USUBJID", "STUDYID")
-# nolint end
+join_keys(data) <- default_cdisc_join_keys[datanames]
 ```
 
-## Create an `app` variable
+## 3 - Create an `app` variable
 
-This is the most important section. We will use the [`teal::init`](https://insightsengineering.github.io/teal/latest-tag/reference/init) function to
-create an app. The data will be handed over using [`teal.data::cdisc_data`](https://insightsengineering.github.io/teal.data/latest-tag/reference/cdisc_data). The app
-itself will be constructed by multiple calls of `tm_g_response` using different
+This is the most important section. We will use the `teal::init()` function to
+create an app. The data will be handed over using `teal.data::teal_data()`. The app
+itself will be constructed by multiple calls of `tm_g_response()` using different
 combinations of data sets.
 
 ```{r echo=TRUE, message=FALSE, warning=FALSE, results="hide"}
-app <- teal::init(
-  data = data,
-  modules = teal::modules(
-    modules(
-      label = "Response plot",
-      tm_g_response(
-        label = "Single wide dataset",
-        response = teal.transform::data_extract_spec(
-          dataname = "ADSL",
-          select = select_spec(
-            label = "Select variable:",
-            choices = variable_choices(data[["ADSL"]], c("BMRKR2", "ITTFL", "BEP01FL")),
-            selected = "BMRKR2",
-            multiple = FALSE,
-            fixed = FALSE
-          )
-        ),
-        x = teal.transform::data_extract_spec(
-          dataname = "ADSL",
-          select = select_spec(
-            label = "Select variable:",
-            choices = variable_choices(data[["ADSL"]], c("SEX", "RACE", "COUNTRY", "ARMCD", "STRATA1")),
-            selected = "ARMCD",
-            multiple = FALSE,
-            fixed = FALSE
-          )
-        )
+# configuration for the single wide dataset
+mod1 <- tm_g_response(
+  label = "Single wide dataset",
+  response = data_extract_spec(
+    dataname = "ADSL",
+    select = select_spec(
+      label = "Select variable:",
+      choices = variable_choices(data[["ADSL"]], c("BMRKR2", "ITTFL", "BEP01FL")),
+      selected = "BMRKR2",
+      multiple = FALSE,
+      fixed = FALSE
+    )
+  ),
+  x = data_extract_spec(
+    dataname = "ADSL",
+    select = select_spec(
+      label = "Select variable:",
+      choices = variable_choices(data[["ADSL"]], c("SEX", "RACE", "COUNTRY", "ARMCD", "STRATA1")),
+      selected = "ARMCD",
+      multiple = FALSE,
+      fixed = FALSE
+    )
+  )
+)
+
+# configuration for the two wide datasets
+mod2 <- tm_g_response(
+  label = "Two wide datasets",
+  response = data_extract_spec(
+    dataname = "ADSL",
+    select = select_spec(
+      label = "Select variable:",
+      choices = variable_choices(data[["ADSL"]], c("BMRKR2", "ITTFL", "BEP01FL")),
+      selected = "BMRKR2",
+      multiple = FALSE
+    )
+  ),
+  x = data_extract_spec(
+    dataname = "ADSL",
+    select = select_spec(
+      label = "Select variable:",
+      choices = c("SEX", "COUNTRY", "RACE", "STRATA1", "ARMCD"),
+      selected = "ARMCD",
+      multiple = FALSE
+    )
+  )
+)
+
+# configuration for the multiple long datasets
+mod3 <- tm_g_response(
+  label = "Multiple long datasets",
+  response = data_extract_spec(
+    dataname = "ADLB",
+    filter = list(
+      filter_spec(
+        label = "Select parameter:",
+        vars = "PARAMCD",
+        choices = levels(data[["ADLB"]]$PARAMCD),
+        selected = levels(data[["ADLB"]]$PARAMCD)[1],
+        multiple = FALSE
       ),
-      tm_g_response(
-        label = "Two wide datasets",
-        response = teal.transform::data_extract_spec(
-          dataname = "ADSL",
-          select = select_spec(
-            label = "Select variable:",
-            choices = variable_choices(data[["ADSL"]], c("BMRKR2", "ITTFL", "BEP01FL")),
-            selected = "BMRKR2",
-            multiple = FALSE
-          )
-        ),
-        x = teal.transform::data_extract_spec(
-          dataname = "ADSL2",
-          select = select_spec(
-            label = "Select variable:",
-            choices = c("SEX", "COUNTRY", "RACE", "STRATA1", "ARMCD"),
-            selected = "ARMCD",
-            multiple = FALSE
-          )
-        )
+      filter_spec(
+        label = "Select visit:",
+        vars = "AVISIT",
+        choices = levels(data[["ADLB"]]$AVISIT),
+        selected = levels(data[["ADLB"]]$AVISIT)[1],
+        multiple = FALSE
+      )
+    ),
+    select = select_spec(
+      label = "Select variable:",
+      choices = variable_choices(data[["ADLB"]], c("BMRKR2", "ITTFL", "BEP01FL")),
+      selected = "BMRKR2",
+      multiple = FALSE
+    )
+  ),
+  x = data_extract_spec(
+    dataname = "ADRS",
+    filter = list(
+      filter_spec(
+        label = "Select parameter:",
+        vars = "PARAMCD",
+        choices = levels(data[["ADRS"]]$PARAMCD),
+        selected = levels(data[["ADRS"]]$PARAMCD)[3],
+        multiple = FALSE
       ),
-      tm_g_response(
-        label = "Multiple long datasets",
-        response = teal.transform::data_extract_spec(
-          dataname = "ADLB",
-          filter = list(
-            filter_spec(
-              label = "Select parameter:",
-              vars = "PARAMCD",
-              choices = levels(data[["ADLB"]]$PARAMCD),
-              selected = levels(data[["ADLB"]]$PARAMCD)[1],
-              multiple = FALSE
-            ),
-            filter_spec(
-              label = "Select visit:",
-              vars = "AVISIT",
-              choices = levels(data[["ADLB"]]$AVISIT),
-              selected = levels(data[["ADLB"]]$AVISIT)[1],
-              multiple = FALSE
-            )
-          ),
-          select = select_spec(
-            label = "Select variable:",
-            choices = variable_choices(data[["ADLB"]], c("BMRKR2", "ITTFL", "BEP01FL")),
-            selected = "BMRKR2",
-            multiple = FALSE
-          )
-        ),
-        x = teal.transform::data_extract_spec(
-          dataname = "ADRS",
-          filter = list(
-            filter_spec(
-              label = "Select parameter:",
-              vars = "PARAMCD",
-              choices = levels(data[["ADRS"]]$PARAMCD),
-              selected = levels(data[["ADRS"]]$PARAMCD)[3],
-              multiple = FALSE
-            ),
-            filter_spec(
-              label = "Select visit:",
-              vars = "AVISIT",
-              choices = levels(data[["ADRS"]]$AVISIT),
-              selected = levels(data[["ADRS"]]$AVISIT)[3],
-              multiple = FALSE
-            )
-          ),
-          select = select_spec(
-            choices = c("AVALC", "ITTFL", "BEP01FL"),
-            selected = "AVALC",
-            multiple = FALSE,
-            fixed = TRUE
-          )
-        ),
-        row_facet = teal.transform::data_extract_spec(
-          dataname = "ADSL",
-          select = select_spec(
-            label = "Select variable:",
-            choices = "SEX",
-            selected = NULL,
-            multiple = FALSE
-          )
-        ),
-        col_facet = teal.transform::data_extract_spec(
-          dataname = "ADSL",
-          select = select_spec(
-            label = "Select variable:",
-            choices = variable_choices(data[["ADSL"]], c("SEX", "COUNTRY")),
-            selected = NULL,
-            multiple = FALSE
-          )
-        )
+      filter_spec(
+        label = "Select visit:",
+        vars = "AVISIT",
+        choices = levels(data[["ADRS"]]$AVISIT),
+        selected = levels(data[["ADRS"]]$AVISIT)[3],
+        multiple = FALSE
+      )
+    ),
+    select = select_spec(
+      choices = c("AVALC", "ITTFL", "BEP01FL"),
+      selected = "AVALC",
+      multiple = FALSE,
+      fixed = TRUE
+    )
+  ),
+  row_facet = data_extract_spec(
+    dataname = "ADSL",
+    select = select_spec(
+      label = "Select variable:",
+      choices = "SEX",
+      selected = NULL,
+      multiple = FALSE
+    )
+  ),
+  col_facet = data_extract_spec(
+    dataname = "ADSL",
+    select = select_spec(
+      label = "Select variable:",
+      choices = variable_choices(data[["ADSL"]], c("SEX", "COUNTRY")),
+      selected = NULL,
+      multiple = FALSE
+    )
+  )
+)
+
+# configuration for the wide and long dataset
+mod4 <- tm_g_response(
+  label = "Wide and long dataset",
+  response = data_extract_spec(
+    dataname = "ADLB",
+    filter = list(
+      filter_spec(
+        vars = "PARAMCD",
+        choices = levels(data[["ADLB"]]$PARAMCD),
+        selected = levels(data[["ADLB"]]$PARAMCD)[2],
+        multiple = TRUE,
+        label = "Select measurement:"
       ),
-      tm_g_response(
-        label = "Wide and long dataset",
-        response = teal.transform::data_extract_spec(
-          dataname = "ADLB",
-          filter = list(
-            filter_spec(
-              vars = "PARAMCD",
-              choices = levels(data[["ADLB"]]$PARAMCD),
-              selected = levels(data[["ADLB"]]$PARAMCD)[2],
-              multiple = TRUE,
-              label = "Select measurement:"
-            ),
-            filter_spec(
-              vars = "AVISIT",
-              choices = levels(data[["ADLB"]]$AVISIT),
-              selected = levels(data[["ADLB"]]$AVISIT)[2],
-              multiple = TRUE,
-              label = "Select visit:"
-            )
-          ),
-          select = select_spec(
-            choices = variable_choices(data[["ADLB"]], c("BMRKR2", "ITTFL", "BEP01FL")),
-            selected = "BMRKR2",
-            multiple = FALSE,
-            fixed = FALSE,
-            label = "Select variable:"
-          )
-        ),
-        x = teal.transform::data_extract_spec(
-          dataname = "ADSL",
-          select = select_spec(
-            choices = variable_choices(data[["ADSL"]], c("ARMCD", "BMRKR1", "BMRKR2", "BEP01FL")),
-            selected = "BMRKR2",
-            multiple = FALSE,
-            fixed = FALSE
-          )
-        )
+      filter_spec(
+        vars = "AVISIT",
+        choices = levels(data[["ADLB"]]$AVISIT),
+        selected = levels(data[["ADLB"]]$AVISIT)[2],
+        multiple = TRUE,
+        label = "Select visit:"
+      )
+    ),
+    select = select_spec(
+      choices = variable_choices(data[["ADLB"]], c("BMRKR2", "ITTFL", "BEP01FL")),
+      selected = "BMRKR2",
+      multiple = FALSE,
+      fixed = FALSE,
+      label = "Select variable:"
+    )
+  ),
+  x = data_extract_spec(
+    dataname = "ADSL",
+    select = select_spec(
+      choices = variable_choices(data[["ADSL"]], c("ARMCD", "BMRKR1", "BMRKR2", "BEP01FL")),
+      selected = "BMRKR2",
+      multiple = FALSE,
+      fixed = FALSE
+    )
+  )
+)
+
+# configuration for the same long datasets (same subsets)
+mod5 <- tm_g_response(
+  label = "Same long datasets (same subsets)",
+  response = data_extract_spec(
+    dataname = "ADRS",
+    select = select_spec(
+      choices = variable_choices(data[["ADRS"]], c("BMRKR2", "AVALC", "BEP01FL")),
+      selected = "AVALC",
+      multiple = FALSE,
+      fixed = TRUE,
+      label = "Select variable:"
+    )
+  ),
+  x = data_extract_spec(
+    dataname = "ADRS",
+    select = select_spec(
+      choices = variable_choices(data[["ADRS"]], c("AVALC", "AGE", "SEX", "ARMCD", "STRATA1")),
+      selected = "ARMCD",
+      multiple = FALSE,
+      fixed = FALSE,
+      label = "Select variable:"
+    )
+  ),
+  row_facet = data_extract_spec(
+    dataname = "ADRS",
+    select = select_spec(
+      choices = "PARAMCD",
+      selected = "PARAMCD",
+      multiple = FALSE,
+      fixed = FALSE,
+      label = "Select variable:"
+    )
+  ),
+  col_facet = data_extract_spec(
+    dataname = "ADRS",
+    select = select_spec(
+      choices = "AVISIT",
+      selected = "AVISIT",
+      multiple = FALSE,
+      fixed = FALSE,
+      label = "Select variable:"
+    )
+  )
+)
+
+# configuration for the same long datasets (different subsets)
+mod6 <- tm_g_response(
+  label = "Same long datasets (different subsets)",
+  response = data_extract_spec(
+    dataname = "ADLB",
+    filter = filter_spec(
+      vars = "PARAMCD",
+      choices = levels(data[["ADLB"]]$PARAMCD),
+      selected = levels(data[["ADLB"]]$PARAMCD)[2],
+      multiple = FALSE,
+      label = "Select lab:"
+    ),
+    select = select_spec(
+      choices = "BMRKR2",
+      selected = "BMRKR2",
+      multiple = FALSE,
+      fixed = TRUE
+    )
+  ),
+  x = data_extract_spec(
+    dataname = "ADLB",
+    filter = filter_spec(
+      vars = "PARAMCD",
+      choices = levels(data[["ADLB"]]$PARAMCD),
+      selected = levels(data[["ADLB"]]$PARAMCD)[1],
+      multiple = FALSE,
+      label = "Select lab:"
+    ),
+    select = select_spec(
+      choices = variable_choices(data[["ADLB"]], c("AVISIT", "PARAMCD", "BEP01FL")),
+      selected = "AVISIT",
+      multiple = FALSE,
+      fixed = TRUE
+    )
+  ),
+  row_facet = data_extract_spec(
+    dataname = "ADLB",
+    filter = list(
+      filter_spec(
+        vars = "PARAMCD",
+        choices = levels(data[["ADLB"]]$PARAMCD),
+        selected = levels(data[["ADLB"]]$PARAMCD)[1],
+        multiple = FALSE,
+        label = "Select lab:"
       ),
-      tm_g_response(
-        label = "Same long datasets",
-        response = teal.transform::data_extract_spec(
-          dataname = "ADRS",
-          select = select_spec(
-            choices = variable_choices(data[["ADRS"]], c("BMRKR2", "AVALC", "BEP01FL")),
-            selected = "AVALC",
-            multiple = FALSE,
-            fixed = TRUE,
-            label = "Select variable:"
-          )
-        ),
-        x = teal.transform::data_extract_spec(
-          dataname = "ADRS",
-          select = select_spec(
-            choices = variable_choices(data[["ADRS"]], c("AVALC", "AGE", "SEX", "ARMCD", "STRATA1")),
-            selected = "ARMCD",
-            multiple = FALSE,
-            fixed = FALSE,
-            label = "Select variable:"
-          )
-        ),
-        row_facet = teal.transform::data_extract_spec(
-          dataname = "ADRS",
-          select = select_spec(
-            choices = "PARAMCD",
-            selected = "PARAMCD",
-            multiple = FALSE,
-            fixed = FALSE,
-            label = "Select variable:"
-          )
-        ),
-        col_facet = teal.transform::data_extract_spec(
-          dataname = "ADRS",
-          select = select_spec(
-            choices = "AVISIT",
-            selected = "AVISIT",
-            multiple = FALSE,
-            fixed = FALSE,
-            label = "Select variable:"
-          )
-        )
+      filter_spec(
+        vars = "AVISIT",
+        choices = levels(data[["ADLB"]]$AVISIT),
+        selected = levels(data[["ADLB"]]$AVISIT)[1],
+        multiple = FALSE,
+        label = "Select visit:"
+      )
+    ),
+    select = select_spec(
+      choices = variable_choices(data[["ADLB"]], c("SEX", "RACE", "ARMCD")),
+      selected = NULL,
+      multiple = FALSE,
+      fixed = FALSE,
+      label = "Select Variable"
+    )
+  ),
+  col_facet = data_extract_spec(
+    dataname = "ADLB",
+    filter = list(
+      filter_spec(
+        vars = "PARAMCD",
+        choices = levels(data[["ADLB"]]$PARAMCD),
+        selected = levels(data[["ADLB"]]$PARAMCD)[1],
+        multiple = FALSE,
+        label = "Select lab:"
       ),
-      tm_g_response(
-        label = "Same long datasets  (different subsets)",
-        response = teal.transform::data_extract_spec(
-          dataname = "ADLB",
-          filter = teal.transform::filter_spec(
-            vars = "PARAMCD",
-            choices = levels(data[["ADLB"]]$PARAMCD),
-            selected = levels(data[["ADLB"]]$PARAMCD)[2],
-            multiple = FALSE,
-            label = "Select lab:"
-          ),
-          select = select_spec(
-            choices = "BMRKR2",
-            selected = "BMRKR2",
-            multiple = FALSE,
-            fixed = TRUE
-          )
-        ),
-        x = teal.transform::data_extract_spec(
-          dataname = "ADLB",
-          filter = teal.transform::filter_spec(
-            vars = "PARAMCD",
-            choices = levels(data[["ADLB"]]$PARAMCD),
-            selected = levels(data[["ADLB"]]$PARAMCD)[1],
-            multiple = FALSE,
-            label = "Select lab:"
-          ),
-          select = select_spec(
-            choices = variable_choices(data[["ADLB"]], c("AVISIT", "PARAMCD", "BEP01FL")),
-            selected = "AVISIT",
-            multiple = FALSE,
-            fixed = TRUE
-          )
-        ),
-        row_facet = teal.transform::data_extract_spec(
-          dataname = "ADLB",
-          filter = list(
-            filter_spec(
-              vars = "PARAMCD",
-              choices = levels(data[["ADLB"]]$PARAMCD),
-              selected = levels(data[["ADLB"]]$PARAMCD)[1],
-              multiple = FALSE,
-              label = "Select lab:"
-            ),
-            filter_spec(
-              vars = "AVISIT",
-              choices = levels(data[["ADLB"]]$AVISIT),
-              selected = levels(data[["ADLB"]]$AVISIT)[1],
-              multiple = FALSE,
-              label = "Select visit:"
-            )
-          ),
-          select = select_spec(
-            choices = variable_choices(data[["ADLB"]], c("SEX", "RACE", "ARMCD")),
-            selected = NULL,
-            multiple = FALSE,
-            fixed = FALSE,
-            label = "Select Variable"
-          )
-        ),
-        col_facet = teal.transform::data_extract_spec(
-          dataname = "ADLB",
-          filter = list(
-            filter_spec(
-              vars = "PARAMCD",
-              choices = levels(data[["ADLB"]]$PARAMCD),
-              selected = levels(data[["ADLB"]]$PARAMCD)[1],
-              multiple = FALSE,
-              label = "Select lab:"
-            ),
-            filter_spec(
-              vars = "AVISIT",
-              choices = levels(data[["ADLB"]]$AVISIT),
-              selected = levels(data[["ADLB"]]$AVISIT)[1],
-              multiple = FALSE,
-              label = "Select visit:"
-            )
-          ),
-          select = select_spec(
-            choices = variable_choices(data[["ADLB"]], c("SEX", "RACE", "ARMCD")),
-            selected = NULL,
-            multiple = FALSE,
-            fixed = FALSE,
-            label = "Select variable:"
-          )
-        )
+      filter_spec(
+        vars = "AVISIT",
+        choices = levels(data[["ADLB"]]$AVISIT),
+        selected = levels(data[["ADLB"]]$AVISIT)[1],
+        multiple = FALSE,
+        label = "Select visit:"
       )
+    ),
+    select = select_spec(
+      choices = variable_choices(data[["ADLB"]], c("SEX", "RACE", "ARMCD")),
+      selected = NULL,
+      multiple = FALSE,
+      fixed = FALSE,
+      label = "Select variable:"
+    )
+  )
+)
+
+# initialize the app
+app <- init(
+  data = data,
+  modules = modules(
+    modules(
+      label = "Response plot",
+      mod1,
+      mod2,
+      mod3,
+      mod4,
+      mod5,
+      mod6
     )
   )
 )
 ```
 
-## Run the app
+## 4 - Run the app
 
-A simple `shiny::shinyApp` call will let you run the app.
-Note that app is only displayed when running this code inside an R session.
+A simple `shiny::shinyApp()` call will let you run the app.
+Note that app is only displayed when running this code inside an `R` session.
 
-```{r echo=TRUE}
+```{r, echo=TRUE, results="hide"}
 shinyApp(app$ui, app$server, options = list(height = 1024, width = 1024))
 ```
 
-
+<img src="images/app-using-response-plot.png" style = "display: block; margin: 0px; width: 100%"/>
diff --git a/vignettes/using-scatterplot-matrix.Rmd b/vignettes/using-scatterplot-matrix.Rmd
index 7b3167a68..c462e68a8 100644
--- a/vignettes/using-scatterplot-matrix.Rmd
+++ b/vignettes/using-scatterplot-matrix.Rmd
@@ -12,37 +12,34 @@ vignette: >
 
 # `teal` application to use scatter plot matrix with various datasets types
 
-This vignette will guide you through 4 parts to create a teal application using
-various types of datasets inside an scatter plot matrix module:
+This vignette will guide you through the four parts to create a `teal` application using
+various types of datasets using the scatter plot matrix module `tm_g_scatterplotmatrix()`:
 
-1. Load Libraries
+1. Load libraries
 2. Create data sets
 3. Create an `app` variable
-4. Run the App
+4. Run the app
 
-## Loading libraries
+## 1 - Load libraries
 
 ```{r echo=TRUE, message=FALSE, warning=FALSE, results="hide"}
 library(teal.modules.general) # used to create the app
 library(dplyr) # used to modify data sets
 ```
 
-## Create data sets
+## 2 - Create data sets
 
-Inside this app 5 datasets will be used
+Inside this app 4 datasets will be used
 
 1. `ADSL` A wide data set with subject data
-2. `ADSL2` A wide data set with subject data
-3. `ADRS` A long data set with response data for subjects at different time points of the study
-4. `ADTTE` A long data set with time to event data
-5. `ADLB` A long data set with lab measurements for each subject
+2. `ADRS` A long data set with response data for subjects at different time points of the study
+3. `ADTTE` A long data set with time to event data
+4. `ADLB` A long data set with lab measurements for each subject
 
 ```{r echo=TRUE, message=FALSE, warning=FALSE, results="hide"}
-# nolint start
 data <- teal_data()
 data <- within(data, {
-  ADSL <- teal.modules.general::rADSL
-  ADSL2 <- teal.modules.general::rADSL %>%
+  ADSL <- teal.modules.general::rADSL %>%
     mutate(TRTDUR = round(as.numeric(TRTEDTM - TRTSDTM), 1))
   ADRS <- teal.modules.general::rADRS
   ADTTE <- teal.modules.general::rADTTE
@@ -53,137 +50,115 @@ data <- within(data, {
       TRUE ~ "-"
     )))
 })
-datanames <- c("ADSL", "ADSL2", "ADRS", "ADTTE", "ADLB")
+datanames <- c("ADSL", "ADRS", "ADTTE", "ADLB")
 datanames(data) <- datanames
-jk <- default_cdisc_join_keys[datanames]
-jk_adsl2 <- jk
-names(jk_adsl2)[names(jk_adsl2) == "ADSL"] <- "ADSL2"
-jk <- c(jk, jk_adsl2)
-jk["ADSL2", "ADSL"] <- c("USUBJID", "STUDYID")
-# nolint end
+join_keys(data) <- default_cdisc_join_keys[datanames]
 ```
 
-## Create an `app` variable
+## 3 - Create an `app` variable
 
-This is the most important section. We will use the [`teal::init`](https://insightsengineering.github.io/teal/latest-tag/reference/init) function to
-create an app. The data will be handed over using [`teal.data::cdisc_data`](https://insightsengineering.github.io/teal.data/latest-tag/reference/cdisc_data). The app
-itself will be constructed by multiple calls of `tm_g_scatterplotmatrix` using different
+This is the most important section. We will use the `teal::init()` function to
+create an app. The data will be handed over using `teal.data::teal_data()`. The app
+itself will be constructed by multiple calls of `tm_g_scatterplotmatrix()` using different
 combinations of data sets.
 
 ```{r echo=TRUE, message=FALSE, warning=FALSE, results="hide"}
-app <- teal::init(
-  data = data,
-  modules = teal::modules(
-    modules(
-      label = "Scatterplot matrix",
-      # .. single wide ----
-      tm_g_scatterplotmatrix(
-        label = "Single wide dataset",
-        variables = teal.transform::data_extract_spec(
-          dataname = "ADSL",
-          select = select_spec(
-            label = "Select variables:",
-            choices = variable_choices(data[["ADSL"]]),
-            selected = c("AGE", "RACE", "SEX", "BMRKR1", "BMRKR2"),
-            multiple = TRUE,
-            fixed = FALSE,
-            ordered = TRUE
-          )
-        )
-      ),
-      tm_g_scatterplotmatrix(
-        label = "Multiple wide datasets",
-        variables = list(
-          teal.transform::data_extract_spec(
-            dataname = "ADSL",
-            select = select_spec(
-              label = "Select variables:",
-              choices = variable_choices(data[["ADSL"]]),
-              selected = c("AGE", "ACTARM", "SEX", "BMRKR1"),
-              multiple = TRUE,
-              fixed = FALSE,
-              ordered = TRUE
-            )
-          ),
-          teal.transform::data_extract_spec(
-            dataname = "ADSL2",
-            select = select_spec(
-              label = "Select variables:",
-              choices = variable_choices(data[["ADSL2"]]),
-              selected = c("COUNTRY", "ACTARM", "STRATA1"),
-              multiple = TRUE,
-              fixed = FALSE,
-              ordered = TRUE
-            )
-          )
-        )
+# configuration for the single wide dataset
+mod1 <- tm_g_scatterplotmatrix(
+  label = "Single wide dataset",
+  variables = data_extract_spec(
+    dataname = "ADSL",
+    select = select_spec(
+      label = "Select variables:",
+      choices = variable_choices(data[["ADSL"]]),
+      selected = c("AGE", "RACE", "SEX", "BMRKR1", "BMRKR2"),
+      multiple = TRUE,
+      fixed = FALSE,
+      ordered = TRUE
+    )
+  )
+)
+
+# configuration for the one long datasets
+mod2 <- tm_g_scatterplotmatrix(
+  "One long dataset",
+  variables = data_extract_spec(
+    dataname = "ADTTE",
+    select = select_spec(
+      choices = variable_choices(data[["ADTTE"]], c("AVAL", "BMRKR1", "BMRKR2")),
+      selected = c("AVAL", "BMRKR1", "BMRKR2"),
+      multiple = TRUE,
+      fixed = FALSE,
+      ordered = TRUE,
+      label = "Select variables:"
+    )
+  )
+)
+
+# configuration for the two long datasets
+mod3 <- tm_g_scatterplotmatrix(
+  label = "Two long datasets",
+  variables = list(
+    data_extract_spec(
+      dataname = "ADRS",
+      select = select_spec(
+        label = "Select variables:",
+        choices = variable_choices(data[["ADRS"]]),
+        selected = c("AVAL", "AVALC"),
+        multiple = TRUE,
+        fixed = FALSE,
+        ordered = TRUE,
       ),
-      tm_g_scatterplotmatrix(
-        "One long dataset",
-        variables = teal.transform::data_extract_spec(
-          dataname = "ADTTE",
-          select = select_spec(
-            choices = variable_choices(data[["ADTTE"]], c("AVAL", "BMRKR1", "BMRKR2")),
-            selected = c("AVAL", "BMRKR1", "BMRKR2"),
-            multiple = TRUE,
-            fixed = FALSE,
-            ordered = TRUE,
-            label = "Select variables:"
-          )
-        )
+      filter = filter_spec(
+        label = "Select endpoints:",
+        vars = c("PARAMCD", "AVISIT"),
+        choices = value_choices(data[["ADRS"]], c("PARAMCD", "AVISIT"), c("PARAM", "AVISIT")),
+        selected = "OVRINV - SCREENING",
+        multiple = FALSE
+      )
+    ),
+    data_extract_spec(
+      dataname = "ADTTE",
+      select = select_spec(
+        label = "Select variables:",
+        choices = variable_choices(data[["ADTTE"]]),
+        selected = c("AVAL", "CNSR"),
+        multiple = TRUE,
+        fixed = FALSE,
+        ordered = TRUE
       ),
-      tm_g_scatterplotmatrix(
-        label = "Two long datasets",
-        variables = list(
-          teal.transform::data_extract_spec(
-            dataname = "ADRS",
-            select = select_spec(
-              label = "Select variables:",
-              choices = variable_choices(data[["ADRS"]]),
-              selected = c("AVAL", "AVALC"),
-              multiple = TRUE,
-              fixed = FALSE,
-              ordered = TRUE,
-            ),
-            filter = teal.transform::filter_spec(
-              label = "Select endpoints:",
-              vars = c("PARAMCD", "AVISIT"),
-              choices = value_choices(data[["ADRS"]], c("PARAMCD", "AVISIT"), c("PARAM", "AVISIT")),
-              selected = "OVRINV - SCREENING",
-              multiple = FALSE
-            )
-          ),
-          teal.transform::data_extract_spec(
-            dataname = "ADTTE",
-            select = select_spec(
-              label = "Select variables:",
-              choices = variable_choices(data[["ADTTE"]]),
-              selected = c("AVAL", "CNSR"),
-              multiple = TRUE,
-              fixed = FALSE,
-              ordered = TRUE
-            ),
-            filter = teal.transform::filter_spec(
-              label = "Select parameters:",
-              vars = "PARAMCD",
-              choices = value_choices(data[["ADTTE"]], "PARAMCD", "PARAM"),
-              selected = "OS",
-              multiple = TRUE
-            )
-          )
-        )
+      filter = filter_spec(
+        label = "Select parameters:",
+        vars = "PARAMCD",
+        choices = value_choices(data[["ADTTE"]], "PARAMCD", "PARAM"),
+        selected = "OS",
+        multiple = TRUE
       )
     )
   )
 )
+
+# initialize the app
+app <- init(
+  data = data,
+  modules = modules(
+    modules(
+      label = "Scatterplot matrix",
+      mod1,
+      mod2,
+      mod3
+    )
+  )
+)
 ```
 
-## Run the app
+## 4 - Run the app
 
-A simple `shiny::shinyApp` call will let you run the app.
-Note that app is only displayed when running this code inside an R session.
+A simple `shiny::shinyApp()` call will let you run the app.
+Note that app is only displayed when running this code inside an `R` session.
 
-```{r echo=TRUE}
+```{r, echo=TRUE, results="hide"}
 shinyApp(app$ui, app$server, options = list(height = 1024, width = 1024))
 ```
 
+<img src="images/app-using-scatterplot-matrix.png" style = "display: block; margin: 0px; width: 100%"/>
diff --git a/vignettes/using-scatterplot.Rmd b/vignettes/using-scatterplot.Rmd
index 32c1ec3d1..4ae42895c 100644
--- a/vignettes/using-scatterplot.Rmd
+++ b/vignettes/using-scatterplot.Rmd
@@ -12,37 +12,34 @@ vignette: >
 
 # `teal` application to use scatter plot with various datasets types
 
-This vignette will guide you through 4 parts to create a teal application using
-various types of datasets inside an scatter plot module:
+This vignette will guide you through the four parts to create a `teal` application using
+various types of datasets using the scatter plot module `tm_g_scatterplot()`:
 
-1. Load Libraries
+1. Load libraries
 2. Create data sets
 3. Create an `app` variable
-4. Run the App
+4. Run the app
 
-## Loading libraries
+## 1 - Load libraries
 
 ```{r echo=TRUE, message=FALSE, warning=FALSE, results="hide"}
 library(teal.modules.general) # used to create the app
 library(dplyr) # used to modify data sets
 ```
 
-## Create data sets
+## 2 - Create data sets
 
-Inside this app 5 datasets will be used
+Inside this app 4 datasets will be used
 
 1. `ADSL` A wide data set with subject data
-2. `ADSL2` A wide data set with subject data
-3. `ADRS` A long data set with response data for subjects at different time points of the study
-4. `ADTTE` A long data set with time to event data
-5. `ADLB` A long data set with lab measurements for each subject
+2. `ADRS` A long data set with response data for subjects at different time points of the study
+3. `ADTTE` A long data set with time to event data
+4. `ADLB` A long data set with lab measurements for each subject
 
 ```{r echo=TRUE, message=FALSE, warning=FALSE, results="hide"}
-# nolint start
 data <- teal_data()
 data <- within(data, {
-  ADSL <- teal.modules.general::rADSL
-  ADSL2 <- teal.modules.general::rADSL %>%
+  ADSL <- teal.modules.general::rADSL %>%
     mutate(TRTDUR = round(as.numeric(TRTEDTM - TRTSDTM), 1))
   ADRS <- teal.modules.general::rADRS
   ADTTE <- teal.modules.general::rADTTE
@@ -53,21 +50,16 @@ data <- within(data, {
       TRUE ~ "-"
     )))
 })
-datanames <- c("ADSL", "ADSL2", "ADRS", "ADTTE", "ADLB")
+datanames <- c("ADSL", "ADRS", "ADTTE", "ADLB")
 datanames(data) <- datanames
-jk <- default_cdisc_join_keys[datanames]
-jk_adsl2 <- jk
-names(jk_adsl2)[names(jk_adsl2) == "ADSL"] <- "ADSL2"
-jk <- c(jk, jk_adsl2)
-jk["ADSL2", "ADSL"] <- c("USUBJID", "STUDYID")
-# nolint end
+join_keys(data) <- default_cdisc_join_keys[datanames]
 ```
 
-## Create an `app` variable
+## 3 - Create an `app` variable
 
-This is the most important section. We will use the [`teal::init`](https://insightsengineering.github.io/teal/latest-tag/reference/init) function to
-create an app. The data will be handed over using [`teal.data::cdisc_data`](https://insightsengineering.github.io/teal.data/latest-tag/reference/cdisc_data). The app
-itself will be constructed by multiple calls of `tm_g_scatterplot` using different
+This is the most important section. We will use the `teal::init()` function to
+create an app. The data will be handed over using `teal.data::teal_data()`. The app
+itself will be constructed by multiple calls of `tm_g_scatterplot()` using different
 combinations of data sets.
 
 ```{r ggExtra, include = FALSE}
@@ -77,296 +69,316 @@ ggextra_available <- requireNamespace("ggExtra", quietly = TRUE)
 # NOTE: The code will not be run as package ggExtra is not installed.
 ```
 ```{r, eval = ggextra_available, echo=TRUE, message=FALSE, warning=FALSE, results="hide"}
-app <- teal::init(
-  data = data,
-  modules = teal::modules(
-    modules(
-      label = "Scatterplot",
-      tm_g_scatterplot(
-        label = "Single wide dataset",
-        x = teal.transform::data_extract_spec(
-          dataname = "ADSL",
-          select = select_spec(
-            label = "Select variable:",
-            choices = variable_choices(data[["ADSL"]], c("AGE", "BMRKR1", "BMRKR2")),
-            selected = "AGE",
-            multiple = FALSE,
-            fixed = FALSE
-          )
-        ),
-        y = teal.transform::data_extract_spec(
-          dataname = "ADSL",
-          select = select_spec(
-            label = "Select variable:",
-            choices = variable_choices(data[["ADSL"]], c("AGE", "BMRKR1", "BMRKR2")),
-            selected = "BMRKR1",
-            multiple = FALSE,
-            fixed = FALSE
-          )
-        ),
-        color_by = teal.transform::data_extract_spec(
-          dataname = "ADSL",
-          select = select_spec(
-            label = "Select variables:",
-            choices = variable_choices(data[["ADSL"]], c("RACE", "SEX")),
-            selected = NULL,
-            multiple = TRUE,
-            fixed = FALSE
-          )
-        )
-      ),
-      # .. Two wide -----
-      tm_g_scatterplot(
-        label = "Two wide datasets",
-        x = teal.transform::data_extract_spec(
-          dataname = "ADSL",
-          select = select_spec(
-            label = "Select variable:",
-            choices = variable_choices(data[["ADSL"]], c("BMRKR1", "BMRKR2")),
-            selected = "BMRKR1",
-            multiple = FALSE,
-            fixed = FALSE
-          )
-        ),
-        y = teal.transform::data_extract_spec(
-          dataname = "ADSL2",
-          select = select_spec(
-            label = "Select variable:",
-            choices = variable_choices(data[["ADSL2"]], c("AGE", "SEX")),
-            selected = "AGE",
-            multiple = FALSE,
-            fixed = FALSE
-          )
-        ),
-        color_by = teal.transform::data_extract_spec(
-          dataname = "ADSL2",
-          select = select_spec(
-            label = "Select variable:",
-            choices = variable_choices(data[["ADSL2"]], c("COUNTRY", "AGE", "RACE")),
-            selected = "COUNTRY",
-            multiple = FALSE,
-            fixed = FALSE
-          )
-        )
+# configuration for the single wide datasets
+mod1 <- tm_g_scatterplot(
+  label = "Single wide dataset",
+  x = data_extract_spec(
+    dataname = "ADSL",
+    select = select_spec(
+      label = "Select variable:",
+      choices = variable_choices(data[["ADSL"]], c("AGE", "BMRKR1", "BMRKR2")),
+      selected = "AGE",
+      multiple = FALSE,
+      fixed = FALSE
+    )
+  ),
+  y = data_extract_spec(
+    dataname = "ADSL",
+    select = select_spec(
+      label = "Select variable:",
+      choices = variable_choices(data[["ADSL"]], c("AGE", "BMRKR1", "BMRKR2")),
+      selected = "BMRKR1",
+      multiple = FALSE,
+      fixed = FALSE
+    )
+  ),
+  color_by = data_extract_spec(
+    dataname = "ADSL",
+    select = select_spec(
+      label = "Select variables:",
+      choices = variable_choices(data[["ADSL"]], c("RACE", "SEX")),
+      selected = NULL,
+      multiple = TRUE,
+      fixed = FALSE
+    )
+  )
+)
+
+# configuration for the two wide datasets
+mod2 <- tm_g_scatterplot(
+  label = "Two wide datasets",
+  x = data_extract_spec(
+    dataname = "ADSL",
+    select = select_spec(
+      label = "Select variable:",
+      choices = variable_choices(data[["ADSL"]], c("BMRKR1", "BMRKR2")),
+      selected = "BMRKR1",
+      multiple = FALSE,
+      fixed = FALSE
+    )
+  ),
+  y = data_extract_spec(
+    dataname = "ADSL",
+    select = select_spec(
+      label = "Select variable:",
+      choices = variable_choices(data[["ADSL"]], c("AGE", "SEX")),
+      selected = "AGE",
+      multiple = FALSE,
+      fixed = FALSE
+    )
+  ),
+  color_by = data_extract_spec(
+    dataname = "ADSL",
+    select = select_spec(
+      label = "Select variable:",
+      choices = variable_choices(data[["ADSL"]], c("COUNTRY", "AGE", "RACE")),
+      selected = "COUNTRY",
+      multiple = FALSE,
+      fixed = FALSE
+    )
+  )
+)
+
+# configuration for the different long datasets
+mod3 <- tm_g_scatterplot(
+  label = "Different long datasets",
+  x = data_extract_spec(
+    dataname = "ADRS",
+    select = select_spec(
+      label = "Select variable:",
+      choices = variable_choices(data[["ADRS"]]),
+      selected = "AVAL",
+      multiple = FALSE,
+      fixed = FALSE
+    ),
+    filter = filter_spec(
+      label = "Select endpoint:",
+      vars = c("PARAMCD", "AVISIT"),
+      choices = value_choices(data[["ADRS"]], c("PARAMCD", "AVISIT"), c("PARAM", "AVISIT")),
+      selected = "OVRINV - SCREENING",
+      multiple = FALSE
+    )
+  ),
+  y = data_extract_spec(
+    dataname = "ADTTE",
+    select = select_spec(
+      label = "Select variable:",
+      choices = variable_choices(data[["ADTTE"]]),
+      selected = "AVAL",
+      multiple = FALSE,
+      fixed = FALSE
+    ),
+    filter = filter_spec(
+      label = "Select parameters:",
+      vars = c("PARAMCD"),
+      choices = value_choices(data[["ADTTE"]], "PARAMCD", "PARAM"),
+      selected = "OS",
+      multiple = TRUE
+    )
+  ),
+  color_by = data_extract_spec(
+    dataname = "ADSL",
+    select = select_spec(
+      label = "Select variable:",
+      choices = variable_choices(data[["ADSL"]], c("AGE", "SEX")),
+      selected = "AGE",
+      multiple = FALSE,
+      fixed = FALSE
+    )
+  )
+)
+
+# configuration for the wide and long datasets
+mod4 <- tm_g_scatterplot(
+  label = "Wide and long datasets",
+  x = data_extract_spec(
+    dataname = "ADSL",
+    select = select_spec(
+      label = "Select variable:",
+      choices = variable_choices(data[["ADSL"]], c("SEX", "AGE", "BMRKR1", "COUNTRY")),
+      selected = "AGE",
+      multiple = FALSE,
+      fixed = FALSE
+    )
+  ),
+  y = data_extract_spec(
+    dataname = "ADLB",
+    filter = list(
+      filter_spec(
+        vars = "PARAMCD",
+        choices = value_choices(data[["ADLB"]], "PARAMCD", "PARAM"),
+        selected = levels(data[["ADLB"]]$PARAMCD)[1],
+        multiple = FALSE,
+        label = "Select measurement:"
       ),
-      tm_g_scatterplot(
-        label = "Different long datasets",
-        x = teal.transform::data_extract_spec(
-          dataname = "ADRS",
-          select = select_spec(
-            label = "Select variable:",
-            choices = variable_choices(data[["ADRS"]]),
-            selected = "AVAL",
-            multiple = FALSE,
-            fixed = FALSE
-          ),
-          filter = teal.transform::filter_spec(
-            label = "Select endpoint:",
-            vars = c("PARAMCD", "AVISIT"),
-            choices = value_choices(data[["ADRS"]], c("PARAMCD", "AVISIT"), c("PARAM", "AVISIT")),
-            selected = "OVRINV - SCREENING",
-            multiple = FALSE
-          )
-        ),
-        y = teal.transform::data_extract_spec(
-          dataname = "ADTTE",
-          select = select_spec(
-            label = "Select variable:",
-            choices = variable_choices(data[["ADTTE"]]),
-            selected = "AVAL",
-            multiple = FALSE,
-            fixed = FALSE
-          ),
-          filter = teal.transform::filter_spec(
-            label = "Select parameters:",
-            vars = c("PARAMCD"),
-            choices = value_choices(data[["ADTTE"]], "PARAMCD", "PARAM"),
-            selected = "OS",
-            multiple = TRUE
-          )
-        ),
-        color_by = teal.transform::data_extract_spec(
-          dataname = "ADSL",
-          select = select_spec(
-            label = "Select variable:",
-            choices = variable_choices(data[["ADSL"]], c("AGE", "SEX")),
-            selected = "AGE",
-            multiple = FALSE,
-            fixed = FALSE
-          )
-        )
+      filter_spec(
+        vars = "AVISIT",
+        choices = levels(data[["ADLB"]]$AVISIT),
+        selected = levels(data[["ADLB"]]$AVISIT)[1],
+        multiple = FALSE,
+        label = "Select visit:"
+      )
+    ),
+    select = select_spec(
+      label = "Selected variable:",
+      choices = "AVAL",
+      selected = "AVAL",
+      multiple = FALSE,
+      fixed = TRUE
+    )
+  ),
+  color_by = data_extract_spec(
+    dataname = "ADSL",
+    select = select_spec(
+      label = "Select variable:",
+      choices = variable_choices(data[["ADSL"]], c("SEX", "AGE", "RACE", "COUNTRY")),
+      selected = NULL,
+      multiple = FALSE,
+      fixed = FALSE
+    )
+  )
+)
+
+# configuration for the same long datasets (same subsets)
+mod5 <- tm_g_scatterplot(
+  label = "Same long datasets (same subsets)",
+  x = data_extract_spec(
+    dataname = "ADRS",
+    select = select_spec(
+      choices = variable_choices(data[["ADRS"]], c("AVAL", "BMRKR1", "BMRKR2")),
+      selected = "AVAL",
+      multiple = FALSE,
+      fixed = FALSE,
+      label = "Select variable:"
+    )
+  ),
+  y = data_extract_spec(
+    dataname = "ADRS",
+    select = select_spec(
+      choices = variable_choices(data[["ADRS"]], c("AVAL", "BMRKR1", "BMRKR2")),
+      selected = "BMRKR1",
+      multiple = FALSE,
+      fixed = FALSE,
+      label = "Select variable:"
+    )
+  ),
+  color_by = data_extract_spec(
+    dataname = "ADRS",
+    select = select_spec(
+      choices = variable_choices(data[["ADRS"]], c("AGE", "SEX", "RACE")),
+      selected = NULL,
+      multiple = FALSE,
+      fixed = FALSE,
+      label = "Select variable:"
+    )
+  )
+)
+
+# configuration for the same long datasets (different subsets)
+mod6 <- tm_g_scatterplot(
+  label = "Same long datasets (different subsets)",
+  x = data_extract_spec(
+    dataname = "ADLB",
+    filter = list(
+      filter_spec(
+        vars = "PARAMCD",
+        choices = value_choices(data[["ADLB"]], "PARAMCD", "PARAM"),
+        selected = levels(data[["ADLB"]]$PARAMCD)[1],
+        multiple = FALSE,
+        label = "Select lab:"
       ),
-      tm_g_scatterplot(
-        label = "Wide and long datasets",
-        x = teal.transform::data_extract_spec(
-          dataname = "ADSL",
-          select = select_spec(
-            label = "Select variable:",
-            choices = variable_choices(data[["ADSL"]], c("SEX", "AGE", "BMRKR1", "COUNTRY")),
-            selected = "AGE",
-            multiple = FALSE,
-            fixed = FALSE
-          )
-        ),
-        y = teal.transform::data_extract_spec(
-          dataname = "ADLB",
-          filter = list(
-            filter_spec(
-              vars = "PARAMCD",
-              choices = value_choices(data[["ADLB"]], "PARAMCD", "PARAM"),
-              selected = levels(data[["ADLB"]]$PARAMCD)[1],
-              multiple = FALSE,
-              label = "Select measurement:"
-            ),
-            filter_spec(
-              vars = "AVISIT",
-              choices = levels(data[["ADLB"]]$AVISIT),
-              selected = levels(data[["ADLB"]]$AVISIT)[1],
-              multiple = FALSE,
-              label = "Select visit:"
-            )
-          ),
-          select = select_spec(
-            label = "Selected variable:",
-            choices = "AVAL",
-            selected = "AVAL",
-            multiple = FALSE,
-            fixed = TRUE
-          )
-        ),
-        color_by = teal.transform::data_extract_spec(
-          dataname = "ADSL",
-          select = select_spec(
-            label = "Select variable:",
-            choices = variable_choices(data[["ADSL"]], c("SEX", "AGE", "RACE", "COUNTRY")),
-            selected = NULL,
-            multiple = FALSE,
-            fixed = FALSE
-          )
-        )
+      filter_spec(
+        vars = "AVISIT",
+        choices = levels(data[["ADLB"]]$AVISIT),
+        selected = levels(data[["ADLB"]]$AVISIT)[1],
+        multiple = FALSE,
+        label = "Select visit:"
+      )
+    ),
+    select = select_spec(
+      choices = "AVAL",
+      selected = "AVAL",
+      multiple = FALSE,
+      fixed = TRUE
+    )
+  ),
+  y = data_extract_spec(
+    dataname = "ADLB",
+    filter = list(
+      filter_spec(
+        vars = "PARAMCD",
+        choices = value_choices(data[["ADLB"]], "PARAMCD", "PARAM"),
+        selected = levels(data[["ADLB"]]$PARAMCD)[1],
+        multiple = FALSE,
+        label = "Select lab:"
       ),
-      tm_g_scatterplot(
-        label = "Same long datasets (same subsets)",
-        x = teal.transform::data_extract_spec(
-          dataname = "ADRS",
-          select = select_spec(
-            choices = variable_choices(data[["ADRS"]], c("AVAL", "BMRKR1", "BMRKR2")),
-            selected = "AVAL",
-            multiple = FALSE,
-            fixed = FALSE,
-            label = "Select variable:"
-          )
-        ),
-        y = teal.transform::data_extract_spec(
-          dataname = "ADRS",
-          select = select_spec(
-            choices = variable_choices(data[["ADRS"]], c("AVAL", "BMRKR1", "BMRKR2")),
-            selected = "BMRKR1",
-            multiple = FALSE,
-            fixed = FALSE,
-            label = "Select variable:"
-          )
-        ),
-        color_by = teal.transform::data_extract_spec(
-          dataname = "ADRS",
-          select = select_spec(
-            choices = variable_choices(data[["ADRS"]], c("AGE", "SEX", "RACE")),
-            selected = NULL,
-            multiple = FALSE,
-            fixed = FALSE,
-            label = "Select variable:"
-          )
-        )
+      filter_spec(
+        vars = "AVISIT",
+        choices = levels(data[["ADLB"]]$AVISIT),
+        selected = levels(data[["ADLB"]]$AVISIT)[1],
+        multiple = FALSE,
+        label = "Select visit:"
+      )
+    ),
+    select = select_spec(
+      choices = "AVAL",
+      selected = "AVAL",
+      multiple = FALSE,
+      fixed = TRUE
+    )
+  ),
+  color_by = data_extract_spec(
+    dataname = "ADLB",
+    filter = list(
+      filter_spec(
+        vars = "PARAMCD",
+        choices = value_choices(data[["ADLB"]], "PARAMCD", "PARAM"),
+        selected = levels(data[["ADLB"]]$PARAMCD)[1],
+        multiple = FALSE,
+        label = "Select lab:"
       ),
-      tm_g_scatterplot(
-        label = "Same long datasets (different subsets)",
-        x = teal.transform::data_extract_spec(
-          dataname = "ADLB",
-          filter = list(
-            filter_spec(
-              vars = "PARAMCD",
-              choices = value_choices(data[["ADLB"]], "PARAMCD", "PARAM"),
-              selected = levels(data[["ADLB"]]$PARAMCD)[1],
-              multiple = FALSE,
-              label = "Select lab:"
-            ),
-            filter_spec(
-              vars = "AVISIT",
-              choices = levels(data[["ADLB"]]$AVISIT),
-              selected = levels(data[["ADLB"]]$AVISIT)[1],
-              multiple = FALSE,
-              label = "Select visit:"
-            )
-          ),
-          select = select_spec(
-            choices = "AVAL",
-            selected = "AVAL",
-            multiple = FALSE,
-            fixed = TRUE
-          )
-        ),
-        y = teal.transform::data_extract_spec(
-          dataname = "ADLB",
-          filter = list(
-            filter_spec(
-              vars = "PARAMCD",
-              choices = value_choices(data[["ADLB"]], "PARAMCD", "PARAM"),
-              selected = levels(data[["ADLB"]]$PARAMCD)[1],
-              multiple = FALSE,
-              label = "Select lab:"
-            ),
-            filter_spec(
-              vars = "AVISIT",
-              choices = levels(data[["ADLB"]]$AVISIT),
-              selected = levels(data[["ADLB"]]$AVISIT)[1],
-              multiple = FALSE,
-              label = "Select visit:"
-            )
-          ),
-          select = select_spec(
-            choices = "AVAL",
-            selected = "AVAL",
-            multiple = FALSE,
-            fixed = TRUE
-          )
-        ),
-        color_by = teal.transform::data_extract_spec(
-          dataname = "ADLB",
-          filter = list(
-            filter_spec(
-              vars = "PARAMCD",
-              choices = value_choices(data[["ADLB"]], "PARAMCD", "PARAM"),
-              selected = levels(data[["ADLB"]]$PARAMCD)[1],
-              multiple = FALSE,
-              label = "Select lab:"
-            ),
-            filter_spec(
-              vars = "AVISIT",
-              choices = levels(data[["ADLB"]]$AVISIT),
-              selected = levels(data[["ADLB"]]$AVISIT)[1],
-              multiple = FALSE,
-              label = "Select visit:"
-            )
-          ),
-          select = select_spec(
-            choices = variable_choices(data[["ADLB"]], c("RACE", "SEX")),
-            selected = "SEX",
-            multiple = FALSE,
-            fixed = FALSE,
-            label = "Select variable:"
-          )
-        )
+      filter_spec(
+        vars = "AVISIT",
+        choices = levels(data[["ADLB"]]$AVISIT),
+        selected = levels(data[["ADLB"]]$AVISIT)[1],
+        multiple = FALSE,
+        label = "Select visit:"
       )
+    ),
+    select = select_spec(
+      choices = variable_choices(data[["ADLB"]], c("RACE", "SEX")),
+      selected = "SEX",
+      multiple = FALSE,
+      fixed = FALSE,
+      label = "Select variable:"
+    )
+  )
+)
+
+# initialize the app
+app <- init(
+  data = data,
+  modules = modules(
+    modules(
+      label = "Scatterplot",
+      mod1,
+      mod2,
+      mod3,
+      mod4,
+      mod5,
+      mod6
     )
   )
 )
 ```
 
-## Run the app
+## 4 - Run the app
 
-A simple `shiny::shinyApp` call will let you run the app.
-Note that app is only displayed when running this code inside an R session.
+A simple `shiny::shinyApp()` call will let you run the app.
+Note that app is only displayed when running this code inside an `R` session.
 
-```{r, eval = ggextra_available, echo=TRUE}
+```{r, echo=TRUE, results="hide"}
 shinyApp(app$ui, app$server, options = list(height = 1024, width = 1024))
 ```
+
+<img src="images/app-using-scatterplot.png" style = "display: block; margin: 0px; width: 100%"/>

From ee8cd14ef449772da66bc2efa15ef6c3777e502e Mon Sep 17 00:00:00 2001
From: Aleksander Chlebowski <114988527+chlebowa@users.noreply.github.com>
Date: Wed, 28 Feb 2024 08:53:59 +0100
Subject: [PATCH 43/62] 641 non exported functions (#680)
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

Closes #641

Dropped examples for non-exported functions. There were only a few.

Cleaned up a bit. There was a lot of duplication in `create_sparklines`
docs, for instance.

Moved `@export` tags to always be the last ones before function
definition.

---------

Signed-off-by: Aleksander Chlebowski <114988527+chlebowa@users.noreply.github.com>
Co-authored-by: André Veríssimo <211358+averissimo@users.noreply.github.com>
Co-authored-by: Marcin <133694481+m7pr@users.noreply.github.com>
---
 R/tm_file_viewer.R         |  17 +-
 R/tm_front_page.R          |  12 +-
 R/tm_g_bivariate.R         |   2 +-
 R/tm_g_scatterplotmatrix.R |   2 +
 R/tm_missing_data.R        |   2 +-
 R/tm_variable_browser.R    | 415 +++++++++++++++++++------------------
 R/utils.R                  |  52 ++---
 R/zzz.R                    |   1 +
 man/call_fun_dots.Rd       |  18 +-
 man/create_sparklines.Rd   |  32 +--
 man/plot_var_summary.Rd    |   2 +-
 man/tm_file_viewer.Rd      |  19 +-
 man/tm_front_page.Rd       |  13 +-
 man/tm_g_bivariate.Rd      |   2 +-
 man/tm_missing_data.Rd     |   2 +-
 man/var_missings_info.Rd   |   6 +-
 man/var_summary_table.Rd   |   2 +-
 man/variable_type_icons.Rd |  14 +-
 man/varname_w_label.Rd     |   9 +-
 19 files changed, 292 insertions(+), 330 deletions(-)

diff --git a/R/tm_file_viewer.R b/R/tm_file_viewer.R
index ad6111657..232a3ff0d 100644
--- a/R/tm_file_viewer.R
+++ b/R/tm_file_viewer.R
@@ -8,18 +8,20 @@
 #' @inheritParams shared_params
 #' @param input_path (`list`) of the input paths, optional. Each element can be:
 #'
-#' 1. Specific path to files of accepted formats
-#' 2. A directory or a URL
+#' @inherit shared_params return
 #'
-#' The paths can be specified as absolute paths or relative to the running
-#' directory of the application.
+#' Paths can be specified as absolute paths or relative to the running directory of the application.
 #' Default to the current working directory if not supplied.
 #'
-#' @inherit shared_params return
-#'
 #' @examples
+#' data <- teal_data()
+#' data <- within(data, {
+#'   data <- data.frame(1)
+#' })
+#' datanames(data) <- c("data")
+#'
 #' app <- init(
-#'   data = teal_data(data = 1), # Mock dataset to initialize the app without error
+#'   data = data
 #'   modules = modules(
 #'     tm_file_viewer(
 #'       input_path = list(
@@ -34,6 +36,7 @@
 #' if (interactive()) {
 #'   shinyApp(app$ui, app$server)
 #' }
+#'
 #' @export
 #'
 tm_file_viewer <- function(label = "File Viewer Module",
diff --git a/R/tm_front_page.R b/R/tm_front_page.R
index 028bc4673..9ce3464c8 100644
--- a/R/tm_front_page.R
+++ b/R/tm_front_page.R
@@ -15,17 +15,17 @@
 #' element, if named the name is shown first in bold, followed by the value.
 #' @param show_metadata (`logical`) indicating whether the metadata of the datasets be available on the module.
 #'
-#' @examples
+#' @inherit shared_params return
 #'
+#' @examples
 #' data <- teal_data()
 #' data <- within(data, {
 #'   require(nestcolor)
-#'   ADSL <- teal.modules.general::rADSL
+#'   ADSL <- rADSL
 #'   attr(ADSL, "metadata") <- list("Author" = "NEST team", "data_source" = "synthetic data")
 #' })
-#' datanames <- c("ADSL")
-#' datanames(data) <- datanames
-#' join_keys(data) <- default_cdisc_join_keys[datanames]
+#' datanames(data) <- "ADSL"
+#' join_keys(data) <- default_cdisc_join_keys[datanames(data)]
 #'
 #' table_1 <- data.frame(Info = c("A", "B"), Text = c("A", "B"))
 #' table_2 <- data.frame(`Column 1` = c("C", "D"), `Column 2` = c(5.5, 6.6), `Column 3` = c("A", "B"))
@@ -40,7 +40,7 @@
 #' app <- init(
 #'   data = data,
 #'   modules = modules(
-#'     teal.modules.general::tm_front_page(
+#'     tm_front_page(
 #'       header_text = c(
 #'         "Important information" = "It can go here.",
 #'         "Other information" = "Can go here."
diff --git a/R/tm_g_bivariate.R b/R/tm_g_bivariate.R
index 1abad45c2..966650e67 100644
--- a/R/tm_g_bivariate.R
+++ b/R/tm_g_bivariate.R
@@ -47,7 +47,7 @@
 #' @examples
 #' library(teal.widgets)
 #'
-#' # general data exapmle
+#' # general data example
 #' data <- teal_data()
 #' data <- within(data, {
 #'   require(nestcolor)
diff --git a/R/tm_g_scatterplotmatrix.R b/R/tm_g_scatterplotmatrix.R
index 96b99998e..3325da87d 100644
--- a/R/tm_g_scatterplotmatrix.R
+++ b/R/tm_g_scatterplotmatrix.R
@@ -477,6 +477,7 @@ srv_g_scatterplotmatrix <- function(id, data, reporter, filter_panel_api, variab
 #' stats::cor.test(x, y, na.action = "na.fail")
 #' stats::cor.test(~ x + y,  na.action = "na.fail")
 #' ```
+#'
 #' @param x,y (`numeric`) vectors of data values. `x` and `y` must have the same length.
 #' @param .f (`function`) function that accepts x and y as formula input `~ x + y`.
 #' Default `stats::cor.test`.
@@ -485,6 +486,7 @@ srv_g_scatterplotmatrix <- function(id, data, reporter, filter_panel_api, variab
 #' @param round_pval (`integer(1)`) optional. Number of decimal places to use when rounding the p-value.
 #'
 #' @return Character with stats. For [stats::cor.test()] correlation coefficient and p-value.
+#'
 #' @examples
 #' set.seed(1)
 #' x <- runif(25, 0, 1)
diff --git a/R/tm_missing_data.R b/R/tm_missing_data.R
index 7273fd471..89ef30f82 100644
--- a/R/tm_missing_data.R
+++ b/R/tm_missing_data.R
@@ -1,6 +1,6 @@
 #' `teal` module: Missing data analysis
 #'
-#' Module analyzes missing data in `data.frame`s to help users explore missing observations and
+#' This module analyzes missing data in `data.frame`s to help users explore missing observations and
 #' gain insights into the completeness of their data.
 #' It is useful for clinical data analysis within the context of `CDISC` standards and
 #' adaptable for general data analysis purposes.
diff --git a/R/tm_variable_browser.R b/R/tm_variable_browser.R
index 384d9fb6f..6c4f9f289 100644
--- a/R/tm_variable_browser.R
+++ b/R/tm_variable_browser.R
@@ -527,197 +527,16 @@ srv_variable_browser <- function(id,
   })
 }
 
-#' Summarizes missings occurrence
+#' Summarize NAs.
 #'
-#' Summarizes missings occurrence in vector.
+#' Summarizes occurrence of missing values in vector.
 #' @param x vector of any type and length
-#' @return Text describing \code{NA} occurrence.
+#' @return Character string describing `NA` occurrence.
 #' @keywords internal
 var_missings_info <- function(x) {
   sprintf("%s [%s%%]", sum(is.na(x)), round(mean(is.na(x) * 100), 2))
 }
 
-#' S3 generic for \code{sparkline} widget HTML
-#'
-#' Generates the \code{sparkline} HTML code corresponding to the input array.
-#' For numeric variables creates a box plot, for character and factors - bar plot.
-#' Produces an empty string for variables of other types.
-#'
-#' @param arr vector of any type and length
-#' @param width \code{numeric} the width of the \code{sparkline} widget (pixels)
-#' @param ... \code{list} additional options passed to bar plots of \code{jquery.sparkline};  see
-#' \href{https://omnipotent.net/jquery.sparkline/#common}{\code{jquery.sparkline docs}}
-#' @param bar_spacing \code{numeric} the spacing between the bars (in pixels)
-#' @param bar_width \code{numeric} the width of the bars (in pixels)
-#'
-#' @return character variable containing the HTML code of the \code{sparkline} HTML widget
-#' @keywords internal
-create_sparklines <- function(arr, width = 150, ...) {
-  if (all(is.null(arr))) {
-    return("")
-  }
-  UseMethod("create_sparklines")
-}
-
-#' @export
-#' @rdname create_sparklines
-create_sparklines.default <- function(arr, width = 150, ...) {
-  as.character(tags$code("unsupported variable type", class = "text-blue"))
-}
-
-#' @export
-#' @rdname create_sparklines
-create_sparklines.Date <- function(arr, width = 150, bar_spacing = 5, bar_width = 20, ...) {
-  arr_num <- as.numeric(arr)
-  arr_num <- sort(arr_num, decreasing = FALSE, method = "radix")
-  binwidth <- get_bin_width(arr_num, 1)
-  bins <- floor(diff(range(arr_num)) / binwidth) + 1
-  if (all(is.na(bins))) {
-    return(as.character(tags$code("only NA", class = "text-blue")))
-  } else if (bins == 1) {
-    return(as.character(tags$code("one date", class = "text-blue")))
-  }
-  counts <- as.vector(unname(base::table(cut(arr_num, breaks = bins))))
-  max_value <- max(counts)
-
-  start_bins <- as.integer(seq(1, length(arr_num), length.out = bins))
-  labels_start <- as.character(as.Date(arr_num[start_bins], origin = as.Date("1970-01-01")))
-  labels <- paste("Start:", labels_start)
-
-  sparkline::spk_chr(
-    unname(counts),
-    type = "bar",
-    chartRangeMin = 0,
-    chartRangeMax = max_value,
-    width = width,
-    barWidth = bar_width,
-    barSpacing = bar_spacing,
-    tooltipFormatter = custom_sparkline_formatter(labels, counts)
-  )
-}
-
-#' @export
-#' @rdname create_sparklines
-create_sparklines.POSIXct <- function(arr, width = 150, bar_spacing = 5, bar_width = 20, ...) {
-  arr_num <- as.numeric(arr)
-  arr_num <- sort(arr_num, decreasing = FALSE, method = "radix")
-  binwidth <- get_bin_width(arr_num, 1)
-  bins <- floor(diff(range(arr_num)) / binwidth) + 1
-  if (all(is.na(bins))) {
-    return(as.character(tags$code("only NA", class = "text-blue")))
-  } else if (bins == 1) {
-    return(as.character(tags$code("one date-time", class = "text-blue")))
-  }
-  counts <- as.vector(unname(base::table(cut(arr_num, breaks = bins))))
-  max_value <- max(counts)
-
-  start_bins <- as.integer(seq(1, length(arr_num), length.out = bins))
-  labels_start <- as.character(format(as.POSIXct(arr_num[start_bins], origin = as.Date("1970-01-01")), "%Y-%m-%d"))
-  labels <- paste("Start:", labels_start)
-
-  sparkline::spk_chr(
-    unname(counts),
-    type = "bar",
-    chartRangeMin = 0,
-    chartRangeMax = max_value,
-    width = width,
-    barWidth = bar_width,
-    barSpacing = bar_spacing,
-    tooltipFormatter = custom_sparkline_formatter(labels, counts)
-  )
-}
-
-#' @export
-#' @rdname create_sparklines
-create_sparklines.POSIXlt <- function(arr, width = 150, bar_spacing = 5, bar_width = 20, ...) {
-  arr_num <- as.numeric(arr)
-  arr_num <- sort(arr_num, decreasing = FALSE, method = "radix")
-  binwidth <- get_bin_width(arr_num, 1)
-  bins <- floor(diff(range(arr_num)) / binwidth) + 1
-  if (all(is.na(bins))) {
-    return(as.character(tags$code("only NA", class = "text-blue")))
-  } else if (bins == 1) {
-    return(as.character(tags$code("one date-time", class = "text-blue")))
-  }
-  counts <- as.vector(unname(base::table(cut(arr_num, breaks = bins))))
-  max_value <- max(counts)
-
-  start_bins <- as.integer(seq(1, length(arr_num), length.out = bins))
-  labels_start <- as.character(format(as.POSIXct(arr_num[start_bins], origin = as.Date("1970-01-01")), "%Y-%m-%d"))
-  labels <- paste("Start:", labels_start)
-
-  sparkline::spk_chr(
-    unname(counts),
-    type = "bar",
-    chartRangeMin = 0,
-    chartRangeMax = max_value,
-    width = width,
-    barWidth = bar_width,
-    barSpacing = bar_spacing,
-    tooltipFormatter = custom_sparkline_formatter(labels, counts)
-  )
-}
-
-#' @export
-#' @rdname create_sparklines
-create_sparklines.character <- function(arr, ...) {
-  create_sparklines(as.factor(arr))
-}
-
-#' @export
-#' @rdname create_sparklines
-create_sparklines.logical <- function(arr, ...) {
-  create_sparklines(as.factor(arr))
-}
-
-#' @export
-#' @rdname create_sparklines
-create_sparklines.factor <- function(arr, width = 150, bar_spacing = 5, bar_width = 20, ...) {
-  decreasing_order <- TRUE
-
-  counts <- table(arr)
-  if (length(counts) >= 100) {
-    return(as.character(tags$code("> 99 levels", class = "text-blue")))
-  } else if (length(counts) == 0) {
-    return(as.character(tags$code("no levels", class = "text-blue")))
-  } else if (length(counts) == 1) {
-    return(as.character(tags$code("one level", class = "text-blue")))
-  }
-
-  # Summarize the occurences of different levels
-  # and get the maximum and minimum number of occurences
-  # This is needed for the sparkline to correctly display the bar plots
-  # Otherwise they are cropped
-  counts <- sort(counts, decreasing = decreasing_order, method = "radix")
-  max_value <- if (decreasing_order) counts[1] else counts[length[counts]]
-  max_value <- unname(max_value)
-
-  sparkline::spk_chr(
-    unname(counts),
-    type = "bar",
-    chartRangeMin = 0,
-    chartRangeMax = max_value,
-    width = width,
-    barWidth = bar_width,
-    barSpacing = bar_spacing,
-    tooltipFormatter = custom_sparkline_formatter(names(counts), as.vector(counts))
-  )
-}
-
-#' @export
-#' @rdname create_sparklines
-create_sparklines.numeric <- function(arr, width = 150, ...) {
-  if (any(is.infinite(arr))) {
-    return(as.character(tags$code("infinite values", class = "text-blue")))
-  }
-  if (length(arr) > 100000) {
-    return(as.character(tags$code("Too many rows (>100000)", class = "text-blue")))
-  }
-
-  arr <- arr[!is.na(arr)]
-  sparkline::spk_chr(unname(arr), type = "box", width = width, ...)
-}
-
 #' Summarizes variable
 #'
 #' Creates html summary with statistics relevant to data type. For numeric values it returns central
@@ -725,10 +544,10 @@ create_sparklines.numeric <- function(arr, width = 150, ...) {
 #' number of levels.
 #'
 #' @param x vector of any type
-#' @param numeric_as_factor \code{logical} should the numeric variable be treated as a factor
-#' @param dt_rows \code{numeric} current/latest `DT` page length
+#' @param numeric_as_factor `logical` should the numeric variable be treated as a factor
+#' @param dt_rows `numeric` current/latest `DT` page length
 #' @param outlier_definition If 0 no outliers are removed, otherwise
-#'   outliers (those more than outlier_definition*IQR below/above Q1/Q3 be removed)
+#'   outliers (those more than `outlier_definition*IQR below/above Q1/Q3` be removed)
 #' @return text with simple statistics.
 #' @keywords internal
 var_summary_table <- function(x, numeric_as_factor, dt_rows, outlier_definition) {
@@ -821,7 +640,7 @@ var_summary_table <- function(x, numeric_as_factor, dt_rows, outlier_definition)
 #' @param wrap_character (`numeric`) number of characters at which to wrap text values of `var`
 #' @param numeric_as_factor (`logical`) should the numeric variable be treated as a factor
 #' @param display_density (`logical`) should density estimation be displayed for numeric values
-#' @param remove_NA_hist (`logical`) should (`NA`) values be removed for histogram of factor like variables
+#' @param remove_NA_hist (`logical`) should `NA` values be removed for histogram of factor like variables
 #' @param outlier_definition if 0 no outliers are removed, otherwise
 #'   outliers (those more than outlier_definition*IQR below/above Q1/Q3 be removed)
 #' @param records_for_factor (`numeric`) if the number of factor levels is >= than this value then
@@ -1239,20 +1058,6 @@ get_bin_width <- function(x_vec, scaling_factor = 2) {
   if (isTRUE(x_span / binwidth >= 2)) binwidth else x_span / 2
 }
 
-#' @noRd
-#' @keywords internal
-custom_sparkline_formatter <- function(labels, counts) {
-  htmlwidgets::JS(
-    sprintf(
-      "function(sparkline, options, field) {
-        return 'ID: ' + %s[field[0].offset] + '<br>' + 'Count: ' + %s[field[0].offset];
-        }",
-      jsonlite::toJSON(labels),
-      jsonlite::toJSON(counts)
-    )
-  )
-}
-
 #' Removes the outlier observation from an array
 #'
 #' @param var (`numeric`) a numeric vector
@@ -1268,3 +1073,209 @@ remove_outliers_from <- function(var, outlier_definition) {
   iqr <- q1_q3[2] - q1_q3[1]
   var[var >= q1_q3[1] - outlier_definition * iqr & var <= q1_q3[2] + outlier_definition * iqr]
 }
+
+
+# sparklines ----
+
+#' S3 generic for `sparkline` widget HTML
+#'
+#' Generates the `sparkline` HTML code corresponding to the input array.
+#' For numeric variables creates a box plot, for character and factors - bar plot.
+#' Produces an empty string for variables of other types.
+#'
+#' @param arr vector of any type and length
+#' @param width `numeric` the width of the `sparkline` widget (pixels)
+#' @param bar_spacing `numeric` the spacing between the bars (in pixels)
+#' @param bar_width `numeric` the width of the bars (in pixels)
+#' @param ... `list` additional options passed to bar plots of `jquery.sparkline`;
+#'                   see [`jquery.sparkline docs`](https://omnipotent.net/jquery.sparkline/#common)
+#'
+#' @return Character string containing HTML code of the `sparkline` HTML widget.
+#' @keywords internal
+create_sparklines <- function(arr, width = 150, ...) {
+  if (all(is.null(arr))) {
+    return("")
+  }
+  UseMethod("create_sparklines")
+}
+
+#' @rdname create_sparklines
+#' @keywords internal
+#' @export
+create_sparklines.logical <- function(arr, ...) {
+  create_sparklines(as.factor(arr))
+}
+
+#' @rdname create_sparklines
+#' @keywords internal
+#' @export
+create_sparklines.numeric <- function(arr, width = 150, ...) {
+  if (any(is.infinite(arr))) {
+    return(as.character(tags$code("infinite values", class = "text-blue")))
+  }
+  if (length(arr) > 100000) {
+    return(as.character(tags$code("Too many rows (>100000)", class = "text-blue")))
+  }
+
+  arr <- arr[!is.na(arr)]
+  sparkline::spk_chr(unname(arr), type = "box", width = width, ...)
+}
+
+#' @rdname create_sparklines
+#' @keywords internal
+#' @export
+create_sparklines.character <- function(arr, ...) {
+  return(create_sparklines(as.factor(arr)))
+}
+
+
+#' @rdname create_sparklines
+#' @keywords internal
+#' @export
+create_sparklines.factor <- function(arr, width = 150, bar_spacing = 5, bar_width = 20, ...) {
+  decreasing_order <- TRUE
+
+  counts <- table(arr)
+  if (length(counts) >= 100) {
+    return(as.character(tags$code("> 99 levels", class = "text-blue")))
+  } else if (length(counts) == 0) {
+    return(as.character(tags$code("no levels", class = "text-blue")))
+  } else if (length(counts) == 1) {
+    return(as.character(tags$code("one level", class = "text-blue")))
+  }
+
+  # Summarize the occurences of different levels
+  # and get the maximum and minimum number of occurences
+  # This is needed for the sparkline to correctly display the bar plots
+  # Otherwise they are cropped
+  counts <- sort(counts, decreasing = decreasing_order, method = "radix")
+  max_value <- if (decreasing_order) counts[1] else counts[length[counts]]
+  max_value <- unname(max_value)
+
+  sparkline::spk_chr(
+    unname(counts),
+    type = "bar",
+    chartRangeMin = 0,
+    chartRangeMax = max_value,
+    width = width,
+    barWidth = bar_width,
+    barSpacing = bar_spacing,
+    tooltipFormatter = custom_sparkline_formatter(names(counts), as.vector(counts))
+  )
+}
+
+#' @rdname create_sparklines
+#' @keywords internal
+#' @export
+create_sparklines.Date <- function(arr, width = 150, bar_spacing = 5, bar_width = 20, ...) {
+  arr_num <- as.numeric(arr)
+  arr_num <- sort(arr_num, decreasing = FALSE, method = "radix")
+  binwidth <- get_bin_width(arr_num, 1)
+  bins <- floor(diff(range(arr_num)) / binwidth) + 1
+  if (all(is.na(bins))) {
+    return(as.character(tags$code("only NA", class = "text-blue")))
+  } else if (bins == 1) {
+    return(as.character(tags$code("one date", class = "text-blue")))
+  }
+  counts <- as.vector(unname(base::table(cut(arr_num, breaks = bins))))
+  max_value <- max(counts)
+
+  start_bins <- as.integer(seq(1, length(arr_num), length.out = bins))
+  labels_start <- as.character(as.Date(arr_num[start_bins], origin = as.Date("1970-01-01")))
+  labels <- paste("Start:", labels_start)
+
+  sparkline::spk_chr(
+    unname(counts),
+    type = "bar",
+    chartRangeMin = 0,
+    chartRangeMax = max_value,
+    width = width,
+    barWidth = bar_width,
+    barSpacing = bar_spacing,
+    tooltipFormatter = custom_sparkline_formatter(labels, counts)
+  )
+}
+
+#' @rdname create_sparklines
+#' @keywords internal
+#' @export
+create_sparklines.POSIXct <- function(arr, width = 150, bar_spacing = 5, bar_width = 20, ...) {
+  arr_num <- as.numeric(arr)
+  arr_num <- sort(arr_num, decreasing = FALSE, method = "radix")
+  binwidth <- get_bin_width(arr_num, 1)
+  bins <- floor(diff(range(arr_num)) / binwidth) + 1
+  if (all(is.na(bins))) {
+    return(as.character(tags$code("only NA", class = "text-blue")))
+  } else if (bins == 1) {
+    return(as.character(tags$code("one date-time", class = "text-blue")))
+  }
+  counts <- as.vector(unname(base::table(cut(arr_num, breaks = bins))))
+  max_value <- max(counts)
+
+  start_bins <- as.integer(seq(1, length(arr_num), length.out = bins))
+  labels_start <- as.character(format(as.POSIXct(arr_num[start_bins], origin = as.Date("1970-01-01")), "%Y-%m-%d"))
+  labels <- paste("Start:", labels_start)
+
+  sparkline::spk_chr(
+    unname(counts),
+    type = "bar",
+    chartRangeMin = 0,
+    chartRangeMax = max_value,
+    width = width,
+    barWidth = bar_width,
+    barSpacing = bar_spacing,
+    tooltipFormatter = custom_sparkline_formatter(labels, counts)
+  )
+}
+
+#' @rdname create_sparklines
+#' @keywords internal
+#' @export
+create_sparklines.POSIXlt <- function(arr, width = 150, bar_spacing = 5, bar_width = 20, ...) {
+  arr_num <- as.numeric(arr)
+  arr_num <- sort(arr_num, decreasing = FALSE, method = "radix")
+  binwidth <- get_bin_width(arr_num, 1)
+  bins <- floor(diff(range(arr_num)) / binwidth) + 1
+  if (all(is.na(bins))) {
+    return(as.character(tags$code("only NA", class = "text-blue")))
+  } else if (bins == 1) {
+    return(as.character(tags$code("one date-time", class = "text-blue")))
+  }
+  counts <- as.vector(unname(base::table(cut(arr_num, breaks = bins))))
+  max_value <- max(counts)
+
+  start_bins <- as.integer(seq(1, length(arr_num), length.out = bins))
+  labels_start <- as.character(format(as.POSIXct(arr_num[start_bins], origin = as.Date("1970-01-01")), "%Y-%m-%d"))
+  labels <- paste("Start:", labels_start)
+
+  sparkline::spk_chr(
+    unname(counts),
+    type = "bar",
+    chartRangeMin = 0,
+    chartRangeMax = max_value,
+    width = width,
+    barWidth = bar_width,
+    barSpacing = bar_spacing,
+    tooltipFormatter = custom_sparkline_formatter(labels, counts)
+  )
+}
+
+#' @rdname create_sparklines
+#' @keywords internal
+#' @export
+create_sparklines.default <- function(arr, width = 150, ...) {
+  as.character(tags$code("unsupported variable type", class = "text-blue"))
+}
+
+
+custom_sparkline_formatter <- function(labels, counts) {
+  htmlwidgets::JS(
+    sprintf(
+      "function(sparkline, options, field) {
+        return 'ID: ' + %s[field[0].offset] + '<br>' + 'Count: ' + %s[field[0].offset];
+        }",
+      jsonlite::toJSON(labels),
+      jsonlite::toJSON(counts)
+    )
+  )
+}
diff --git a/R/utils.R b/R/utils.R
index 1b78f47e7..b1b1661d5 100644
--- a/R/utils.R
+++ b/R/utils.R
@@ -128,26 +128,15 @@ add_facet_labels <- function(p, xfacet_label = NULL, yfacet_label = NULL) {
   })
 }
 
-#' Call a function with a character vector for the \code{...} argument
+#' Call a function with a character vector for the `...` argument
 #'
-#' @param fun (`character`) Name of a function where the \code{...} argument
-#'   shall be replaced by values from \code{str_args}.
-#' @param str_args (`character`) A character vector that the function shall
-#'  be executed with
+#' @param fun (`character`) Name of a function where the `...` argument shall be replaced by values from `str_args`.
+#' @param str_args (`character`) A character vector that the function shall be executed with
 #'
-#' @return Call (i.e. expression) of the function provided by \code{fun}
-#'  with arguments provided by \code{str_args}.
-#'
-#' @examples
-#' call_fun_dots <- getFromNamespace("call_fun_dots", "teal.modules.general")
-#'
-#' a <- 1
-#' b <- 2
-#' call_fun_dots("sum", c("a", "b"))
-#' eval(call_fun_dots("sum", c("a", "b")))
+#' @return
+#' Value of call to `fun` with arguments specified in `str_args`.
 #'
 #' @keywords internal
-#'
 call_fun_dots <- function(fun, str_args) {
   do.call("call", c(list(fun), lapply(str_args, as.name)), quote = TRUE)
 }
@@ -156,14 +145,11 @@ call_fun_dots <- function(fun, str_args) {
 #'
 #' @param var_names (`character`) Name of variable to extract labels from.
 #' @param dataset (`dataset`) Name of analysis dataset.
-#' @param prefix (`character`) String to paste to the beginning of the
-#'   variable name with label.
-#' @param suffix (`character`) String to paste to the end of the variable
-#'   name with label.
-#' @param wrap_width (`numeric`) Number of characters to wrap original
-#'   label to. Defaults to 80.
+#' @param prefix,suffix (`character`) String to paste to the beginning/end of the variable name with label.
+#' @param wrap_width (`numeric`) Number of characters to wrap original label to. Defaults to 80.
 #'
 #' @return (`character`) String with variable name and label.
+#'
 #' @keywords internal
 #'
 varname_w_label <- function(var_names,
@@ -208,21 +194,9 @@ shape_names <- c(
 
 #' Get icons to represent variable types in dataset
 #'
-#' @param var_type (`character`)\cr
-#'  of `R` internal types (classes).
-#'
-#' @return Vector of HTML icons corresponding to data type in each column.
-#'
-#' @examples
-#' variable_type_icons <- getFromNamespace("variable_type_icons", "teal.modules.general")
-#'
-#' variable_type_icons(c(
-#'   "integer", "numeric", "logical", "Date", "POSIXct", "POSIXlt",
-#'   "factor", "character", "unknown", ""
-#' ))
-#'
+#' @param var_type (`character`) of R internal types (classes).
+#' @return (`character`) vector of HTML icons corresponding to data type in each column.
 #' @keywords internal
-#'
 variable_type_icons <- function(var_type) {
   checkmate::assert_character(var_type, any.missing = FALSE)
 
@@ -240,7 +214,7 @@ variable_type_icons <- function(var_type) {
   )
   class_to_icon <- lapply(class_to_icon, function(icon_name) toString(icon(icon_name, lib = "font-awesome")))
 
-  res <- unname(vapply(
+  unname(vapply(
     var_type,
     FUN.VALUE = character(1),
     FUN = function(class) {
@@ -253,8 +227,6 @@ variable_type_icons <- function(var_type) {
       }
     }
   ))
-
-  return(res)
 }
 
 #' Include `CSS` files from `/inst/css/` package directory to application header
@@ -276,7 +248,7 @@ include_css_files <- function(pattern = "*") {
   if (length(css_files) == 0) {
     return(NULL)
   }
-  return(shiny::singleton(shiny::tags$head(lapply(css_files, shiny::includeCSS))))
+  shiny::singleton(shiny::tags$head(lapply(css_files, shiny::includeCSS)))
 }
 
 #' JavaScript condition to check if a specific tab is active
diff --git a/R/zzz.R b/R/zzz.R
index f9db273c7..88430df7b 100644
--- a/R/zzz.R
+++ b/R/zzz.R
@@ -2,4 +2,5 @@
   teal.logger::register_logger(namespace = "teal.modules.general")
 }
 
+### global variables
 ggplot_themes <- c("gray", "bw", "linedraw", "light", "dark", "minimal", "classic", "void")
diff --git a/man/call_fun_dots.Rd b/man/call_fun_dots.Rd
index 249ed5438..7905870da 100644
--- a/man/call_fun_dots.Rd
+++ b/man/call_fun_dots.Rd
@@ -7,26 +7,14 @@
 call_fun_dots(fun, str_args)
 }
 \arguments{
-\item{fun}{(\code{character}) Name of a function where the \code{...} argument
-shall be replaced by values from \code{str_args}.}
+\item{fun}{(\code{character}) Name of a function where the \code{...} argument shall be replaced by values from \code{str_args}.}
 
-\item{str_args}{(\code{character}) A character vector that the function shall
-be executed with}
+\item{str_args}{(\code{character}) A character vector that the function shall be executed with}
 }
 \value{
-Call (i.e. expression) of the function provided by \code{fun}
-with arguments provided by \code{str_args}.
+Value of call to \code{fun} with arguments specified in \code{str_args}.
 }
 \description{
 Call a function with a character vector for the \code{...} argument
-}
-\examples{
-call_fun_dots <- getFromNamespace("call_fun_dots", "teal.modules.general")
-
-a <- 1
-b <- 2
-call_fun_dots("sum", c("a", "b"))
-eval(call_fun_dots("sum", c("a", "b")))
-
 }
 \keyword{internal}
diff --git a/man/create_sparklines.Rd b/man/create_sparklines.Rd
index 18cc1080b..e269ffb51 100644
--- a/man/create_sparklines.Rd
+++ b/man/create_sparklines.Rd
@@ -2,48 +2,48 @@
 % Please edit documentation in R/tm_variable_browser.R
 \name{create_sparklines}
 \alias{create_sparklines}
-\alias{create_sparklines.default}
+\alias{create_sparklines.logical}
+\alias{create_sparklines.numeric}
+\alias{create_sparklines.character}
+\alias{create_sparklines.factor}
 \alias{create_sparklines.Date}
 \alias{create_sparklines.POSIXct}
 \alias{create_sparklines.POSIXlt}
-\alias{create_sparklines.character}
-\alias{create_sparklines.logical}
-\alias{create_sparklines.factor}
-\alias{create_sparklines.numeric}
+\alias{create_sparklines.default}
 \title{S3 generic for \code{sparkline} widget HTML}
 \usage{
 create_sparklines(arr, width = 150, ...)
 
-\method{create_sparklines}{default}(arr, width = 150, ...)
+\method{create_sparklines}{logical}(arr, ...)
 
-\method{create_sparklines}{Date}(arr, width = 150, bar_spacing = 5, bar_width = 20, ...)
+\method{create_sparklines}{numeric}(arr, width = 150, ...)
 
-\method{create_sparklines}{POSIXct}(arr, width = 150, bar_spacing = 5, bar_width = 20, ...)
+\method{create_sparklines}{character}(arr, ...)
 
-\method{create_sparklines}{POSIXlt}(arr, width = 150, bar_spacing = 5, bar_width = 20, ...)
+\method{create_sparklines}{factor}(arr, width = 150, bar_spacing = 5, bar_width = 20, ...)
 
-\method{create_sparklines}{character}(arr, ...)
+\method{create_sparklines}{Date}(arr, width = 150, bar_spacing = 5, bar_width = 20, ...)
 
-\method{create_sparklines}{logical}(arr, ...)
+\method{create_sparklines}{POSIXct}(arr, width = 150, bar_spacing = 5, bar_width = 20, ...)
 
-\method{create_sparklines}{factor}(arr, width = 150, bar_spacing = 5, bar_width = 20, ...)
+\method{create_sparklines}{POSIXlt}(arr, width = 150, bar_spacing = 5, bar_width = 20, ...)
 
-\method{create_sparklines}{numeric}(arr, width = 150, ...)
+\method{create_sparklines}{default}(arr, width = 150, ...)
 }
 \arguments{
 \item{arr}{vector of any type and length}
 
 \item{width}{\code{numeric} the width of the \code{sparkline} widget (pixels)}
 
-\item{...}{\code{list} additional options passed to bar plots of \code{jquery.sparkline};  see
-\href{https://omnipotent.net/jquery.sparkline/#common}{\code{jquery.sparkline docs}}}
+\item{...}{\code{list} additional options passed to bar plots of \code{jquery.sparkline};
+see \href{https://omnipotent.net/jquery.sparkline/#common}{\verb{jquery.sparkline docs}}}
 
 \item{bar_spacing}{\code{numeric} the spacing between the bars (in pixels)}
 
 \item{bar_width}{\code{numeric} the width of the bars (in pixels)}
 }
 \value{
-character variable containing the HTML code of the \code{sparkline} HTML widget
+Character string containing HTML code of the \code{sparkline} HTML widget.
 }
 \description{
 Generates the \code{sparkline} HTML code corresponding to the input array.
diff --git a/man/plot_var_summary.Rd b/man/plot_var_summary.Rd
index 423c9297c..0b36bba23 100644
--- a/man/plot_var_summary.Rd
+++ b/man/plot_var_summary.Rd
@@ -28,7 +28,7 @@ density line, for factors it creates frequency plot}
 
 \item{display_density}{(\code{logical}) should density estimation be displayed for numeric values}
 
-\item{remove_NA_hist}{(\code{logical}) should (\code{NA}) values be removed for histogram of factor like variables}
+\item{remove_NA_hist}{(\code{logical}) should \code{NA} values be removed for histogram of factor like variables}
 
 \item{outlier_definition}{if 0 no outliers are removed, otherwise
 outliers (those more than outlier_definition*IQR below/above Q1/Q3 be removed)}
diff --git a/man/tm_file_viewer.Rd b/man/tm_file_viewer.Rd
index 8386b5917..ff994a4e8 100644
--- a/man/tm_file_viewer.Rd
+++ b/man/tm_file_viewer.Rd
@@ -13,15 +13,7 @@ tm_file_viewer(
 \item{label}{(\code{character(1)}) Label shown in the navigation item for the module or module group.
 For \code{modules()} defaults to \code{"root"}. See \code{Details}.}
 
-\item{input_path}{(\code{list}) of the input paths, optional. Each element can be:
-\enumerate{
-\item Specific path to files of accepted formats
-\item A directory or a URL
-}
-
-The paths can be specified as absolute paths or relative to the running
-directory of the application.
-Default to the current working directory if not supplied.}
+\item{input_path}{(\code{list}) of the input paths, optional. Each element can be:}
 }
 \value{
 Object of class \code{teal_module} to be used in \code{teal} applications.
@@ -32,8 +24,14 @@ Supported formats include text formats, \code{PDF}, \code{PNG} \code{APNG},
 \code{JPEG} \code{SVG}, \code{WEBP}, \code{GIF} and \code{BMP}.
 }
 \examples{
+data <- teal_data()
+data <- within(data, {
+  data <- data.frame(1)
+})
+datanames(data) <- c("data")
+
 app <- init(
-  data = teal_data(data = 1), # Mock dataset to initialize the app without error
+  data = data
   modules = modules(
     tm_file_viewer(
       input_path = list(
@@ -48,4 +46,5 @@ app <- init(
 if (interactive()) {
   shinyApp(app$ui, app$server)
 }
+
 }
diff --git a/man/tm_front_page.Rd b/man/tm_front_page.Rd
index 8043dc80a..31ba69019 100644
--- a/man/tm_front_page.Rd
+++ b/man/tm_front_page.Rd
@@ -32,21 +32,22 @@ element, if named the name is shown first in bold, followed by the value.}
 
 \item{show_metadata}{(\code{logical}) indicating whether the metadata of the datasets be available on the module.}
 }
+\value{
+Object of class \code{teal_module} to be used in \code{teal} applications.
+}
 \description{
 Creates a simple front page for \code{teal} applications, displaying
 introductory text, tables, additional \code{html} or \code{shiny} tags, and footnotes.
 }
 \examples{
-
 data <- teal_data()
 data <- within(data, {
   require(nestcolor)
-  ADSL <- teal.modules.general::rADSL
+  ADSL <- rADSL
   attr(ADSL, "metadata") <- list("Author" = "NEST team", "data_source" = "synthetic data")
 })
-datanames <- c("ADSL")
-datanames(data) <- datanames
-join_keys(data) <- default_cdisc_join_keys[datanames]
+datanames(data) <- "ADSL"
+join_keys(data) <- default_cdisc_join_keys[datanames(data)]
 
 table_1 <- data.frame(Info = c("A", "B"), Text = c("A", "B"))
 table_2 <- data.frame(`Column 1` = c("C", "D"), `Column 2` = c(5.5, 6.6), `Column 3` = c("A", "B"))
@@ -61,7 +62,7 @@ table_input <- list(
 app <- init(
   data = data,
   modules = modules(
-    teal.modules.general::tm_front_page(
+    tm_front_page(
       header_text = c(
         "Important information" = "It can go here.",
         "Other information" = "Can go here."
diff --git a/man/tm_g_bivariate.Rd b/man/tm_g_bivariate.Rd
index 419f965c3..8929db567 100644
--- a/man/tm_g_bivariate.Rd
+++ b/man/tm_g_bivariate.Rd
@@ -115,7 +115,7 @@ For more examples, please see the vignette "Using bivariate plot" via
 \examples{
 library(teal.widgets)
 
-# general data exapmle
+# general data example
 data <- teal_data()
 data <- within(data, {
   require(nestcolor)
diff --git a/man/tm_missing_data.Rd b/man/tm_missing_data.Rd
index 0ef2b28c9..a5b463bcb 100644
--- a/man/tm_missing_data.Rd
+++ b/man/tm_missing_data.Rd
@@ -49,7 +49,7 @@ with text placed before the output to put the output into context. For example a
 adding context or further instructions. Elements like \code{shiny::helpText()} are useful.}
 }
 \description{
-Module analyzes missing data in \code{data.frame}s to help users explore missing observations and
+This module analyzes missing data in \code{data.frame}s to help users explore missing observations and
 gain insights into the completeness of their data.
 It is useful for clinical data analysis within the context of \code{CDISC} standards and
 adaptable for general data analysis purposes.
diff --git a/man/var_missings_info.Rd b/man/var_missings_info.Rd
index 70426bf8d..d675c99a3 100644
--- a/man/var_missings_info.Rd
+++ b/man/var_missings_info.Rd
@@ -2,7 +2,7 @@
 % Please edit documentation in R/tm_variable_browser.R
 \name{var_missings_info}
 \alias{var_missings_info}
-\title{Summarizes missings occurrence}
+\title{Summarize NAs.}
 \usage{
 var_missings_info(x)
 }
@@ -10,9 +10,9 @@ var_missings_info(x)
 \item{x}{vector of any type and length}
 }
 \value{
-Text describing \code{NA} occurrence.
+Character string describing \code{NA} occurrence.
 }
 \description{
-Summarizes missings occurrence in vector.
+Summarizes occurrence of missing values in vector.
 }
 \keyword{internal}
diff --git a/man/var_summary_table.Rd b/man/var_summary_table.Rd
index 99cd3d26d..f13ceef22 100644
--- a/man/var_summary_table.Rd
+++ b/man/var_summary_table.Rd
@@ -14,7 +14,7 @@ var_summary_table(x, numeric_as_factor, dt_rows, outlier_definition)
 \item{dt_rows}{\code{numeric} current/latest \code{DT} page length}
 
 \item{outlier_definition}{If 0 no outliers are removed, otherwise
-outliers (those more than outlier_definition*IQR below/above Q1/Q3 be removed)}
+outliers (those more than \verb{outlier_definition*IQR below/above Q1/Q3} be removed)}
 }
 \value{
 text with simple statistics.
diff --git a/man/variable_type_icons.Rd b/man/variable_type_icons.Rd
index 9d564369b..22591bded 100644
--- a/man/variable_type_icons.Rd
+++ b/man/variable_type_icons.Rd
@@ -7,22 +7,12 @@
 variable_type_icons(var_type)
 }
 \arguments{
-\item{var_type}{(\code{character})\cr
-of \code{R} internal types (classes).}
+\item{var_type}{(\code{character}) of R internal types (classes).}
 }
 \value{
-Vector of HTML icons corresponding to data type in each column.
+(\code{character}) vector of HTML icons corresponding to data type in each column.
 }
 \description{
 Get icons to represent variable types in dataset
-}
-\examples{
-variable_type_icons <- getFromNamespace("variable_type_icons", "teal.modules.general")
-
-variable_type_icons(c(
-  "integer", "numeric", "logical", "Date", "POSIXct", "POSIXlt",
-  "factor", "character", "unknown", ""
-))
-
 }
 \keyword{internal}
diff --git a/man/varname_w_label.Rd b/man/varname_w_label.Rd
index f752406d7..92bcc5c97 100644
--- a/man/varname_w_label.Rd
+++ b/man/varname_w_label.Rd
@@ -17,14 +17,9 @@ varname_w_label(
 
 \item{dataset}{(\code{dataset}) Name of analysis dataset.}
 
-\item{wrap_width}{(\code{numeric}) Number of characters to wrap original
-label to. Defaults to 80.}
+\item{wrap_width}{(\code{numeric}) Number of characters to wrap original label to. Defaults to 80.}
 
-\item{prefix}{(\code{character}) String to paste to the beginning of the
-variable name with label.}
-
-\item{suffix}{(\code{character}) String to paste to the end of the variable
-name with label.}
+\item{prefix, suffix}{(\code{character}) String to paste to the beginning/end of the variable name with label.}
 }
 \value{
 (\code{character}) String with variable name and label.

From fcd025a3b61a51991fd365bf7b2a90fd2b0ae679 Mon Sep 17 00:00:00 2001
From: Aleksander Chlebowski <aleksander.chlebowski@contractors.roche.com>
Date: Wed, 28 Feb 2024 09:06:14 +0100
Subject: [PATCH 44/62] missing comma

---
 R/tm_file_viewer.R    | 2 +-
 man/tm_file_viewer.Rd | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/R/tm_file_viewer.R b/R/tm_file_viewer.R
index 232a3ff0d..b79029d4d 100644
--- a/R/tm_file_viewer.R
+++ b/R/tm_file_viewer.R
@@ -21,7 +21,7 @@
 #' datanames(data) <- c("data")
 #'
 #' app <- init(
-#'   data = data
+#'   data = data,
 #'   modules = modules(
 #'     tm_file_viewer(
 #'       input_path = list(
diff --git a/man/tm_file_viewer.Rd b/man/tm_file_viewer.Rd
index ff994a4e8..07f323541 100644
--- a/man/tm_file_viewer.Rd
+++ b/man/tm_file_viewer.Rd
@@ -31,7 +31,7 @@ data <- within(data, {
 datanames(data) <- c("data")
 
 app <- init(
-  data = data
+  data = data,
   modules = modules(
     tm_file_viewer(
       input_path = list(

From 87f6eeed2b01de142a1e3f896668b0688711ab81 Mon Sep 17 00:00:00 2001
From: unknown <kirar.kartikeya1@gmail.com>
Date: Wed, 28 Feb 2024 13:51:37 +0530
Subject: [PATCH 45/62] removed @noRd tags and added return from shared_params

---
 R/tm_a_pca.R                  |  2 ++
 R/tm_a_regression.R           |  2 ++
 R/tm_data_table.R             |  2 ++
 R/tm_g_association.R          |  2 ++
 R/tm_g_bivariate.R            | 20 +++++---------------
 R/tm_g_distribution.R         |  2 ++
 R/tm_g_scatterplot.R          |  2 ++
 R/tm_g_scatterplotmatrix.R    |  2 ++
 R/tm_missing_data.R           |  2 ++
 R/tm_outliers.R               |  2 ++
 R/tm_variable_browser.R       | 16 ++++------------
 man/tm_a_pca.Rd               |  3 +++
 man/tm_a_regression.Rd        |  3 +++
 man/tm_data_table.Rd          |  3 +++
 man/tm_g_association.Rd       |  3 +++
 man/tm_g_bivariate.Rd         |  3 +++
 man/tm_g_distribution.Rd      |  3 +++
 man/tm_g_scatterplot.Rd       |  3 +++
 man/tm_g_scatterplotmatrix.Rd |  3 +++
 man/tm_missing_data.Rd        |  3 +++
 man/tm_outliers.Rd            |  3 +++
 man/tm_variable_browser.Rd    |  3 +++
 22 files changed, 60 insertions(+), 27 deletions(-)

diff --git a/R/tm_a_pca.R b/R/tm_a_pca.R
index 3e36da008..5177ca2ca 100644
--- a/R/tm_a_pca.R
+++ b/R/tm_a_pca.R
@@ -16,6 +16,8 @@
 #' @templateVar ggnames "Elbow plot", "Circle plot", "Biplot", "Eigenvector plot"
 #' @template ggplot2_args_multi
 #'
+#' @inherit shared_params return
+#'
 #' @examples
 #' library(teal.widgets)
 #'
diff --git a/R/tm_a_regression.R b/R/tm_a_regression.R
index 2009bc380..c53ad2373 100644
--- a/R/tm_a_regression.R
+++ b/R/tm_a_regression.R
@@ -40,6 +40,8 @@
 #' @templateVar ggnames `r regression_names`
 #' @template ggplot2_args_multi
 #'
+#' @inherit shared_params return
+#'
 #' @examples
 #' # general data example
 #' library(teal.widgets)
diff --git a/R/tm_data_table.R b/R/tm_data_table.R
index d95342d9e..33a88db34 100644
--- a/R/tm_data_table.R
+++ b/R/tm_data_table.R
@@ -27,6 +27,8 @@
 #' @param server_rendering (`logical`) should the data table be rendered server side
 #' (see `server` argument of [DT::renderDataTable()])
 #'
+#' @inherit shared_params return
+#'
 #' @examples
 #' # general data example
 #' data <- teal_data()
diff --git a/R/tm_g_association.R b/R/tm_g_association.R
index 7697a16e9..a8aa35e5d 100644
--- a/R/tm_g_association.R
+++ b/R/tm_g_association.R
@@ -23,6 +23,8 @@
 #' @templateVar ggnames "Bivariate1", "Bivariate2"
 #' @template ggplot2_args_multi
 #'
+#' @inherit shared_params return
+#'
 #' @examples
 #' library(teal.widgets)
 #'
diff --git a/R/tm_g_bivariate.R b/R/tm_g_bivariate.R
index 966650e67..f982bf57a 100644
--- a/R/tm_g_bivariate.R
+++ b/R/tm_g_bivariate.R
@@ -44,6 +44,8 @@
 #' Does not allow scaling to be changed by default (`FALSE`).
 #' @param swap_axes (`logical`, optional) Whether to swap X and Y axes. Defaults to `FALSE`.
 #'
+#' @inherit shared_params return
+#'
 #' @examples
 #' library(teal.widgets)
 #'
@@ -291,9 +293,7 @@ tm_g_bivariate <- function(label = "Bivariate Plots",
   )
 }
 
-# UI function for the bivariate module.
-#' @noRd
-#' @keywords internal
+# UI function for the bivariate module
 ui_g_bivariate <- function(id, ...) {
   args <- list(...)
   is_single_dataset_value <- teal.transform::is_single_dataset(
@@ -434,9 +434,7 @@ ui_g_bivariate <- function(id, ...) {
   )
 }
 
-# Server function for the bivariate module.
-#' @noRd
-#' @keywords internal
+# Server function for the bivariate module
 srv_g_bivariate <- function(id,
                             data,
                             reporter,
@@ -718,8 +716,6 @@ srv_g_bivariate <- function(id,
 }
 
 # Get Substituted ggplot call
-#' @noRd
-#' @keywords internal
 bivariate_plot_call <- function(data_name,
                                 x = character(0),
                                 y = character(0),
@@ -770,8 +766,6 @@ bivariate_plot_call <- function(data_name,
 
 # Create ggplot part of plot call
 # Due to the type of the x and y variable the plot type is chosen
-#' @noRd
-#' @keywords internal
 bivariate_ggplot_call <- function(x_class = c("NULL", "numeric", "integer", "factor", "character", "logical"),
                                   y_class = c("NULL", "numeric", "integer", "factor", "character", "logical"),
                                   freq = TRUE,
@@ -955,9 +949,7 @@ bivariate_ggplot_call <- function(x_class = c("NULL", "numeric", "integer", "fac
   plot_call
 }
 
-#' Create facet call
-#' @noRd
-#' @keywords internal
+# Create facet call
 facet_ggplot_call <- function(row_facet = character(0),
                               col_facet = character(0),
                               free_x_scales = FALSE,
@@ -988,8 +980,6 @@ facet_ggplot_call <- function(row_facet = character(0),
   }
 }
 
-#' @noRd
-#' @keywords internal
 coloring_ggplot_call <- function(colour,
                                  fill,
                                  size,
diff --git a/R/tm_g_distribution.R b/R/tm_g_distribution.R
index 0436df5df..bf77345a9 100644
--- a/R/tm_g_distribution.R
+++ b/R/tm_g_distribution.R
@@ -25,6 +25,8 @@
 #' @templateVar ggnames "Histogram", "QQplot"
 #' @template ggplot2_args_multi
 #'
+#' @inherit shared_params return
+#'
 #' @examples
 #' library(teal.widgets)
 #'
diff --git a/R/tm_g_scatterplot.R b/R/tm_g_scatterplot.R
index 5c36051eb..d2369364c 100644
--- a/R/tm_g_scatterplot.R
+++ b/R/tm_g_scatterplot.R
@@ -28,6 +28,8 @@
 #' @param max_deg (`integer`, optional) The maximum degree for the polynomial trend line. Must not be less than 1.
 #' @param table_dec (`integer`, optional) Number of decimal places used to round numeric values in the table.
 #'
+#' @inherit shared_params return
+#'
 #' @examples
 #' library(teal.widgets)
 #'
diff --git a/R/tm_g_scatterplotmatrix.R b/R/tm_g_scatterplotmatrix.R
index 3325da87d..e528c00a5 100644
--- a/R/tm_g_scatterplotmatrix.R
+++ b/R/tm_g_scatterplotmatrix.R
@@ -16,6 +16,8 @@
 #' `data_extract_spec` use `select_spec(..., ordered = TRUE)` if plot elements should be
 #' rendered according to selection order.
 #'
+#' @inherit shared_params return
+#'
 #' @examples
 #' # general data example
 #' data <- teal_data()
diff --git a/R/tm_missing_data.R b/R/tm_missing_data.R
index 89ef30f82..311a64e44 100644
--- a/R/tm_missing_data.R
+++ b/R/tm_missing_data.R
@@ -15,6 +15,8 @@
 #' @templateVar ggnames "Summary Obs", "Summary Patients", "Combinations Main", "Combinations Hist", "By Subject"
 #' @template ggplot2_args_multi
 #'
+#' @inherit shared_params return
+#'
 #' @examples
 #' library(teal.widgets)
 #'
diff --git a/R/tm_outliers.R b/R/tm_outliers.R
index 3c17565a5..488d2b9d1 100644
--- a/R/tm_outliers.R
+++ b/R/tm_outliers.R
@@ -15,6 +15,8 @@
 #' @templateVar ggnames "Boxplot","Density Plot","Cumulative Distribution Plot"
 #' @template ggplot2_args_multi
 #'
+#' @inherit shared_params return
+#'
 #' @examples
 #' library(teal.widgets)
 #'
diff --git a/R/tm_variable_browser.R b/R/tm_variable_browser.R
index 6c4f9f289..8b150966d 100644
--- a/R/tm_variable_browser.R
+++ b/R/tm_variable_browser.R
@@ -19,6 +19,8 @@
 #' If vector of length zero (default) then all datasets are shown.
 #' Note: Only `data.frame` objects are compatible; using other types will cause an error.
 #'
+#' @inherit shared_params return
+#'
 #' @examples
 #' library(teal.widgets)
 #'
@@ -107,9 +109,7 @@ tm_variable_browser <- function(label = "Variable Browser",
   )
 }
 
-# UI function for the variable browser module.
-#' @noRd
-#' @keywords internal
+# UI function for the variable browser module
 ui_variable_browser <- function(id,
                                 pre_output = NULL,
                                 post_output = NULL) {
@@ -179,9 +179,7 @@ ui_variable_browser <- function(id,
   )
 }
 
-# Server function for the variable browser module.
-#' @noRd
-#' @keywords internal
+# Server function for the variable browser module
 srv_variable_browser <- function(id,
                                  data,
                                  reporter,
@@ -799,8 +797,6 @@ plot_var_summary <- function(var,
   plot_main
 }
 
-#' @noRd
-#' @keywords internal
 is_num_var_short <- function(.unique_records_for_factor, input, data_for_analysis) {
   length(unique(data_for_analysis()$data)) < .unique_records_for_factor && !is.null(input$numeric_as_factor)
 }
@@ -828,8 +824,6 @@ validate_input <- function(input, plot_var, data) {
   })
 }
 
-#' @noRd
-#' @keywords internal
 get_plotted_data <- function(input, plot_var, data) {
   dataset_name <- input$tabset_panel
   varname <- plot_var$variable[[dataset_name]]
@@ -1045,8 +1039,6 @@ establish_updating_selection <- function(datanames, input, plot_var, columns_nam
   })
 }
 
-#' @noRd
-#' @keywords internal
 get_bin_width <- function(x_vec, scaling_factor = 2) {
   x_vec <- x_vec[!is.na(x_vec)]
   qntls <- stats::quantile(x_vec, probs = c(0.1, 0.25, 0.75, 0.9), type = 2)
diff --git a/man/tm_a_pca.Rd b/man/tm_a_pca.Rd
index 45161c7cf..c2d91f5e2 100644
--- a/man/tm_a_pca.Rd
+++ b/man/tm_a_pca.Rd
@@ -73,6 +73,9 @@ with text placed before the output to put the output into context. For example a
 \item{post_output}{(\code{shiny.tag}, optional) Text or UI element to be displayed after the module's output,
 adding context or further instructions. Elements like \code{shiny::helpText()} are useful.}
 }
+\value{
+Object of class \code{teal_module} to be used in \code{teal} applications.
+}
 \description{
 Module conducts principal component analysis (PCA) on a given dataset and offers different
 ways of visualizing the outcomes, including elbow plot, circle plot, biplot, and eigenvector plot.
diff --git a/man/tm_a_regression.Rd b/man/tm_a_regression.Rd
index 627734540..0c59a0f66 100644
--- a/man/tm_a_regression.Rd
+++ b/man/tm_a_regression.Rd
@@ -97,6 +97,9 @@ It takes the form of \code{c(value, min, max)} and it is passed to the \code{val
 argument in \code{teal.widgets::optionalSliderInputValMinMax}.
 }}
 }
+\value{
+Object of class \code{teal_module} to be used in \code{teal} applications.
+}
 \description{
 Module for visualizing regression analysis, including scatterplots and
 various regression diagnostics plots.
diff --git a/man/tm_data_table.Rd b/man/tm_data_table.Rd
index bf3c62851..06abb22b2 100644
--- a/man/tm_data_table.Rd
+++ b/man/tm_data_table.Rd
@@ -47,6 +47,9 @@ with text placed before the output to put the output into context. For example a
 \item{post_output}{(\code{shiny.tag}, optional) Text or UI element to be displayed after the module's output,
 adding context or further instructions. Elements like \code{shiny::helpText()} are useful.}
 }
+\value{
+Object of class \code{teal_module} to be used in \code{teal} applications.
+}
 \description{
 Module provides a dynamic and interactive way to view \code{data.frame}s in a \code{teal} application.
 It uses the \code{DT} package to display data tables in a paginated, searchable, and sortable format,
diff --git a/man/tm_g_association.Rd b/man/tm_g_association.Rd
index f7b62f3c8..1222d29d3 100644
--- a/man/tm_g_association.Rd
+++ b/man/tm_g_association.Rd
@@ -58,6 +58,9 @@ List names should match the following: \code{c("default", "Bivariate1", "Bivaria
 
 For more details see the vignette: \code{vignette("custom-ggplot2-arguments", package = "teal.widgets")}.}
 }
+\value{
+Object of class \code{teal_module} to be used in \code{teal} applications.
+}
 \description{
 Module provides functionality for visualizing the distribution of variables and
 their association with a reference variable.
diff --git a/man/tm_g_bivariate.Rd b/man/tm_g_bivariate.Rd
index 8929db567..62f35aa01 100644
--- a/man/tm_g_bivariate.Rd
+++ b/man/tm_g_bivariate.Rd
@@ -101,6 +101,9 @@ with text placed before the output to put the output into context. For example a
 \item{post_output}{(\code{shiny.tag}, optional) Text or UI element to be displayed after the module's output,
 adding context or further instructions. Elements like \code{shiny::helpText()} are useful.}
 }
+\value{
+Object of class \code{teal_module} to be used in \code{teal} applications.
+}
 \description{
 Module enables the creation of univariate and bivariate plots,
 facilitating the exploration of data distributions and relationships between two variables.
diff --git a/man/tm_g_distribution.Rd b/man/tm_g_distribution.Rd
index a13227224..53a229e97 100644
--- a/man/tm_g_distribution.Rd
+++ b/man/tm_g_distribution.Rd
@@ -65,6 +65,9 @@ with text placed before the output to put the output into context. For example a
 \item{post_output}{(\code{shiny.tag}, optional) with text placed after the output to put the output
 into context. For example the \code{\link[shiny:helpText]{shiny::helpText()}} elements are useful.}
 }
+\value{
+Object of class \code{teal_module} to be used in \code{teal} applications.
+}
 \description{
 Module is designed to explore the distribution of a single variable within a given dataset.
 It offers several tools, such as histograms, Q-Q plots, and various statistical tests to
diff --git a/man/tm_g_scatterplot.Rd b/man/tm_g_scatterplot.Rd
index 4ff8705bd..815fc0931 100644
--- a/man/tm_g_scatterplot.Rd
+++ b/man/tm_g_scatterplot.Rd
@@ -94,6 +94,9 @@ The argument is merged with options variable \code{teal.ggplot2_args} and defaul
 
 For more details see the vignette: \code{vignette("custom-ggplot2-arguments", package = "teal.widgets")}}
 }
+\value{
+Object of class \code{teal_module} to be used in \code{teal} applications.
+}
 \description{
 Generates a customizable scatterplot using \code{ggplot2}.
 This module allows users to select variables for the x and y axes,
diff --git a/man/tm_g_scatterplotmatrix.Rd b/man/tm_g_scatterplotmatrix.Rd
index 829fe01a4..46db4256d 100644
--- a/man/tm_g_scatterplotmatrix.Rd
+++ b/man/tm_g_scatterplotmatrix.Rd
@@ -35,6 +35,9 @@ with text placed before the output to put the output into context. For example a
 \item{post_output}{(\code{shiny.tag}, optional) Text or UI element to be displayed after the module's output,
 adding context or further instructions. Elements like \code{shiny::helpText()} are useful.}
 }
+\value{
+Object of class \code{teal_module} to be used in \code{teal} applications.
+}
 \description{
 Generates a scatterplot matrix from selected \code{variables} from datasets.
 Each plot within the matrix represents the relationship between two variables,
diff --git a/man/tm_missing_data.Rd b/man/tm_missing_data.Rd
index a5b463bcb..39900e40d 100644
--- a/man/tm_missing_data.Rd
+++ b/man/tm_missing_data.Rd
@@ -48,6 +48,9 @@ with text placed before the output to put the output into context. For example a
 \item{post_output}{(\code{shiny.tag}, optional) Text or UI element to be displayed after the module's output,
 adding context or further instructions. Elements like \code{shiny::helpText()} are useful.}
 }
+\value{
+Object of class \code{teal_module} to be used in \code{teal} applications.
+}
 \description{
 This module analyzes missing data in \code{data.frame}s to help users explore missing observations and
 gain insights into the completeness of their data.
diff --git a/man/tm_outliers.Rd b/man/tm_outliers.Rd
index 2e39076a1..d36ff08ae 100644
--- a/man/tm_outliers.Rd
+++ b/man/tm_outliers.Rd
@@ -49,6 +49,9 @@ with text placed before the output to put the output into context. For example a
 \item{post_output}{(\code{shiny.tag}, optional) Text or UI element to be displayed after the module's output,
 adding context or further instructions. Elements like \code{shiny::helpText()} are useful.}
 }
+\value{
+Object of class \code{teal_module} to be used in \code{teal} applications.
+}
 \description{
 Module to analyze and identify outliers using different methods
 such as IQR, Z-score, and Percentiles, and offers visualizations including
diff --git a/man/tm_variable_browser.Rd b/man/tm_variable_browser.Rd
index 7acf170ab..efe5cbb06 100644
--- a/man/tm_variable_browser.Rd
+++ b/man/tm_variable_browser.Rd
@@ -41,6 +41,9 @@ The argument is merged with options variable \code{teal.ggplot2_args} and defaul
 
 For more details see the vignette: \code{vignette("custom-ggplot2-arguments", package = "teal.widgets")}}
 }
+\value{
+Object of class \code{teal_module} to be used in \code{teal} applications.
+}
 \description{
 Module provides provides a detailed summary and visualization of variable distributions
 for \code{data.frame} objects, with interactive features to customize analysis.

From bddee61b509ec42d9980d9db398b9a9d7dcc34b2 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Andr=C3=A9=20Ver=C3=ADssimo?=
 <211358+averissimo@users.noreply.github.com>
Date: Wed, 28 Feb 2024 14:34:58 +0100
Subject: [PATCH 46/62] Update to roxygen2 `@template` for `ggplot2_args`
 arguments (#694)

# Pull Request

<!--- Replace `#nnn` with your issue link for reference. -->

- Closes #695
- Part of #624

#### Changes description

- Update type in `ggplot2_args`
- Minor change to phrasing
- Move template file under `man` page to avoid extra folder at root
level ([available
since](https://roxygen2.r-lib.org/news/index.html?q=template#options-7-0-0)
`roxygen2@7.0.0`)
- Update `.Rbuildignore` accordingly

#### Reviewer should consider

- `@template` has been superseded
(https://roxygen2.r-lib.org/articles/reuse.html?q=template#superseded)
  - There's no equivalent though _(with parameterized strings)_
- Alternative: we could add `ggplot2_args` to `shared_params` and
specific list of names it can take in `@details` on each function that
uses this
---
 .Rbuildignore                              | 2 +-
 man-roxygen/ggplot2_args_multi.R           | 7 -------
 man/roxygen/templates/ggplot2_args_multi.R | 8 ++++++++
 man/tm_a_pca.Rd                            | 5 +++--
 man/tm_a_regression.Rd                     | 5 +++--
 man/tm_g_association.Rd                    | 5 +++--
 man/tm_g_distribution.Rd                   | 5 +++--
 man/tm_missing_data.Rd                     | 5 +++--
 man/tm_outliers.Rd                         | 5 +++--
 9 files changed, 27 insertions(+), 20 deletions(-)
 delete mode 100644 man-roxygen/ggplot2_args_multi.R
 create mode 100644 man/roxygen/templates/ggplot2_args_multi.R

diff --git a/.Rbuildignore b/.Rbuildignore
index 08f35f406..bc51aef0c 100644
--- a/.Rbuildignore
+++ b/.Rbuildignore
@@ -28,7 +28,7 @@ SECURITY.md
 ^Jenkinsfile$
 ^logs$
 ^Makefile$
-^man-roxygen$
+^man/roxygen$
 ^Meta$
 ^outputdir$
 ^scratch$
diff --git a/man-roxygen/ggplot2_args_multi.R b/man-roxygen/ggplot2_args_multi.R
deleted file mode 100644
index 332f0084d..000000000
--- a/man-roxygen/ggplot2_args_multi.R
+++ /dev/null
@@ -1,7 +0,0 @@
-#' @param ggplot2_args optional, (`ggplot2_args`) object created by [`teal.widgets::ggplot2_args()`]
-#'  with settings for all the plots or named list of `ggplot2_args` objects for plot-specific settings.
-#'  The argument is merged with options variable `teal.ggplot2_args` and default module setup.
-#'
-#'  List names should match the following: `c("default", <%=ggnames%>)`.
-#'
-#'  For more details see the vignette: `vignette("custom-ggplot2-arguments", package = "teal.widgets")`.
diff --git a/man/roxygen/templates/ggplot2_args_multi.R b/man/roxygen/templates/ggplot2_args_multi.R
new file mode 100644
index 000000000..466c9a2fa
--- /dev/null
+++ b/man/roxygen/templates/ggplot2_args_multi.R
@@ -0,0 +1,8 @@
+#' @param ggplot2_args (`ggplot2_args` or `named list` of `ggplot2_args`s) optional.
+#' Object created by [`teal.widgets::ggplot2_args()`] and contains settings for all the plots,
+#' or is a named `list` of `ggplot2_args` objects for plot-specific settings.
+#' The argument is merged with options variable `teal.ggplot2_args` and default module setup.
+#'
+#' List names should match the following: `c("default", <%=ggnames%>)`.
+#'
+#' For more details see the vignette: `vignette("custom-ggplot2-arguments", package = "teal.widgets")`.
diff --git a/man/tm_a_pca.Rd b/man/tm_a_pca.Rd
index c2d91f5e2..1e93711e1 100644
--- a/man/tm_a_pca.Rd
+++ b/man/tm_a_pca.Rd
@@ -34,8 +34,9 @@ specifying columns used to compute PCA.}
 
 \item{ggtheme}{optional, (\code{character}) \code{ggplot2} theme to be used by default. Defaults to \code{"gray"}.}
 
-\item{ggplot2_args}{optional, (\code{ggplot2_args}) object created by \code{\link[teal.widgets:ggplot2_args]{teal.widgets::ggplot2_args()}}
-with settings for all the plots or named list of \code{ggplot2_args} objects for plot-specific settings.
+\item{ggplot2_args}{(\code{ggplot2_args} or \verb{named list} of \code{ggplot2_args}s) optional.
+Object created by \code{\link[teal.widgets:ggplot2_args]{teal.widgets::ggplot2_args()}} and contains settings for all the plots,
+or is a named \code{list} of \code{ggplot2_args} objects for plot-specific settings.
 The argument is merged with options variable \code{teal.ggplot2_args} and default module setup.
 
 List names should match the following: \code{c("default", "Elbow plot", "Circle plot", "Biplot", "Eigenvector plot")}.
diff --git a/man/tm_a_regression.Rd b/man/tm_a_regression.Rd
index 0c59a0f66..04a72fd89 100644
--- a/man/tm_a_regression.Rd
+++ b/man/tm_a_regression.Rd
@@ -53,8 +53,9 @@ vector of \code{value}, \code{min}, and \code{max}.
 
 \item{ggtheme}{optional, (\code{character}) \code{ggplot2} theme to be used by default. Defaults to \code{"gray"}.}
 
-\item{ggplot2_args}{optional, (\code{ggplot2_args}) object created by \code{\link[teal.widgets:ggplot2_args]{teal.widgets::ggplot2_args()}}
-with settings for all the plots or named list of \code{ggplot2_args} objects for plot-specific settings.
+\item{ggplot2_args}{(\code{ggplot2_args} or \verb{named list} of \code{ggplot2_args}s) optional.
+Object created by \code{\link[teal.widgets:ggplot2_args]{teal.widgets::ggplot2_args()}} and contains settings for all the plots,
+or is a named \code{list} of \code{ggplot2_args} objects for plot-specific settings.
 The argument is merged with options variable \code{teal.ggplot2_args} and default module setup.
 
 List names should match the following: \verb{c("default", "Response vs Regressor", "Residuals vs Fitted", "Scale-Location", "Cook's distance", "Residuals vs Leverage"", "Cook's dist vs Leverage")}.
diff --git a/man/tm_g_association.Rd b/man/tm_g_association.Rd
index 1222d29d3..6713cff1e 100644
--- a/man/tm_g_association.Rd
+++ b/man/tm_g_association.Rd
@@ -50,8 +50,9 @@ with text placed before the output to put the output into context. For example a
 \item{post_output}{(\code{shiny.tag}, optional) Text or UI element to be displayed after the module's output,
 adding context or further instructions. Elements like \code{shiny::helpText()} are useful.}
 
-\item{ggplot2_args}{optional, (\code{ggplot2_args}) object created by \code{\link[teal.widgets:ggplot2_args]{teal.widgets::ggplot2_args()}}
-with settings for all the plots or named list of \code{ggplot2_args} objects for plot-specific settings.
+\item{ggplot2_args}{(\code{ggplot2_args} or \verb{named list} of \code{ggplot2_args}s) optional.
+Object created by \code{\link[teal.widgets:ggplot2_args]{teal.widgets::ggplot2_args()}} and contains settings for all the plots,
+or is a named \code{list} of \code{ggplot2_args} objects for plot-specific settings.
 The argument is merged with options variable \code{teal.ggplot2_args} and default module setup.
 
 List names should match the following: \code{c("default", "Bivariate1", "Bivariate2")}.
diff --git a/man/tm_g_distribution.Rd b/man/tm_g_distribution.Rd
index 53a229e97..dadb2d4c5 100644
--- a/man/tm_g_distribution.Rd
+++ b/man/tm_g_distribution.Rd
@@ -37,8 +37,9 @@ Defaults to density (\code{FALSE}).}
 
 \item{ggtheme}{optional, (\code{character}) \code{ggplot2} theme to be used by default. Defaults to \code{"gray"}.}
 
-\item{ggplot2_args}{optional, (\code{ggplot2_args}) object created by \code{\link[teal.widgets:ggplot2_args]{teal.widgets::ggplot2_args()}}
-with settings for all the plots or named list of \code{ggplot2_args} objects for plot-specific settings.
+\item{ggplot2_args}{(\code{ggplot2_args} or \verb{named list} of \code{ggplot2_args}s) optional.
+Object created by \code{\link[teal.widgets:ggplot2_args]{teal.widgets::ggplot2_args()}} and contains settings for all the plots,
+or is a named \code{list} of \code{ggplot2_args} objects for plot-specific settings.
 The argument is merged with options variable \code{teal.ggplot2_args} and default module setup.
 
 List names should match the following: \code{c("default", "Histogram", "QQplot")}.
diff --git a/man/tm_missing_data.Rd b/man/tm_missing_data.Rd
index 39900e40d..7cb76d88f 100644
--- a/man/tm_missing_data.Rd
+++ b/man/tm_missing_data.Rd
@@ -33,8 +33,9 @@ ignored.}
 
 \item{ggtheme}{(\code{character}, optional) Specifies the default \code{ggplot2} theme for plots. Defaults to \code{classic}.}
 
-\item{ggplot2_args}{optional, (\code{ggplot2_args}) object created by \code{\link[teal.widgets:ggplot2_args]{teal.widgets::ggplot2_args()}}
-with settings for all the plots or named list of \code{ggplot2_args} objects for plot-specific settings.
+\item{ggplot2_args}{(\code{ggplot2_args} or \verb{named list} of \code{ggplot2_args}s) optional.
+Object created by \code{\link[teal.widgets:ggplot2_args]{teal.widgets::ggplot2_args()}} and contains settings for all the plots,
+or is a named \code{list} of \code{ggplot2_args} objects for plot-specific settings.
 The argument is merged with options variable \code{teal.ggplot2_args} and default module setup.
 
 List names should match the following: \code{c("default", "Summary Obs", "Summary Patients", "Combinations Main", "Combinations Hist", "By Subject")}.
diff --git a/man/tm_outliers.Rd b/man/tm_outliers.Rd
index d36ff08ae..3e9e705d0 100644
--- a/man/tm_outliers.Rd
+++ b/man/tm_outliers.Rd
@@ -28,8 +28,9 @@ Specifies the categorical variable(s) to split the selected outlier variables on
 
 \item{ggtheme}{optional, (\code{character}) \code{ggplot2} theme to be used by default. Defaults to \code{"gray"}.}
 
-\item{ggplot2_args}{optional, (\code{ggplot2_args}) object created by \code{\link[teal.widgets:ggplot2_args]{teal.widgets::ggplot2_args()}}
-with settings for all the plots or named list of \code{ggplot2_args} objects for plot-specific settings.
+\item{ggplot2_args}{(\code{ggplot2_args} or \verb{named list} of \code{ggplot2_args}s) optional.
+Object created by \code{\link[teal.widgets:ggplot2_args]{teal.widgets::ggplot2_args()}} and contains settings for all the plots,
+or is a named \code{list} of \code{ggplot2_args} objects for plot-specific settings.
 The argument is merged with options variable \code{teal.ggplot2_args} and default module setup.
 
 List names should match the following: \code{c("default", "Boxplot","Density Plot","Cumulative Distribution Plot")}.

From 7da5cae716a6801b4cfe045a347ad08624bf9799 Mon Sep 17 00:00:00 2001
From: Marcin <133694481+m7pr@users.noreply.github.com>
Date: Wed, 28 Feb 2024 14:56:55 +0100
Subject: [PATCH 47/62] Update R/tm_file_viewer.R
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

Co-authored-by: André Veríssimo <211358+averissimo@users.noreply.github.com>
Signed-off-by: Marcin <133694481+m7pr@users.noreply.github.com>
---
 R/tm_file_viewer.R | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/R/tm_file_viewer.R b/R/tm_file_viewer.R
index b79029d4d..edcc354d4 100644
--- a/R/tm_file_viewer.R
+++ b/R/tm_file_viewer.R
@@ -8,11 +8,11 @@
 #' @inheritParams shared_params
 #' @param input_path (`list`) of the input paths, optional. Each element can be:
 #'
-#' @inherit shared_params return
-#'
 #' Paths can be specified as absolute paths or relative to the running directory of the application.
 #' Default to the current working directory if not supplied.
 #'
+#' @inherit shared_params return
+#'
 #' @examples
 #' data <- teal_data()
 #' data <- within(data, {

From bc56c51eaa1dcc0ec9f9270ae229e3627c26f664 Mon Sep 17 00:00:00 2001
From: "27856297+dependabot-preview[bot]@users.noreply.github.com"
 <27856297+dependabot-preview[bot]@users.noreply.github.com>
Date: Wed, 28 Feb 2024 14:33:21 +0000
Subject: [PATCH 48/62] [skip roxygen] [skip vbump] Roxygen Man Pages Auto
 Update

---
 man/tm_file_viewer.Rd | 5 ++++-
 1 file changed, 4 insertions(+), 1 deletion(-)

diff --git a/man/tm_file_viewer.Rd b/man/tm_file_viewer.Rd
index 07f323541..c04f73a2e 100644
--- a/man/tm_file_viewer.Rd
+++ b/man/tm_file_viewer.Rd
@@ -13,7 +13,10 @@ tm_file_viewer(
 \item{label}{(\code{character(1)}) Label shown in the navigation item for the module or module group.
 For \code{modules()} defaults to \code{"root"}. See \code{Details}.}
 
-\item{input_path}{(\code{list}) of the input paths, optional. Each element can be:}
+\item{input_path}{(\code{list}) of the input paths, optional. Each element can be:
+
+Paths can be specified as absolute paths or relative to the running directory of the application.
+Default to the current working directory if not supplied.}
 }
 \value{
 Object of class \code{teal_module} to be used in \code{teal} applications.

From e5fc4c9e269c40bee0a3a3a7e548a86b0f570b53 Mon Sep 17 00:00:00 2001
From: kartikeya kirar <kirar.kartikeya1@gmail.com>
Date: Thu, 29 Feb 2024 20:07:46 +0530
Subject: [PATCH 49/62] standardize the notation for optional parameters (#698)

fixes
https://github.com/insightsengineering/teal.modules.general/issues/674
---
 R/tm_a_pca.R                               |  4 +--
 R/tm_a_regression.R                        |  4 +--
 R/tm_g_association.R                       |  4 +--
 R/tm_g_bivariate.R                         | 30 ++++++++--------
 R/tm_g_distribution.R                      |  4 +--
 R/tm_g_scatterplot.R                       | 22 ++++++------
 R/tm_g_scatterplotmatrix.R                 |  4 +--
 R/tm_missing_data.R                        |  2 +-
 R/tm_outliers.R                            |  4 +--
 R/utils.R                                  | 18 +++++-----
 man-roxygen/ggplot2_args_multi.R           |  7 ++++
 man/get_scatterplotmatrix_stats.Rd         |  4 +--
 man/include_css_files.Rd                   |  2 +-
 man/roxygen/templates/ggplot2_args_multi.R |  8 -----
 man/shared_params.Rd                       | 16 ++++-----
 man/tm_a_pca.Rd                            | 23 ++++++------
 man/tm_a_regression.Rd                     | 23 ++++++------
 man/tm_data_table.Rd                       |  4 +--
 man/tm_g_association.Rd                    | 17 +++++----
 man/tm_g_bivariate.Rd                      | 42 +++++++++++-----------
 man/tm_g_distribution.Rd                   | 15 ++++----
 man/tm_g_response.Rd                       | 12 +++----
 man/tm_g_scatterplot.Rd                    | 38 ++++++++++----------
 man/tm_g_scatterplotmatrix.Rd              |  8 ++---
 man/tm_missing_data.Rd                     | 15 ++++----
 man/tm_outliers.Rd                         | 19 +++++-----
 man/tm_t_crosstable.Rd                     |  4 +--
 man/tm_variable_browser.Rd                 |  4 +--
 28 files changed, 175 insertions(+), 182 deletions(-)
 create mode 100644 man-roxygen/ggplot2_args_multi.R
 delete mode 100644 man/roxygen/templates/ggplot2_args_multi.R

diff --git a/R/tm_a_pca.R b/R/tm_a_pca.R
index 5177ca2ca..8d7ef14e2 100644
--- a/R/tm_a_pca.R
+++ b/R/tm_a_pca.R
@@ -8,8 +8,8 @@
 #' @inheritParams teal::module
 #' @inheritParams shared_params
 #' @param dat (`data_extract_spec` or `list` of multiple `data_extract_spec`)
-#'   specifying columns used to compute PCA.
-#' @param font_size (`numeric`, optional) Specifies font size.
+#' specifying columns used to compute PCA.
+#' @param font_size (`numeric`) optional, specifies font size.
 #' It controls the font size for plot titles, axis labels, and legends.
 #' - If vector of `length == 1` then the font sizes will have a fixed size.
 #' - while vector of `value`, `min`, and `max` allows dynamic adjustment.
diff --git a/R/tm_a_regression.R b/R/tm_a_regression.R
index c53ad2373..9093d3919 100644
--- a/R/tm_a_regression.R
+++ b/R/tm_a_regression.R
@@ -14,8 +14,8 @@
 #' Regressor variables from an incoming dataset with filtering and selecting.
 #' @param response (`data_extract_spec` or `list` of multiple `data_extract_spec`)
 #' Response variables from an incoming dataset with filtering and selecting.
-#' @param default_outlier_label (`character`, optional) The default column selected to label outliers.
-#' @param default_plot_type (`numeric`, optional) Defaults to Response vs Regressor.
+#' @param default_outlier_label (`character`) optional, default column selected to label outliers.
+#' @param default_plot_type (`numeric`) optional, defaults to "Response vs Regressor".
 #' 1. Response vs Regressor
 #' 2. Residuals vs Fitted
 #' 3. Normal Q-Q
diff --git a/R/tm_g_association.R b/R/tm_g_association.R
index 32cf28bc2..6e93f4a24 100644
--- a/R/tm_g_association.R
+++ b/R/tm_g_association.R
@@ -15,9 +15,9 @@
 #' to ensure single selection option.
 #' @param vars (`data_extract_spec` or `list` of multiple `data_extract_spec`)
 #' Variables to be associated with the reference variable.
-#' @param show_association (`logical`) optional whether show association of `vars`
+#' @param show_association (`logical`) optional, whether show association of `vars`
 #' with reference variable. Defaults to `TRUE`.
-#' @param distribution_theme,association_theme (`character`) optional `ggplot2` themes to be used by default.
+#' @param distribution_theme,association_theme (`character`) optional, `ggplot2` themes to be used by default.
 #' Default to `"gray"`.
 #'
 #' @templateVar ggnames "Bivariate1", "Bivariate2"
diff --git a/R/tm_g_bivariate.R b/R/tm_g_bivariate.R
index 6388fa8b1..2cc65ea80 100644
--- a/R/tm_g_bivariate.R
+++ b/R/tm_g_bivariate.R
@@ -18,31 +18,31 @@
 #' @param y (`data_extract_spec` or `list` of multiple `data_extract_spec`)
 #' Variable names selected to plot along the y-axis by default.
 #' Can be numeric, factor or character.
-#' @param use_density (`logical`, optional) Indicates whether to plot density (`TRUE`) or frequency (`FALSE`).
+#' @param use_density (`logical`) optional, indicates whether to plot density (`TRUE`) or frequency (`FALSE`).
 #' Defaults to frequency (`FALSE`).
-#' @param row_facet (`data_extract_spec` or `list` of multiple `data_extract_spec`, optional)
-#' Variables for row facetting.
-#' @param col_facet (`data_extract_spec` or `list` of multiple `data_extract_spec`, optional)
-#' Variables for column facetting.
-#' @param facet (`logical`, optional) to specify whether the facet encodings `ui` elements are toggled
+#' @param row_facet (`data_extract_spec` or `list` of multiple `data_extract_spec`) optional,
+#' specification of the data variable(s) to use for faceting rows.
+#' @param col_facet (`data_extract_spec` or `list` of multiple `data_extract_spec`) optional,
+#' specification of the data variable(s) to use for faceting columns.
+#' @param facet (`logical`) optional, specifies whether the facet encodings `ui` elements are toggled
 #' on and shown to the user by default. Defaults to `TRUE` if either `row_facet` or `column_facet`
 #' are supplied.
 #' @param color_settings (`logical`) Whether coloring, filling and size should be applied
 #' and `UI` tool offered to the user.
-#' @param color (`data_extract_spec` or `list` of multiple `data_extract_spec`, optional)
-#' Variables selected for the outline color inside the coloring settings.
+#' @param color (`data_extract_spec` or `list` of multiple `data_extract_spec`) optional,
+#' specification of the data variable(s) selected for the outline color inside the coloring settings.
 #' It will be applied when `color_settings` is set to `TRUE`.
-#' @param fill (`data_extract_spec` or `list` of multiple `data_extract_spec`, optional)
-#' Variables selected for the fill color inside the coloring settings.
+#' @param fill (`data_extract_spec` or `list` of multiple `data_extract_spec`) optional,
+#' specification of the data variable(s) selected for the fill color inside the coloring settings.
 #' It will be applied when `color_settings` is set to `TRUE`.
-#' @param size (`data_extract_spec` or `list` of multiple `data_extract_spec`, optional)
-#' Variables selected for the size of `geom_point` plots inside the coloring settings.
+#' @param size (`data_extract_spec` or `list` of multiple `data_extract_spec`) optional,
+#' specification of the data variable(s) selected for the size of `geom_point` plots inside the coloring settings.
 #' It will be applied when `color_settings` is set to `TRUE`.
-#' @param free_x_scales (`logical`, optional) Whether X scaling shall be changeable.
+#' @param free_x_scales (`logical`) optional, whether X scaling shall be changeable.
 #' Does not allow scaling to be changed by default (`FALSE`).
-#' @param free_y_scales (`logical`, optional) Whether Y scaling shall be changeable.
+#' @param free_y_scales (`logical`) optional, whether Y scaling shall be changeable.
 #' Does not allow scaling to be changed by default (`FALSE`).
-#' @param swap_axes (`logical`, optional) Whether to swap X and Y axes. Defaults to `FALSE`.
+#' @param swap_axes (`logical`) optional, whether to swap X and Y axes. Defaults to `FALSE`.
 #'
 #' @inherit shared_params return
 #'
diff --git a/R/tm_g_distribution.R b/R/tm_g_distribution.R
index bf77345a9..edac703e8 100644
--- a/R/tm_g_distribution.R
+++ b/R/tm_g_distribution.R
@@ -14,9 +14,9 @@
 #' Categorical variable used to split the distribution analysis.
 #' @param group_var (`data_extract_spec` or `list` of multiple `data_extract_spec`)
 #' Variable used for faceting plot into multiple panels.
-#' @param freq (`logical`, optional) Whether to display frequency (`TRUE`) or density (`FALSE`).
+#' @param freq (`logical`) optional, whether to display frequency (`TRUE`) or density (`FALSE`).
 #' Defaults to density (`FALSE`).
-#' @param bins (`integer(1)` or `integer(3)`, optional)  Determines the number of bins for the histogram.
+#' @param bins (`integer(1)` or `integer(3)`) optional,  specifies the number of bins for the histogram.
 #' - When the length of `bins` is one: The histogram bins will have a fixed size based on the `bins` provided.
 #' - When the length of `bins` is three: The histogram bins are dynamically adjusted based on vector of `value`, `min`,
 #' and `max`.
diff --git a/R/tm_g_scatterplot.R b/R/tm_g_scatterplot.R
index d2369364c..00efed7cf 100644
--- a/R/tm_g_scatterplot.R
+++ b/R/tm_g_scatterplot.R
@@ -14,19 +14,19 @@
 #' variable names selected to plot along the x-axis by default.
 #' @param y (`data_extract_spec` or `list` of multiple `data_extract_spec`) Specifies
 #' variable names selected to plot along the y-axis by default.
-#' @param color_by (`data_extract_spec` or `list` of multiple `data_extract_spec`, optional)
-#' Defines the color encoding. If `NULL` then no color encoding option will be displayed.
-#' @param size_by (`data_extract_spec` or `list` of multiple `data_extract_spec`, optional)
-#' Defines the point size encoding. If `NULL` then no size encoding option will be displayed.
-#' @param row_facet (`data_extract_spec` or `list` of multiple `data_extract_spec`, optional)
-#' Specifies the variable(s) for faceting rows.
-#' @param col_facet (`data_extract_spec` or `list` of multiple `data_extract_spec`, optional)
-#' Specifies the variable(s) for faceting columns.
-#' @param shape (`character`, optional) A character vector with the names of the
+#' @param color_by (`data_extract_spec` or `list` of multiple `data_extract_spec`) optional,
+#' defines the color encoding. If `NULL` then no color encoding option will be displayed.
+#' @param size_by (`data_extract_spec` or `list` of multiple `data_extract_spec`) optional,
+#' defines the point size encoding. If `NULL` then no size encoding option will be displayed.
+#' @param row_facet (`data_extract_spec` or `list` of multiple `data_extract_spec`) optional,
+#' specifies the variable(s) for faceting rows.
+#' @param col_facet (`data_extract_spec` or `list` of multiple `data_extract_spec`) optional,
+#' specifies the variable(s) for faceting columns.
+#' @param shape (`character`) optional, character vector with the names of the
 #' shape, e.g. `c("triangle", "square", "circle")`. It defaults to `shape_names`. This is a complete list from
 #' `vignette("ggplot2-specs", package="ggplot2")`.
-#' @param max_deg (`integer`, optional) The maximum degree for the polynomial trend line. Must not be less than 1.
-#' @param table_dec (`integer`, optional) Number of decimal places used to round numeric values in the table.
+#' @param max_deg (`integer`) optional, maximum degree for the polynomial trend line. Must not be less than 1.
+#' @param table_dec (`integer`) optional, number of decimal places used to round numeric values in the table.
 #'
 #' @inherit shared_params return
 #'
diff --git a/R/tm_g_scatterplotmatrix.R b/R/tm_g_scatterplotmatrix.R
index e528c00a5..68115ddff 100644
--- a/R/tm_g_scatterplotmatrix.R
+++ b/R/tm_g_scatterplotmatrix.R
@@ -484,8 +484,8 @@ srv_g_scatterplotmatrix <- function(id, data, reporter, filter_panel_api, variab
 #' @param .f (`function`) function that accepts x and y as formula input `~ x + y`.
 #' Default `stats::cor.test`.
 #' @param .f_args (`list`) of arguments to be passed to `.f`.
-#' @param round_stat (`integer(1)`) optional. Number of decimal places to use when rounding the estimate.
-#' @param round_pval (`integer(1)`) optional. Number of decimal places to use when rounding the p-value.
+#' @param round_stat (`integer(1)`) optional, number of decimal places to use when rounding the estimate.
+#' @param round_pval (`integer(1)`) optional, number of decimal places to use when rounding the p-value.
 #'
 #' @return Character with stats. For [stats::cor.test()] correlation coefficient and p-value.
 #'
diff --git a/R/tm_missing_data.R b/R/tm_missing_data.R
index 311a64e44..9af5189f5 100644
--- a/R/tm_missing_data.R
+++ b/R/tm_missing_data.R
@@ -10,7 +10,7 @@
 #' @param parent_dataname (`character(1)`) Specifies the parent dataset name. Default is `ADSL` for `CDISC` data.
 #' If provided and exists, enables additional analysis "by subject". For non-`CDISC` data, this parameter can be
 #' ignored.
-#' @param ggtheme (`character`, optional) Specifies the default `ggplot2` theme for plots. Defaults to `classic`.
+#' @param ggtheme (`character`) optional, specifies the default `ggplot2` theme for plots. Defaults to `classic`.
 #'
 #' @templateVar ggnames "Summary Obs", "Summary Patients", "Combinations Main", "Combinations Hist", "By Subject"
 #' @template ggplot2_args_multi
diff --git a/R/tm_outliers.R b/R/tm_outliers.R
index 56b451db8..b09b680ed 100644
--- a/R/tm_outliers.R
+++ b/R/tm_outliers.R
@@ -9,8 +9,8 @@
 #'
 #' @param outlier_var (`data_extract_spec` or `list` of multiple `data_extract_spec`)
 #' Specifies variable(s) to be analyzed for outliers.
-#' @param categorical_var (`data_extract_spec` or `list` of multiple `data_extract_spec`, optional)
-#' Specifies the categorical variable(s) to split the selected outlier variables on.
+#' @param categorical_var (`data_extract_spec` or `list` of multiple `data_extract_spec`) optional,
+#' specifies the categorical variable(s) to split the selected outlier variables on.
 #'
 #' @templateVar ggnames "Boxplot","Density Plot","Cumulative Distribution Plot"
 #' @template ggplot2_args_multi
diff --git a/R/utils.R b/R/utils.R
index b1b1661d5..71f822ff4 100644
--- a/R/utils.R
+++ b/R/utils.R
@@ -3,13 +3,13 @@
 #' Defines common arguments shared across multiple functions in the package
 #' to avoid repetition by using `inheritParams`.
 #'
-#' @param plot_height optional, (`numeric`) Specifies the plot height as a three-element vector of
+#' @param plot_height (`numeric`) optional, specifies the plot height as a three-element vector of
 #' `value`, `min`, and `max` intended for use with a slider UI element.
-#' @param plot_width optional, (`numeric`) Specifies the plot width as a three-element vector of
+#' @param plot_width (`numeric`) optional, specifies the plot width as a three-element vector of
 #' `value`, `min`, and `max` for a slider encoding the plot width.
-#' @param rotate_xaxis_labels optional, (`logical`) Whether to rotate plot X axis labels. Does not
+#' @param rotate_xaxis_labels (`logical`) optional, whether to rotate plot X axis labels. Does not
 #' rotate by default (`FALSE`).
-#' @param ggtheme optional, (`character`) `ggplot2` theme to be used by default. Defaults to `"gray"`.
+#' @param ggtheme (`character`) optional, `ggplot2` theme to be used by default. Defaults to `"gray"`.
 #' @param ggplot2_args (`ggplot2_args`) object created by [teal.widgets::ggplot2_args()]
 #' with settings for the module plot.
 #' The argument is merged with options variable `teal.ggplot2_args` and default module setup.
@@ -20,17 +20,17 @@
 #' The argument is merged with options variable `teal.basic_table_args` and default module setup.
 #'
 #' For more details see the vignette: `vignette("custom-basic-table-arguments", package = "teal.widgets")`
-#' @param pre_output (`shiny.tag`, optional) Text or UI element to be displayed before the module's output,
+#' @param pre_output (`shiny.tag`) optional, text or UI element to be displayed before the module's output,
 #' providing context or a title.
 #'  with text placed before the output to put the output into context. For example a title.
-#' @param post_output (`shiny.tag`, optional) Text or UI element to be displayed after the module's output,
+#' @param post_output (`shiny.tag`) optional, text or UI element to be displayed after the module's output,
 #' adding context or further instructions. Elements like `shiny::helpText()` are useful.
 #'
-#' @param alpha (`integer(1)` or `integer(3)`, optional) Specifies point opacity.
+#' @param alpha (`integer(1)` or `integer(3)`) optional, specifies point opacity.
 #' - When the length of `alpha` is one: the plot points will have a fixed opacity.
 #' - When the length of `alpha` is three: the plot points opacity are dynamically adjusted based on
 #' vector of `value`, `min`, and `max`.
-#' @param size (`integer(1)` or `integer(3)`, optional) Specifies point size.
+#' @param size (`integer(1)` or `integer(3)`) optional, specifies point size.
 #' - When the length of `size` is one: the plot point sizes will have a fixed size.
 #' - When the length of `size` is three: the plot points size are dynamically adjusted based on
 #' vector of `value`, `min`, and `max`.
@@ -235,7 +235,7 @@ variable_type_icons <- function(var_type) {
 #' not work with `devtools`. Therefore, we redefine this method in each package
 #' as needed. Thus, we do not export this method
 #'
-#' @param pattern (`character`) optional regular expression to match the file names to be included.
+#' @param pattern (`character`) optional, regular expression to match the file names to be included.
 #'
 #' @return HTML code that includes `CSS` files.
 #' @keywords internal
diff --git a/man-roxygen/ggplot2_args_multi.R b/man-roxygen/ggplot2_args_multi.R
new file mode 100644
index 000000000..dc0497942
--- /dev/null
+++ b/man-roxygen/ggplot2_args_multi.R
@@ -0,0 +1,7 @@
+#' @param ggplot2_args (`ggplot2_args`) optional, object created by [`teal.widgets::ggplot2_args()`]
+#'  with settings for all the plots or named list of `ggplot2_args` objects for plot-specific settings.
+#'  The argument is merged with options variable `teal.ggplot2_args` and default module setup.
+#'
+#'  List names should match the following: `c("default", <%=ggnames%>)`.
+#'
+#'  For more details see the vignette: `vignette("custom-ggplot2-arguments", package = "teal.widgets")`.
diff --git a/man/get_scatterplotmatrix_stats.Rd b/man/get_scatterplotmatrix_stats.Rd
index f50928b5c..176b24cb1 100644
--- a/man/get_scatterplotmatrix_stats.Rd
+++ b/man/get_scatterplotmatrix_stats.Rd
@@ -21,9 +21,9 @@ Default \code{stats::cor.test}.}
 
 \item{.f_args}{(\code{list}) of arguments to be passed to \code{.f}.}
 
-\item{round_stat}{(\code{integer(1)}) optional. Number of decimal places to use when rounding the estimate.}
+\item{round_stat}{(\code{integer(1)}) optional, number of decimal places to use when rounding the estimate.}
 
-\item{round_pval}{(\code{integer(1)}) optional. Number of decimal places to use when rounding the p-value.}
+\item{round_pval}{(\code{integer(1)}) optional, number of decimal places to use when rounding the p-value.}
 }
 \value{
 Character with stats. For \code{\link[stats:cor.test]{stats::cor.test()}} correlation coefficient and p-value.
diff --git a/man/include_css_files.Rd b/man/include_css_files.Rd
index 44c46e76d..5065250b3 100644
--- a/man/include_css_files.Rd
+++ b/man/include_css_files.Rd
@@ -7,7 +7,7 @@
 include_css_files(pattern = "*")
 }
 \arguments{
-\item{pattern}{(\code{character}) optional regular expression to match the file names to be included.}
+\item{pattern}{(\code{character}) optional, regular expression to match the file names to be included.}
 }
 \value{
 HTML code that includes \code{CSS} files.
diff --git a/man/roxygen/templates/ggplot2_args_multi.R b/man/roxygen/templates/ggplot2_args_multi.R
deleted file mode 100644
index 466c9a2fa..000000000
--- a/man/roxygen/templates/ggplot2_args_multi.R
+++ /dev/null
@@ -1,8 +0,0 @@
-#' @param ggplot2_args (`ggplot2_args` or `named list` of `ggplot2_args`s) optional.
-#' Object created by [`teal.widgets::ggplot2_args()`] and contains settings for all the plots,
-#' or is a named `list` of `ggplot2_args` objects for plot-specific settings.
-#' The argument is merged with options variable `teal.ggplot2_args` and default module setup.
-#'
-#' List names should match the following: `c("default", <%=ggnames%>)`.
-#'
-#' For more details see the vignette: `vignette("custom-ggplot2-arguments", package = "teal.widgets")`.
diff --git a/man/shared_params.Rd b/man/shared_params.Rd
index a31e7e22f..1ea6b7094 100644
--- a/man/shared_params.Rd
+++ b/man/shared_params.Rd
@@ -4,16 +4,16 @@
 \alias{shared_params}
 \title{Shared parameters documentation}
 \arguments{
-\item{plot_height}{optional, (\code{numeric}) Specifies the plot height as a three-element vector of
+\item{plot_height}{(\code{numeric}) optional, specifies the plot height as a three-element vector of
 \code{value}, \code{min}, and \code{max} intended for use with a slider UI element.}
 
-\item{plot_width}{optional, (\code{numeric}) Specifies the plot width as a three-element vector of
+\item{plot_width}{(\code{numeric}) optional, specifies the plot width as a three-element vector of
 \code{value}, \code{min}, and \code{max} for a slider encoding the plot width.}
 
-\item{rotate_xaxis_labels}{optional, (\code{logical}) Whether to rotate plot X axis labels. Does not
+\item{rotate_xaxis_labels}{(\code{logical}) optional, whether to rotate plot X axis labels. Does not
 rotate by default (\code{FALSE}).}
 
-\item{ggtheme}{optional, (\code{character}) \code{ggplot2} theme to be used by default. Defaults to \code{"gray"}.}
+\item{ggtheme}{(\code{character}) optional, \code{ggplot2} theme to be used by default. Defaults to \code{"gray"}.}
 
 \item{ggplot2_args}{(\code{ggplot2_args}) object created by \code{\link[teal.widgets:ggplot2_args]{teal.widgets::ggplot2_args()}}
 with settings for the module plot.
@@ -27,21 +27,21 @@ The argument is merged with options variable \code{teal.basic_table_args} and de
 
 For more details see the vignette: \code{vignette("custom-basic-table-arguments", package = "teal.widgets")}}
 
-\item{pre_output}{(\code{shiny.tag}, optional) Text or UI element to be displayed before the module's output,
+\item{pre_output}{(\code{shiny.tag}) optional, text or UI element to be displayed before the module's output,
 providing context or a title.
 with text placed before the output to put the output into context. For example a title.}
 
-\item{post_output}{(\code{shiny.tag}, optional) Text or UI element to be displayed after the module's output,
+\item{post_output}{(\code{shiny.tag}) optional, text or UI element to be displayed after the module's output,
 adding context or further instructions. Elements like \code{shiny::helpText()} are useful.}
 
-\item{alpha}{(\code{integer(1)} or \code{integer(3)}, optional) Specifies point opacity.
+\item{alpha}{(\code{integer(1)} or \code{integer(3)}) optional, specifies point opacity.
 \itemize{
 \item When the length of \code{alpha} is one: the plot points will have a fixed opacity.
 \item When the length of \code{alpha} is three: the plot points opacity are dynamically adjusted based on
 vector of \code{value}, \code{min}, and \code{max}.
 }}
 
-\item{size}{(\code{integer(1)} or \code{integer(3)}, optional) Specifies point size.
+\item{size}{(\code{integer(1)} or \code{integer(3)}) optional, specifies point size.
 \itemize{
 \item When the length of \code{size} is one: the plot point sizes will have a fixed size.
 \item When the length of \code{size} is three: the plot points size are dynamically adjusted based on
diff --git a/man/tm_a_pca.Rd b/man/tm_a_pca.Rd
index 1e93711e1..a4fa1e679 100644
--- a/man/tm_a_pca.Rd
+++ b/man/tm_a_pca.Rd
@@ -26,52 +26,51 @@ For \code{modules()} defaults to \code{"root"}. See \code{Details}.}
 \item{dat}{(\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec})
 specifying columns used to compute PCA.}
 
-\item{plot_height}{optional, (\code{numeric}) Specifies the plot height as a three-element vector of
+\item{plot_height}{(\code{numeric}) optional, specifies the plot height as a three-element vector of
 \code{value}, \code{min}, and \code{max} intended for use with a slider UI element.}
 
-\item{plot_width}{optional, (\code{numeric}) Specifies the plot width as a three-element vector of
+\item{plot_width}{(\code{numeric}) optional, specifies the plot width as a three-element vector of
 \code{value}, \code{min}, and \code{max} for a slider encoding the plot width.}
 
-\item{ggtheme}{optional, (\code{character}) \code{ggplot2} theme to be used by default. Defaults to \code{"gray"}.}
+\item{ggtheme}{(\code{character}) optional, \code{ggplot2} theme to be used by default. Defaults to \code{"gray"}.}
 
-\item{ggplot2_args}{(\code{ggplot2_args} or \verb{named list} of \code{ggplot2_args}s) optional.
-Object created by \code{\link[teal.widgets:ggplot2_args]{teal.widgets::ggplot2_args()}} and contains settings for all the plots,
-or is a named \code{list} of \code{ggplot2_args} objects for plot-specific settings.
+\item{ggplot2_args}{(\code{ggplot2_args}) optional, object created by \code{\link[teal.widgets:ggplot2_args]{teal.widgets::ggplot2_args()}}
+with settings for all the plots or named list of \code{ggplot2_args} objects for plot-specific settings.
 The argument is merged with options variable \code{teal.ggplot2_args} and default module setup.
 
 List names should match the following: \code{c("default", "Elbow plot", "Circle plot", "Biplot", "Eigenvector plot")}.
 
 For more details see the vignette: \code{vignette("custom-ggplot2-arguments", package = "teal.widgets")}.}
 
-\item{rotate_xaxis_labels}{optional, (\code{logical}) Whether to rotate plot X axis labels. Does not
+\item{rotate_xaxis_labels}{(\code{logical}) optional, whether to rotate plot X axis labels. Does not
 rotate by default (\code{FALSE}).}
 
-\item{font_size}{(\code{numeric}, optional) Specifies font size.
+\item{font_size}{(\code{numeric}) optional, specifies font size.
 It controls the font size for plot titles, axis labels, and legends.
 \itemize{
 \item If vector of \code{length == 1} then the font sizes will have a fixed size.
 \item while vector of \code{value}, \code{min}, and \code{max} allows dynamic adjustment.
 }}
 
-\item{alpha}{(\code{integer(1)} or \code{integer(3)}, optional) Specifies point opacity.
+\item{alpha}{(\code{integer(1)} or \code{integer(3)}) optional, specifies point opacity.
 \itemize{
 \item When the length of \code{alpha} is one: the plot points will have a fixed opacity.
 \item When the length of \code{alpha} is three: the plot points opacity are dynamically adjusted based on
 vector of \code{value}, \code{min}, and \code{max}.
 }}
 
-\item{size}{(\code{integer(1)} or \code{integer(3)}, optional) Specifies point size.
+\item{size}{(\code{integer(1)} or \code{integer(3)}) optional, specifies point size.
 \itemize{
 \item When the length of \code{size} is one: the plot point sizes will have a fixed size.
 \item When the length of \code{size} is three: the plot points size are dynamically adjusted based on
 vector of \code{value}, \code{min}, and \code{max}.
 }}
 
-\item{pre_output}{(\code{shiny.tag}, optional) Text or UI element to be displayed before the module's output,
+\item{pre_output}{(\code{shiny.tag}) optional, text or UI element to be displayed before the module's output,
 providing context or a title.
 with text placed before the output to put the output into context. For example a title.}
 
-\item{post_output}{(\code{shiny.tag}, optional) Text or UI element to be displayed after the module's output,
+\item{post_output}{(\code{shiny.tag}) optional, text or UI element to be displayed after the module's output,
 adding context or further instructions. Elements like \code{shiny::helpText()} are useful.}
 }
 \value{
diff --git a/man/tm_a_regression.Rd b/man/tm_a_regression.Rd
index 04a72fd89..dc4f458f3 100644
--- a/man/tm_a_regression.Rd
+++ b/man/tm_a_regression.Rd
@@ -31,45 +31,44 @@ Regressor variables from an incoming dataset with filtering and selecting.}
 \item{response}{(\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec})
 Response variables from an incoming dataset with filtering and selecting.}
 
-\item{plot_height}{optional, (\code{numeric}) Specifies the plot height as a three-element vector of
+\item{plot_height}{(\code{numeric}) optional, specifies the plot height as a three-element vector of
 \code{value}, \code{min}, and \code{max} intended for use with a slider UI element.}
 
-\item{plot_width}{optional, (\code{numeric}) Specifies the plot width as a three-element vector of
+\item{plot_width}{(\code{numeric}) optional, specifies the plot width as a three-element vector of
 \code{value}, \code{min}, and \code{max} for a slider encoding the plot width.}
 
-\item{alpha}{(\code{integer(1)} or \code{integer(3)}, optional) Specifies point opacity.
+\item{alpha}{(\code{integer(1)} or \code{integer(3)}) optional, specifies point opacity.
 \itemize{
 \item When the length of \code{alpha} is one: the plot points will have a fixed opacity.
 \item When the length of \code{alpha} is three: the plot points opacity are dynamically adjusted based on
 vector of \code{value}, \code{min}, and \code{max}.
 }}
 
-\item{size}{(\code{integer(1)} or \code{integer(3)}, optional) Specifies point size.
+\item{size}{(\code{integer(1)} or \code{integer(3)}) optional, specifies point size.
 \itemize{
 \item When the length of \code{size} is one: the plot point sizes will have a fixed size.
 \item When the length of \code{size} is three: the plot points size are dynamically adjusted based on
 vector of \code{value}, \code{min}, and \code{max}.
 }}
 
-\item{ggtheme}{optional, (\code{character}) \code{ggplot2} theme to be used by default. Defaults to \code{"gray"}.}
+\item{ggtheme}{(\code{character}) optional, \code{ggplot2} theme to be used by default. Defaults to \code{"gray"}.}
 
-\item{ggplot2_args}{(\code{ggplot2_args} or \verb{named list} of \code{ggplot2_args}s) optional.
-Object created by \code{\link[teal.widgets:ggplot2_args]{teal.widgets::ggplot2_args()}} and contains settings for all the plots,
-or is a named \code{list} of \code{ggplot2_args} objects for plot-specific settings.
+\item{ggplot2_args}{(\code{ggplot2_args}) optional, object created by \code{\link[teal.widgets:ggplot2_args]{teal.widgets::ggplot2_args()}}
+with settings for all the plots or named list of \code{ggplot2_args} objects for plot-specific settings.
 The argument is merged with options variable \code{teal.ggplot2_args} and default module setup.
 
 List names should match the following: \verb{c("default", "Response vs Regressor", "Residuals vs Fitted", "Scale-Location", "Cook's distance", "Residuals vs Leverage"", "Cook's dist vs Leverage")}.
 
 For more details see the vignette: \code{vignette("custom-ggplot2-arguments", package = "teal.widgets")}.}
 
-\item{pre_output}{(\code{shiny.tag}, optional) Text or UI element to be displayed before the module's output,
+\item{pre_output}{(\code{shiny.tag}) optional, text or UI element to be displayed before the module's output,
 providing context or a title.
 with text placed before the output to put the output into context. For example a title.}
 
-\item{post_output}{(\code{shiny.tag}, optional) Text or UI element to be displayed after the module's output,
+\item{post_output}{(\code{shiny.tag}) optional, text or UI element to be displayed after the module's output,
 adding context or further instructions. Elements like \code{shiny::helpText()} are useful.}
 
-\item{default_plot_type}{(\code{numeric}, optional) Defaults to Response vs Regressor.
+\item{default_plot_type}{(\code{numeric}) optional, defaults to "Response vs Regressor".
 \enumerate{
 \item Response vs Regressor
 \item Residuals vs Fitted
@@ -80,7 +79,7 @@ adding context or further instructions. Elements like \code{shiny::helpText()} a
 \item Cook's dist vs Leverage
 }}
 
-\item{default_outlier_label}{(\code{character}, optional) The default column selected to label outliers.}
+\item{default_outlier_label}{(\code{character}) optional, default column selected to label outliers.}
 
 \item{label_segment_threshold}{(\code{numeric(1)} or \code{numeric(3)})
 Minimum distance between label and point on the plot that triggers the creation of
diff --git a/man/tm_data_table.Rd b/man/tm_data_table.Rd
index 06abb22b2..f9e799750 100644
--- a/man/tm_data_table.Rd
+++ b/man/tm_data_table.Rd
@@ -40,11 +40,11 @@ Note: Only datasets of the \code{data.frame} class are compatible.}
 \item{server_rendering}{(\code{logical}) should the data table be rendered server side
 (see \code{server} argument of \code{\link[DT:dataTableOutput]{DT::renderDataTable()}})}
 
-\item{pre_output}{(\code{shiny.tag}, optional) Text or UI element to be displayed before the module's output,
+\item{pre_output}{(\code{shiny.tag}) optional, text or UI element to be displayed before the module's output,
 providing context or a title.
 with text placed before the output to put the output into context. For example a title.}
 
-\item{post_output}{(\code{shiny.tag}, optional) Text or UI element to be displayed after the module's output,
+\item{post_output}{(\code{shiny.tag}) optional, text or UI element to be displayed after the module's output,
 adding context or further instructions. Elements like \code{shiny::helpText()} are useful.}
 }
 \value{
diff --git a/man/tm_g_association.Rd b/man/tm_g_association.Rd
index 6713cff1e..ef47169a7 100644
--- a/man/tm_g_association.Rd
+++ b/man/tm_g_association.Rd
@@ -31,28 +31,27 @@ to ensure single selection option.}
 \item{vars}{(\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec})
 Variables to be associated with the reference variable.}
 
-\item{show_association}{(\code{logical}) optional whether show association of \code{vars}
+\item{show_association}{(\code{logical}) optional, whether show association of \code{vars}
 with reference variable. Defaults to \code{TRUE}.}
 
-\item{plot_height}{optional, (\code{numeric}) Specifies the plot height as a three-element vector of
+\item{plot_height}{(\code{numeric}) optional, specifies the plot height as a three-element vector of
 \code{value}, \code{min}, and \code{max} intended for use with a slider UI element.}
 
-\item{plot_width}{optional, (\code{numeric}) Specifies the plot width as a three-element vector of
+\item{plot_width}{(\code{numeric}) optional, specifies the plot width as a three-element vector of
 \code{value}, \code{min}, and \code{max} for a slider encoding the plot width.}
 
-\item{distribution_theme, association_theme}{(\code{character}) optional \code{ggplot2} themes to be used by default.
+\item{distribution_theme, association_theme}{(\code{character}) optional, \code{ggplot2} themes to be used by default.
 Default to \code{"gray"}.}
 
-\item{pre_output}{(\code{shiny.tag}, optional) Text or UI element to be displayed before the module's output,
+\item{pre_output}{(\code{shiny.tag}) optional, text or UI element to be displayed before the module's output,
 providing context or a title.
 with text placed before the output to put the output into context. For example a title.}
 
-\item{post_output}{(\code{shiny.tag}, optional) Text or UI element to be displayed after the module's output,
+\item{post_output}{(\code{shiny.tag}) optional, text or UI element to be displayed after the module's output,
 adding context or further instructions. Elements like \code{shiny::helpText()} are useful.}
 
-\item{ggplot2_args}{(\code{ggplot2_args} or \verb{named list} of \code{ggplot2_args}s) optional.
-Object created by \code{\link[teal.widgets:ggplot2_args]{teal.widgets::ggplot2_args()}} and contains settings for all the plots,
-or is a named \code{list} of \code{ggplot2_args} objects for plot-specific settings.
+\item{ggplot2_args}{(\code{ggplot2_args}) optional, object created by \code{\link[teal.widgets:ggplot2_args]{teal.widgets::ggplot2_args()}}
+with settings for all the plots or named list of \code{ggplot2_args} objects for plot-specific settings.
 The argument is merged with options variable \code{teal.ggplot2_args} and default module setup.
 
 List names should match the following: \code{c("default", "Bivariate1", "Bivariate2")}.
diff --git a/man/tm_g_bivariate.Rd b/man/tm_g_bivariate.Rd
index 62f35aa01..a88344f08 100644
--- a/man/tm_g_bivariate.Rd
+++ b/man/tm_g_bivariate.Rd
@@ -41,52 +41,52 @@ No empty selections are allowed.}
 Variable names selected to plot along the y-axis by default.
 Can be numeric, factor or character.}
 
-\item{row_facet}{(\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec}, optional)
-Variables for row facetting.}
+\item{row_facet}{(\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec}) optional,
+specification of the data variable(s) to use for faceting rows.}
 
-\item{col_facet}{(\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec}, optional)
-Variables for column facetting.}
+\item{col_facet}{(\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec}) optional,
+specification of the data variable(s) to use for faceting columns.}
 
-\item{facet}{(\code{logical}, optional) to specify whether the facet encodings \code{ui} elements are toggled
+\item{facet}{(\code{logical}) optional, specifies whether the facet encodings \code{ui} elements are toggled
 on and shown to the user by default. Defaults to \code{TRUE} if either \code{row_facet} or \code{column_facet}
 are supplied.}
 
-\item{color}{(\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec}, optional)
-Variables selected for the outline color inside the coloring settings.
+\item{color}{(\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec}) optional,
+specification of the data variable(s) selected for the outline color inside the coloring settings.
 It will be applied when \code{color_settings} is set to \code{TRUE}.}
 
-\item{fill}{(\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec}, optional)
-Variables selected for the fill color inside the coloring settings.
+\item{fill}{(\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec}) optional,
+specification of the data variable(s) selected for the fill color inside the coloring settings.
 It will be applied when \code{color_settings} is set to \code{TRUE}.}
 
-\item{size}{(\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec}, optional)
-Variables selected for the size of \code{geom_point} plots inside the coloring settings.
+\item{size}{(\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec}) optional,
+specification of the data variable(s) selected for the size of \code{geom_point} plots inside the coloring settings.
 It will be applied when \code{color_settings} is set to \code{TRUE}.}
 
-\item{use_density}{(\code{logical}, optional) Indicates whether to plot density (\code{TRUE}) or frequency (\code{FALSE}).
+\item{use_density}{(\code{logical}) optional, indicates whether to plot density (\code{TRUE}) or frequency (\code{FALSE}).
 Defaults to frequency (\code{FALSE}).}
 
 \item{color_settings}{(\code{logical}) Whether coloring, filling and size should be applied
 and \code{UI} tool offered to the user.}
 
-\item{free_x_scales}{(\code{logical}, optional) Whether X scaling shall be changeable.
+\item{free_x_scales}{(\code{logical}) optional, whether X scaling shall be changeable.
 Does not allow scaling to be changed by default (\code{FALSE}).}
 
-\item{free_y_scales}{(\code{logical}, optional) Whether Y scaling shall be changeable.
+\item{free_y_scales}{(\code{logical}) optional, whether Y scaling shall be changeable.
 Does not allow scaling to be changed by default (\code{FALSE}).}
 
-\item{plot_height}{optional, (\code{numeric}) Specifies the plot height as a three-element vector of
+\item{plot_height}{(\code{numeric}) optional, specifies the plot height as a three-element vector of
 \code{value}, \code{min}, and \code{max} intended for use with a slider UI element.}
 
-\item{plot_width}{optional, (\code{numeric}) Specifies the plot width as a three-element vector of
+\item{plot_width}{(\code{numeric}) optional, specifies the plot width as a three-element vector of
 \code{value}, \code{min}, and \code{max} for a slider encoding the plot width.}
 
-\item{rotate_xaxis_labels}{optional, (\code{logical}) Whether to rotate plot X axis labels. Does not
+\item{rotate_xaxis_labels}{(\code{logical}) optional, whether to rotate plot X axis labels. Does not
 rotate by default (\code{FALSE}).}
 
-\item{swap_axes}{(\code{logical}, optional) Whether to swap X and Y axes. Defaults to \code{FALSE}.}
+\item{swap_axes}{(\code{logical}) optional, whether to swap X and Y axes. Defaults to \code{FALSE}.}
 
-\item{ggtheme}{optional, (\code{character}) \code{ggplot2} theme to be used by default. Defaults to \code{"gray"}.}
+\item{ggtheme}{(\code{character}) optional, \code{ggplot2} theme to be used by default. Defaults to \code{"gray"}.}
 
 \item{ggplot2_args}{(\code{ggplot2_args}) object created by \code{\link[teal.widgets:ggplot2_args]{teal.widgets::ggplot2_args()}}
 with settings for the module plot.
@@ -94,11 +94,11 @@ The argument is merged with options variable \code{teal.ggplot2_args} and defaul
 
 For more details see the vignette: \code{vignette("custom-ggplot2-arguments", package = "teal.widgets")}}
 
-\item{pre_output}{(\code{shiny.tag}, optional) Text or UI element to be displayed before the module's output,
+\item{pre_output}{(\code{shiny.tag}) optional, text or UI element to be displayed before the module's output,
 providing context or a title.
 with text placed before the output to put the output into context. For example a title.}
 
-\item{post_output}{(\code{shiny.tag}, optional) Text or UI element to be displayed after the module's output,
+\item{post_output}{(\code{shiny.tag}) optional, text or UI element to be displayed after the module's output,
 adding context or further instructions. Elements like \code{shiny::helpText()} are useful.}
 }
 \value{
diff --git a/man/tm_g_distribution.Rd b/man/tm_g_distribution.Rd
index dadb2d4c5..df5c8775d 100644
--- a/man/tm_g_distribution.Rd
+++ b/man/tm_g_distribution.Rd
@@ -32,21 +32,20 @@ Categorical variable used to split the distribution analysis.}
 \item{group_var}{(\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec})
 Variable used for faceting plot into multiple panels.}
 
-\item{freq}{(\code{logical}, optional) Whether to display frequency (\code{TRUE}) or density (\code{FALSE}).
+\item{freq}{(\code{logical}) optional, whether to display frequency (\code{TRUE}) or density (\code{FALSE}).
 Defaults to density (\code{FALSE}).}
 
-\item{ggtheme}{optional, (\code{character}) \code{ggplot2} theme to be used by default. Defaults to \code{"gray"}.}
+\item{ggtheme}{(\code{character}) optional, \code{ggplot2} theme to be used by default. Defaults to \code{"gray"}.}
 
-\item{ggplot2_args}{(\code{ggplot2_args} or \verb{named list} of \code{ggplot2_args}s) optional.
-Object created by \code{\link[teal.widgets:ggplot2_args]{teal.widgets::ggplot2_args()}} and contains settings for all the plots,
-or is a named \code{list} of \code{ggplot2_args} objects for plot-specific settings.
+\item{ggplot2_args}{(\code{ggplot2_args}) optional, object created by \code{\link[teal.widgets:ggplot2_args]{teal.widgets::ggplot2_args()}}
+with settings for all the plots or named list of \code{ggplot2_args} objects for plot-specific settings.
 The argument is merged with options variable \code{teal.ggplot2_args} and default module setup.
 
 List names should match the following: \code{c("default", "Histogram", "QQplot")}.
 
 For more details see the vignette: \code{vignette("custom-ggplot2-arguments", package = "teal.widgets")}.}
 
-\item{bins}{(\code{integer(1)} or \code{integer(3)}, optional)  Determines the number of bins for the histogram.
+\item{bins}{(\code{integer(1)} or \code{integer(3)}) optional,  specifies the number of bins for the histogram.
 \itemize{
 \item When the length of \code{bins} is one: The histogram bins will have a fixed size based on the \code{bins} provided.
 \item When the length of \code{bins} is three: The histogram bins are dynamically adjusted based on vector of \code{value}, \code{min},
@@ -54,10 +53,10 @@ and \code{max}.
 Defaults to \code{c(30L, 1L, 100L)}.
 }}
 
-\item{plot_height}{optional, (\code{numeric}) Specifies the plot height as a three-element vector of
+\item{plot_height}{(\code{numeric}) optional, specifies the plot height as a three-element vector of
 \code{value}, \code{min}, and \code{max} intended for use with a slider UI element.}
 
-\item{plot_width}{optional, (\code{numeric}) Specifies the plot width as a three-element vector of
+\item{plot_width}{(\code{numeric}) optional, specifies the plot width as a three-element vector of
 \code{value}, \code{min}, and \code{max} for a slider encoding the plot width.}
 
 \item{pre_output}{(\code{shiny.tag}, optional)\cr
diff --git a/man/tm_g_response.Rd b/man/tm_g_response.Rd
index 772736fad..6e9e1e93c 100644
--- a/man/tm_g_response.Rd
+++ b/man/tm_g_response.Rd
@@ -53,20 +53,20 @@ and the \code{response} variable on the y-axis.}
 Indicates whether to show count labels.
 Defaults to \code{TRUE}.}
 
-\item{rotate_xaxis_labels}{optional, (\code{logical}) Whether to rotate plot X axis labels. Does not
+\item{rotate_xaxis_labels}{(\code{logical}) optional, whether to rotate plot X axis labels. Does not
 rotate by default (\code{FALSE}).}
 
 \item{freq}{(\code{logical(1)})
 Indicates whether to display frequency (\code{TRUE}) or density (\code{FALSE}).
 Defaults to density (\code{FALSE}).}
 
-\item{plot_height}{optional, (\code{numeric}) Specifies the plot height as a three-element vector of
+\item{plot_height}{(\code{numeric}) optional, specifies the plot height as a three-element vector of
 \code{value}, \code{min}, and \code{max} intended for use with a slider UI element.}
 
-\item{plot_width}{optional, (\code{numeric}) Specifies the plot width as a three-element vector of
+\item{plot_width}{(\code{numeric}) optional, specifies the plot width as a three-element vector of
 \code{value}, \code{min}, and \code{max} for a slider encoding the plot width.}
 
-\item{ggtheme}{optional, (\code{character}) \code{ggplot2} theme to be used by default. Defaults to \code{"gray"}.}
+\item{ggtheme}{(\code{character}) optional, \code{ggplot2} theme to be used by default. Defaults to \code{"gray"}.}
 
 \item{ggplot2_args}{(\code{ggplot2_args}) object created by \code{\link[teal.widgets:ggplot2_args]{teal.widgets::ggplot2_args()}}
 with settings for the module plot.
@@ -74,11 +74,11 @@ The argument is merged with options variable \code{teal.ggplot2_args} and defaul
 
 For more details see the vignette: \code{vignette("custom-ggplot2-arguments", package = "teal.widgets")}}
 
-\item{pre_output}{(\code{shiny.tag}, optional) Text or UI element to be displayed before the module's output,
+\item{pre_output}{(\code{shiny.tag}) optional, text or UI element to be displayed before the module's output,
 providing context or a title.
 with text placed before the output to put the output into context. For example a title.}
 
-\item{post_output}{(\code{shiny.tag}, optional) Text or UI element to be displayed after the module's output,
+\item{post_output}{(\code{shiny.tag}) optional, text or UI element to be displayed after the module's output,
 adding context or further instructions. Elements like \code{shiny::helpText()} are useful.}
 }
 \value{
diff --git a/man/tm_g_scatterplot.Rd b/man/tm_g_scatterplot.Rd
index 815fc0931..466294031 100644
--- a/man/tm_g_scatterplot.Rd
+++ b/man/tm_g_scatterplot.Rd
@@ -36,57 +36,57 @@ variable names selected to plot along the x-axis by default.}
 \item{y}{(\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec}) Specifies
 variable names selected to plot along the y-axis by default.}
 
-\item{color_by}{(\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec}, optional)
-Defines the color encoding. If \code{NULL} then no color encoding option will be displayed.}
+\item{color_by}{(\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec}) optional,
+defines the color encoding. If \code{NULL} then no color encoding option will be displayed.}
 
-\item{size_by}{(\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec}, optional)
-Defines the point size encoding. If \code{NULL} then no size encoding option will be displayed.}
+\item{size_by}{(\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec}) optional,
+defines the point size encoding. If \code{NULL} then no size encoding option will be displayed.}
 
-\item{row_facet}{(\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec}, optional)
-Specifies the variable(s) for faceting rows.}
+\item{row_facet}{(\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec}) optional,
+specifies the variable(s) for faceting rows.}
 
-\item{col_facet}{(\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec}, optional)
-Specifies the variable(s) for faceting columns.}
+\item{col_facet}{(\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec}) optional,
+specifies the variable(s) for faceting columns.}
 
-\item{plot_height}{optional, (\code{numeric}) Specifies the plot height as a three-element vector of
+\item{plot_height}{(\code{numeric}) optional, specifies the plot height as a three-element vector of
 \code{value}, \code{min}, and \code{max} intended for use with a slider UI element.}
 
-\item{plot_width}{optional, (\code{numeric}) Specifies the plot width as a three-element vector of
+\item{plot_width}{(\code{numeric}) optional, specifies the plot width as a three-element vector of
 \code{value}, \code{min}, and \code{max} for a slider encoding the plot width.}
 
-\item{alpha}{(\code{integer(1)} or \code{integer(3)}, optional) Specifies point opacity.
+\item{alpha}{(\code{integer(1)} or \code{integer(3)}) optional, specifies point opacity.
 \itemize{
 \item When the length of \code{alpha} is one: the plot points will have a fixed opacity.
 \item When the length of \code{alpha} is three: the plot points opacity are dynamically adjusted based on
 vector of \code{value}, \code{min}, and \code{max}.
 }}
 
-\item{shape}{(\code{character}, optional) A character vector with the names of the
+\item{shape}{(\code{character}) optional, character vector with the names of the
 shape, e.g. \code{c("triangle", "square", "circle")}. It defaults to \code{shape_names}. This is a complete list from
 \code{vignette("ggplot2-specs", package="ggplot2")}.}
 
-\item{size}{(\code{integer(1)} or \code{integer(3)}, optional) Specifies point size.
+\item{size}{(\code{integer(1)} or \code{integer(3)}) optional, specifies point size.
 \itemize{
 \item When the length of \code{size} is one: the plot point sizes will have a fixed size.
 \item When the length of \code{size} is three: the plot points size are dynamically adjusted based on
 vector of \code{value}, \code{min}, and \code{max}.
 }}
 
-\item{max_deg}{(\code{integer}, optional) The maximum degree for the polynomial trend line. Must not be less than 1.}
+\item{max_deg}{(\code{integer}) optional, maximum degree for the polynomial trend line. Must not be less than 1.}
 
-\item{rotate_xaxis_labels}{optional, (\code{logical}) Whether to rotate plot X axis labels. Does not
+\item{rotate_xaxis_labels}{(\code{logical}) optional, whether to rotate plot X axis labels. Does not
 rotate by default (\code{FALSE}).}
 
-\item{ggtheme}{optional, (\code{character}) \code{ggplot2} theme to be used by default. Defaults to \code{"gray"}.}
+\item{ggtheme}{(\code{character}) optional, \code{ggplot2} theme to be used by default. Defaults to \code{"gray"}.}
 
-\item{pre_output}{(\code{shiny.tag}, optional) Text or UI element to be displayed before the module's output,
+\item{pre_output}{(\code{shiny.tag}) optional, text or UI element to be displayed before the module's output,
 providing context or a title.
 with text placed before the output to put the output into context. For example a title.}
 
-\item{post_output}{(\code{shiny.tag}, optional) Text or UI element to be displayed after the module's output,
+\item{post_output}{(\code{shiny.tag}) optional, text or UI element to be displayed after the module's output,
 adding context or further instructions. Elements like \code{shiny::helpText()} are useful.}
 
-\item{table_dec}{(\code{integer}, optional) Number of decimal places used to round numeric values in the table.}
+\item{table_dec}{(\code{integer}) optional, number of decimal places used to round numeric values in the table.}
 
 \item{ggplot2_args}{(\code{ggplot2_args}) object created by \code{\link[teal.widgets:ggplot2_args]{teal.widgets::ggplot2_args()}}
 with settings for the module plot.
diff --git a/man/tm_g_scatterplotmatrix.Rd b/man/tm_g_scatterplotmatrix.Rd
index 46db4256d..65672cb11 100644
--- a/man/tm_g_scatterplotmatrix.Rd
+++ b/man/tm_g_scatterplotmatrix.Rd
@@ -22,17 +22,17 @@ Specifies plotting variables from an incoming dataset with filtering and selecti
 \code{data_extract_spec} use \code{select_spec(..., ordered = TRUE)} if plot elements should be
 rendered according to selection order.}
 
-\item{plot_height}{optional, (\code{numeric}) Specifies the plot height as a three-element vector of
+\item{plot_height}{(\code{numeric}) optional, specifies the plot height as a three-element vector of
 \code{value}, \code{min}, and \code{max} intended for use with a slider UI element.}
 
-\item{plot_width}{optional, (\code{numeric}) Specifies the plot width as a three-element vector of
+\item{plot_width}{(\code{numeric}) optional, specifies the plot width as a three-element vector of
 \code{value}, \code{min}, and \code{max} for a slider encoding the plot width.}
 
-\item{pre_output}{(\code{shiny.tag}, optional) Text or UI element to be displayed before the module's output,
+\item{pre_output}{(\code{shiny.tag}) optional, text or UI element to be displayed before the module's output,
 providing context or a title.
 with text placed before the output to put the output into context. For example a title.}
 
-\item{post_output}{(\code{shiny.tag}, optional) Text or UI element to be displayed after the module's output,
+\item{post_output}{(\code{shiny.tag}) optional, text or UI element to be displayed after the module's output,
 adding context or further instructions. Elements like \code{shiny::helpText()} are useful.}
 }
 \value{
diff --git a/man/tm_missing_data.Rd b/man/tm_missing_data.Rd
index 7cb76d88f..878adeb14 100644
--- a/man/tm_missing_data.Rd
+++ b/man/tm_missing_data.Rd
@@ -21,32 +21,31 @@ tm_missing_data(
 \item{label}{(\code{character(1)}) Label shown in the navigation item for the module or module group.
 For \code{modules()} defaults to \code{"root"}. See \code{Details}.}
 
-\item{plot_height}{optional, (\code{numeric}) Specifies the plot height as a three-element vector of
+\item{plot_height}{(\code{numeric}) optional, specifies the plot height as a three-element vector of
 \code{value}, \code{min}, and \code{max} intended for use with a slider UI element.}
 
-\item{plot_width}{optional, (\code{numeric}) Specifies the plot width as a three-element vector of
+\item{plot_width}{(\code{numeric}) optional, specifies the plot width as a three-element vector of
 \code{value}, \code{min}, and \code{max} for a slider encoding the plot width.}
 
 \item{parent_dataname}{(\code{character(1)}) Specifies the parent dataset name. Default is \code{ADSL} for \code{CDISC} data.
 If provided and exists, enables additional analysis "by subject". For non-\code{CDISC} data, this parameter can be
 ignored.}
 
-\item{ggtheme}{(\code{character}, optional) Specifies the default \code{ggplot2} theme for plots. Defaults to \code{classic}.}
+\item{ggtheme}{(\code{character}) optional, specifies the default \code{ggplot2} theme for plots. Defaults to \code{classic}.}
 
-\item{ggplot2_args}{(\code{ggplot2_args} or \verb{named list} of \code{ggplot2_args}s) optional.
-Object created by \code{\link[teal.widgets:ggplot2_args]{teal.widgets::ggplot2_args()}} and contains settings for all the plots,
-or is a named \code{list} of \code{ggplot2_args} objects for plot-specific settings.
+\item{ggplot2_args}{(\code{ggplot2_args}) optional, object created by \code{\link[teal.widgets:ggplot2_args]{teal.widgets::ggplot2_args()}}
+with settings for all the plots or named list of \code{ggplot2_args} objects for plot-specific settings.
 The argument is merged with options variable \code{teal.ggplot2_args} and default module setup.
 
 List names should match the following: \code{c("default", "Summary Obs", "Summary Patients", "Combinations Main", "Combinations Hist", "By Subject")}.
 
 For more details see the vignette: \code{vignette("custom-ggplot2-arguments", package = "teal.widgets")}.}
 
-\item{pre_output}{(\code{shiny.tag}, optional) Text or UI element to be displayed before the module's output,
+\item{pre_output}{(\code{shiny.tag}) optional, text or UI element to be displayed before the module's output,
 providing context or a title.
 with text placed before the output to put the output into context. For example a title.}
 
-\item{post_output}{(\code{shiny.tag}, optional) Text or UI element to be displayed after the module's output,
+\item{post_output}{(\code{shiny.tag}) optional, text or UI element to be displayed after the module's output,
 adding context or further instructions. Elements like \code{shiny::helpText()} are useful.}
 }
 \value{
diff --git a/man/tm_outliers.Rd b/man/tm_outliers.Rd
index 3e9e705d0..4ca23deeb 100644
--- a/man/tm_outliers.Rd
+++ b/man/tm_outliers.Rd
@@ -23,31 +23,30 @@ For \code{modules()} defaults to \code{"root"}. See \code{Details}.}
 \item{outlier_var}{(\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec})
 Specifies variable(s) to be analyzed for outliers.}
 
-\item{categorical_var}{(\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec}, optional)
-Specifies the categorical variable(s) to split the selected outlier variables on.}
+\item{categorical_var}{(\code{data_extract_spec} or \code{list} of multiple \code{data_extract_spec}) optional,
+specifies the categorical variable(s) to split the selected outlier variables on.}
 
-\item{ggtheme}{optional, (\code{character}) \code{ggplot2} theme to be used by default. Defaults to \code{"gray"}.}
+\item{ggtheme}{(\code{character}) optional, \code{ggplot2} theme to be used by default. Defaults to \code{"gray"}.}
 
-\item{ggplot2_args}{(\code{ggplot2_args} or \verb{named list} of \code{ggplot2_args}s) optional.
-Object created by \code{\link[teal.widgets:ggplot2_args]{teal.widgets::ggplot2_args()}} and contains settings for all the plots,
-or is a named \code{list} of \code{ggplot2_args} objects for plot-specific settings.
+\item{ggplot2_args}{(\code{ggplot2_args}) optional, object created by \code{\link[teal.widgets:ggplot2_args]{teal.widgets::ggplot2_args()}}
+with settings for all the plots or named list of \code{ggplot2_args} objects for plot-specific settings.
 The argument is merged with options variable \code{teal.ggplot2_args} and default module setup.
 
 List names should match the following: \code{c("default", "Boxplot","Density Plot","Cumulative Distribution Plot")}.
 
 For more details see the vignette: \code{vignette("custom-ggplot2-arguments", package = "teal.widgets")}.}
 
-\item{plot_height}{optional, (\code{numeric}) Specifies the plot height as a three-element vector of
+\item{plot_height}{(\code{numeric}) optional, specifies the plot height as a three-element vector of
 \code{value}, \code{min}, and \code{max} intended for use with a slider UI element.}
 
-\item{plot_width}{optional, (\code{numeric}) Specifies the plot width as a three-element vector of
+\item{plot_width}{(\code{numeric}) optional, specifies the plot width as a three-element vector of
 \code{value}, \code{min}, and \code{max} for a slider encoding the plot width.}
 
-\item{pre_output}{(\code{shiny.tag}, optional) Text or UI element to be displayed before the module's output,
+\item{pre_output}{(\code{shiny.tag}) optional, text or UI element to be displayed before the module's output,
 providing context or a title.
 with text placed before the output to put the output into context. For example a title.}
 
-\item{post_output}{(\code{shiny.tag}, optional) Text or UI element to be displayed after the module's output,
+\item{post_output}{(\code{shiny.tag}) optional, text or UI element to be displayed after the module's output,
 adding context or further instructions. Elements like \code{shiny::helpText()} are useful.}
 }
 \value{
diff --git a/man/tm_t_crosstable.Rd b/man/tm_t_crosstable.Rd
index 4bc8a68a9..54b96b06e 100644
--- a/man/tm_t_crosstable.Rd
+++ b/man/tm_t_crosstable.Rd
@@ -37,11 +37,11 @@ Defaults to \code{TRUE}.}
 Indicates whether to show total column.
 Defaults to \code{TRUE}.}
 
-\item{pre_output}{(\code{shiny.tag}, optional) Text or UI element to be displayed before the module's output,
+\item{pre_output}{(\code{shiny.tag}) optional, text or UI element to be displayed before the module's output,
 providing context or a title.
 with text placed before the output to put the output into context. For example a title.}
 
-\item{post_output}{(\code{shiny.tag}, optional) Text or UI element to be displayed after the module's output,
+\item{post_output}{(\code{shiny.tag}) optional, text or UI element to be displayed after the module's output,
 adding context or further instructions. Elements like \code{shiny::helpText()} are useful.}
 
 \item{basic_table_args}{(\code{basic_table_args}) object created by \code{\link[teal.widgets:basic_table_args]{teal.widgets::basic_table_args()}}
diff --git a/man/tm_variable_browser.Rd b/man/tm_variable_browser.Rd
index efe5cbb06..00d3548b7 100644
--- a/man/tm_variable_browser.Rd
+++ b/man/tm_variable_browser.Rd
@@ -28,11 +28,11 @@ allow users to not show variables in other datasets which exist in this \code{da
 This is typically used to remove \code{ADSL} columns in \code{CDISC} data.
 In non \code{CDISC} data this can be ignored. Defaults to \code{"ADSL"}.}
 
-\item{pre_output}{(\code{shiny.tag}, optional) Text or UI element to be displayed before the module's output,
+\item{pre_output}{(\code{shiny.tag}) optional, text or UI element to be displayed before the module's output,
 providing context or a title.
 with text placed before the output to put the output into context. For example a title.}
 
-\item{post_output}{(\code{shiny.tag}, optional) Text or UI element to be displayed after the module's output,
+\item{post_output}{(\code{shiny.tag}) optional, text or UI element to be displayed after the module's output,
 adding context or further instructions. Elements like \code{shiny::helpText()} are useful.}
 
 \item{ggplot2_args}{(\code{ggplot2_args}) object created by \code{\link[teal.widgets:ggplot2_args]{teal.widgets::ggplot2_args()}}

From bf9ef133a7d11da11610d10b0b7aec57c9ad82b6 Mon Sep 17 00:00:00 2001
From: unknown <kirar.kartikeya1@gmail.com>
Date: Thu, 29 Feb 2024 20:11:29 +0530
Subject: [PATCH 50/62] adding package check arg

---
 teal.modules.general.Rproj | 1 +
 1 file changed, 1 insertion(+)

diff --git a/teal.modules.general.Rproj b/teal.modules.general.Rproj
index ea83efd3c..4713d6572 100644
--- a/teal.modules.general.Rproj
+++ b/teal.modules.general.Rproj
@@ -18,4 +18,5 @@ StripTrailingWhitespace: Yes
 BuildType: Package
 PackageUseDevtools: Yes
 PackageInstallArgs: --no-multiarch --with-keep.source
+PackageCheckArgs: --as-cran
 PackageRoxygenize: rd,collate,namespace

From 962e0591159720edaea57aeaed79611394d65db1 Mon Sep 17 00:00:00 2001
From: unknown <kirar.kartikeya1@gmail.com>
Date: Thu, 29 Feb 2024 21:13:27 +0530
Subject: [PATCH 51/62] removing non standard dir to Rbuildignore

---
 .Rbuildignore | 1 +
 1 file changed, 1 insertion(+)

diff --git a/.Rbuildignore b/.Rbuildignore
index bc51aef0c..f8c83ef87 100644
--- a/.Rbuildignore
+++ b/.Rbuildignore
@@ -29,6 +29,7 @@ SECURITY.md
 ^logs$
 ^Makefile$
 ^man/roxygen$
+^man-roxygen$
 ^Meta$
 ^outputdir$
 ^scratch$

From 3929aad939abe4839c15046103e9067058588ee1 Mon Sep 17 00:00:00 2001
From: kartikeya kirar <kirar.kartikeya1@gmail.com>
Date: Fri, 1 Mar 2024 13:34:31 +0530
Subject: [PATCH 52/62] 701 fixing the validation issue for x/y variable
 selection in `tm_g_bivariate`. (#702)

fixes
https://github.com/insightsengineering/teal.modules.general/issues/701
---
 R/tm_g_bivariate.R | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/R/tm_g_bivariate.R b/R/tm_g_bivariate.R
index 2cc65ea80..a879c3e1b 100644
--- a/R/tm_g_bivariate.R
+++ b/R/tm_g_bivariate.R
@@ -586,8 +586,7 @@ srv_g_bivariate <- function(id,
         size <- NULL
       }
 
-
-      teal::validate_has_data(ANL[, c(x_name, y_name)], 3, complete = TRUE, allow_inf = FALSE)
+      teal::validate_has_data(ANL[, c(x_name, y_name), drop = FALSE], 3, complete = TRUE, allow_inf = FALSE)
 
       cl <- bivariate_plot_call(
         data_name = "ANL",

From 6aa97c0b101984edc1b7b95165b9de4adecafb31 Mon Sep 17 00:00:00 2001
From: unknown <kirar.kartikeya1@gmail.com>
Date: Fri, 1 Mar 2024 13:39:21 +0530
Subject: [PATCH 53/62] removing tdata instance

---
 R/tm_variable_browser.R            | 4 ++--
 man/render_single_tab.Rd           | 2 +-
 man/render_tab_header.Rd           | 2 +-
 man/render_tab_table.Rd            | 2 +-
 man/render_tabset_panel_content.Rd | 2 +-
 man/validate_input.Rd              | 2 +-
 6 files changed, 7 insertions(+), 7 deletions(-)

diff --git a/R/tm_variable_browser.R b/R/tm_variable_browser.R
index 61ac5b98f..6d1c2741f 100644
--- a/R/tm_variable_browser.R
+++ b/R/tm_variable_browser.R
@@ -811,7 +811,7 @@ is_num_var_short <- function(.unique_records_for_factor, input, data_for_analysi
 #'
 #' @param input (`session$input`) the shiny session input
 #' @param plot_var (`list`) list of a data frame and an array of variable names
-#' @param data (`tdata`) the datasets passed to the module
+#' @param data (`teal_data`) the datasets passed to the module
 #'
 #' @returns `logical` TRUE if validations pass; a `shiny` validation error otherwise
 #' @keywords internal
@@ -843,7 +843,7 @@ get_plotted_data <- function(input, plot_var, data) {
 #'
 #' @param datanames (`character`) the name of the dataset
 #' @param parent_dataname (`character`) the name of a parent `dataname` to filter out variables from
-#' @param data (`tdata`) the object containing all datasets
+#' @param data (`teal_data`) the object containing all datasets
 #' @param input (`session$input`) the shiny session input
 #' @param output (`session$output`) the shiny session output
 #' @param columns_names (`environment`) the environment containing bindings for each dataset
diff --git a/man/render_single_tab.Rd b/man/render_single_tab.Rd
index c4a98765a..bcd333a61 100644
--- a/man/render_single_tab.Rd
+++ b/man/render_single_tab.Rd
@@ -21,7 +21,7 @@ render_single_tab(
 
 \item{output}{(\code{session$output}) the shiny session output}
 
-\item{data}{(\code{tdata}) the object containing all datasets}
+\item{data}{(\code{teal_data}) the object containing all datasets}
 
 \item{input}{(\code{session$input}) the shiny session input}
 
diff --git a/man/render_tab_header.Rd b/man/render_tab_header.Rd
index 25321a6ba..7119fb83a 100644
--- a/man/render_tab_header.Rd
+++ b/man/render_tab_header.Rd
@@ -11,7 +11,7 @@ render_tab_header(dataset_name, output, data)
 
 \item{output}{(\code{session$output}) the shiny session output}
 
-\item{data}{(\code{tdata}) the object containing all datasets}
+\item{data}{(\code{teal_data}) the object containing all datasets}
 }
 \description{
 Renders the text headlining a single tab in the left-hand side tabset panel
diff --git a/man/render_tab_table.Rd b/man/render_tab_table.Rd
index 152860aa6..64b241c0a 100644
--- a/man/render_tab_table.Rd
+++ b/man/render_tab_table.Rd
@@ -21,7 +21,7 @@ render_tab_table(
 
 \item{output}{(\code{session$output}) the shiny session output}
 
-\item{data}{(\code{tdata}) the object containing all datasets}
+\item{data}{(\code{teal_data}) the object containing all datasets}
 
 \item{input}{(\code{session$input}) the shiny session input}
 
diff --git a/man/render_tabset_panel_content.Rd b/man/render_tabset_panel_content.Rd
index 95c160eb3..9a80fd65e 100644
--- a/man/render_tabset_panel_content.Rd
+++ b/man/render_tabset_panel_content.Rd
@@ -21,7 +21,7 @@ render_tabset_panel_content(
 
 \item{output}{(\code{session$output}) the shiny session output}
 
-\item{data}{(\code{tdata}) the object containing all datasets}
+\item{data}{(\code{teal_data}) the object containing all datasets}
 
 \item{input}{(\code{session$input}) the shiny session input}
 
diff --git a/man/validate_input.Rd b/man/validate_input.Rd
index 37ab1310d..aebaf472e 100644
--- a/man/validate_input.Rd
+++ b/man/validate_input.Rd
@@ -11,7 +11,7 @@ validate_input(input, plot_var, data)
 
 \item{plot_var}{(\code{list}) list of a data frame and an array of variable names}
 
-\item{data}{(\code{tdata}) the datasets passed to the module}
+\item{data}{(\code{teal_data}) the datasets passed to the module}
 }
 \value{
 \code{logical} TRUE if validations pass; a \code{shiny} validation error otherwise

From cbae77906dba7641c2281601b60f6eec82bf3600 Mon Sep 17 00:00:00 2001
From: unknown <kirar.kartikeya1@gmail.com>
Date: Fri, 1 Mar 2024 13:46:48 +0530
Subject: [PATCH 54/62] adding backtick on shiny keyword

---
 R/teal.modules.general.R            | 2 +-
 R/tm_front_page.R                   | 2 +-
 R/tm_variable_browser.R             | 6 +++---
 man/establish_updating_selection.Rd | 2 +-
 man/render_single_tab.Rd            | 4 ++--
 man/render_tab_header.Rd            | 2 +-
 man/render_tab_table.Rd             | 4 ++--
 man/render_tabset_panel_content.Rd  | 4 ++--
 man/teal.modules.general.Rd         | 2 +-
 man/tm_front_page.Rd                | 2 +-
 man/validate_input.Rd               | 2 +-
 11 files changed, 16 insertions(+), 16 deletions(-)

diff --git a/R/teal.modules.general.R b/R/teal.modules.general.R
index b35caf9dc..82f61a562 100644
--- a/R/teal.modules.general.R
+++ b/R/teal.modules.general.R
@@ -1,4 +1,4 @@
-#' `teal.modules.general`: General modules to add to a teal application
+#' `teal.modules.general`: General modules to add to a `teal` application
 #'
 #' The modules in this package are generic modules that should work with any data set
 #' (not necessarily for clinical trials data).
diff --git a/R/tm_front_page.R b/R/tm_front_page.R
index 9ce3464c8..6371a069a 100644
--- a/R/tm_front_page.R
+++ b/R/tm_front_page.R
@@ -8,7 +8,7 @@
 #' element, if named the name is shown first in bold as a header followed by the value. The first
 #' element's header is displayed larger than the others.
 #' @param tables (`named list` of `data.frame`s) tables to be shown in the module.
-#' @param additional_tags (`shiny.tag.list` or `html`) additional shiny tags or `html` to be included after the table,
+#' @param additional_tags (`shiny.tag.list` or `html`) additional `shiny` tags or `html` to be included after the table,
 #' for example to include an image, `tagList(tags$img(src = "image.png"))` or to include further `html`,
 #' `HTML("html text here")`.
 #' @param footnotes (`character` vector) of text to be shown at the bottom of the module, for each
diff --git a/R/tm_variable_browser.R b/R/tm_variable_browser.R
index 6d1c2741f..c90b029c5 100644
--- a/R/tm_variable_browser.R
+++ b/R/tm_variable_browser.R
@@ -809,7 +809,7 @@ is_num_var_short <- function(.unique_records_for_factor, input, data_for_analysi
 
 #' Validates the variable browser inputs
 #'
-#' @param input (`session$input`) the shiny session input
+#' @param input (`session$input`) the `shiny` session input
 #' @param plot_var (`list`) list of a data frame and an array of variable names
 #' @param data (`teal_data`) the datasets passed to the module
 #'
@@ -844,8 +844,8 @@ get_plotted_data <- function(input, plot_var, data) {
 #' @param datanames (`character`) the name of the dataset
 #' @param parent_dataname (`character`) the name of a parent `dataname` to filter out variables from
 #' @param data (`teal_data`) the object containing all datasets
-#' @param input (`session$input`) the shiny session input
-#' @param output (`session$output`) the shiny session output
+#' @param input (`session$input`) the `shiny` session input
+#' @param output (`session$output`) the `shiny` session output
 #' @param columns_names (`environment`) the environment containing bindings for each dataset
 #' @param plot_var (`list`) the list containing the currently selected dataset (tab) and its column names
 #' @keywords internal
diff --git a/man/establish_updating_selection.Rd b/man/establish_updating_selection.Rd
index d4ed4f7f3..112001743 100644
--- a/man/establish_updating_selection.Rd
+++ b/man/establish_updating_selection.Rd
@@ -9,7 +9,7 @@ establish_updating_selection(datanames, input, plot_var, columns_names)
 \arguments{
 \item{datanames}{(\code{character}) the name of the dataset}
 
-\item{input}{(\code{session$input}) the shiny session input}
+\item{input}{(\code{session$input}) the \code{shiny} session input}
 
 \item{plot_var}{(\code{list}) the list containing the currently selected dataset (tab) and its column names}
 
diff --git a/man/render_single_tab.Rd b/man/render_single_tab.Rd
index bcd333a61..015539a1d 100644
--- a/man/render_single_tab.Rd
+++ b/man/render_single_tab.Rd
@@ -19,11 +19,11 @@ render_single_tab(
 
 \item{parent_dataname}{(\code{character}) the name of a parent \code{dataname} to filter out variables from}
 
-\item{output}{(\code{session$output}) the shiny session output}
+\item{output}{(\code{session$output}) the \code{shiny} session output}
 
 \item{data}{(\code{teal_data}) the object containing all datasets}
 
-\item{input}{(\code{session$input}) the shiny session input}
+\item{input}{(\code{session$input}) the \code{shiny} session input}
 
 \item{columns_names}{(\code{environment}) the environment containing bindings for each dataset}
 
diff --git a/man/render_tab_header.Rd b/man/render_tab_header.Rd
index 7119fb83a..a78896088 100644
--- a/man/render_tab_header.Rd
+++ b/man/render_tab_header.Rd
@@ -9,7 +9,7 @@ render_tab_header(dataset_name, output, data)
 \arguments{
 \item{dataset_name}{(\code{character}) the name of the dataset of the tab}
 
-\item{output}{(\code{session$output}) the shiny session output}
+\item{output}{(\code{session$output}) the \code{shiny} session output}
 
 \item{data}{(\code{teal_data}) the object containing all datasets}
 }
diff --git a/man/render_tab_table.Rd b/man/render_tab_table.Rd
index 64b241c0a..c5eebb929 100644
--- a/man/render_tab_table.Rd
+++ b/man/render_tab_table.Rd
@@ -19,11 +19,11 @@ render_tab_table(
 
 \item{parent_dataname}{(\code{character}) the name of a parent \code{dataname} to filter out variables from}
 
-\item{output}{(\code{session$output}) the shiny session output}
+\item{output}{(\code{session$output}) the \code{shiny} session output}
 
 \item{data}{(\code{teal_data}) the object containing all datasets}
 
-\item{input}{(\code{session$input}) the shiny session input}
+\item{input}{(\code{session$input}) the \code{shiny} session input}
 
 \item{columns_names}{(\code{environment}) the environment containing bindings for each dataset}
 
diff --git a/man/render_tabset_panel_content.Rd b/man/render_tabset_panel_content.Rd
index 9a80fd65e..b28a95c90 100644
--- a/man/render_tabset_panel_content.Rd
+++ b/man/render_tabset_panel_content.Rd
@@ -19,11 +19,11 @@ render_tabset_panel_content(
 
 \item{parent_dataname}{(\code{character}) the name of a parent \code{dataname} to filter out variables from}
 
-\item{output}{(\code{session$output}) the shiny session output}
+\item{output}{(\code{session$output}) the \code{shiny} session output}
 
 \item{data}{(\code{teal_data}) the object containing all datasets}
 
-\item{input}{(\code{session$input}) the shiny session input}
+\item{input}{(\code{session$input}) the \code{shiny} session input}
 
 \item{columns_names}{(\code{environment}) the environment containing bindings for each dataset}
 
diff --git a/man/teal.modules.general.Rd b/man/teal.modules.general.Rd
index 6c36e3436..718d336fd 100644
--- a/man/teal.modules.general.Rd
+++ b/man/teal.modules.general.Rd
@@ -4,7 +4,7 @@
 \name{teal.modules.general}
 \alias{teal.modules.general-package}
 \alias{teal.modules.general}
-\title{\code{teal.modules.general}: General modules to add to a teal application}
+\title{\code{teal.modules.general}: General modules to add to a \code{teal} application}
 \description{
 The modules in this package are generic modules that should work with any data set
 (not necessarily for clinical trials data).
diff --git a/man/tm_front_page.Rd b/man/tm_front_page.Rd
index 31ba69019..801bbd00e 100644
--- a/man/tm_front_page.Rd
+++ b/man/tm_front_page.Rd
@@ -23,7 +23,7 @@ element's header is displayed larger than the others.}
 
 \item{tables}{(\verb{named list} of \code{data.frame}s) tables to be shown in the module.}
 
-\item{additional_tags}{(\code{shiny.tag.list} or \code{html}) additional shiny tags or \code{html} to be included after the table,
+\item{additional_tags}{(\code{shiny.tag.list} or \code{html}) additional \code{shiny} tags or \code{html} to be included after the table,
 for example to include an image, \code{tagList(tags$img(src = "image.png"))} or to include further \code{html},
 \code{HTML("html text here")}.}
 
diff --git a/man/validate_input.Rd b/man/validate_input.Rd
index aebaf472e..e9c21581e 100644
--- a/man/validate_input.Rd
+++ b/man/validate_input.Rd
@@ -7,7 +7,7 @@
 validate_input(input, plot_var, data)
 }
 \arguments{
-\item{input}{(\code{session$input}) the shiny session input}
+\item{input}{(\code{session$input}) the \code{shiny} session input}
 
 \item{plot_var}{(\code{list}) list of a data frame and an array of variable names}
 

From 8151b06cfc8a1a1566a9940a27c1f802db0cf771 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Andr=C3=A9=20Ver=C3=ADssimo?=
 <211358+averissimo@users.noreply.github.com>
Date: Fri, 1 Mar 2024 10:50:40 +0100
Subject: [PATCH 55/62] Adds missing assertions and reorganizes them (#696)
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

# Pull Request

- Fixes #686
- Part of #624

#### Changes descriptions

- Adds missing assertions described on #686
- Adds a helper function called `assert_single_selection`
- Avoids many repetitive calls across functions to check for multiple
selections
  - Adds simple unit tests
- Adds some comments to maintain a consistent structure

---------

Signed-off-by: André Veríssimo <211358+averissimo@users.noreply.github.com>
Co-authored-by: Dawid Kałędkowski <6959016+gogonzo@users.noreply.github.com>
---
 R/tm_a_pca.R                         |  46 +++--
 R/tm_a_regression.R                  |   8 +-
 R/tm_data_table.R                    |  10 +-
 R/tm_file_viewer.R                   |  18 +-
 R/tm_front_page.R                    |   6 +-
 R/tm_g_association.R                 |  13 ++
 R/tm_g_bivariate.R                   |  80 ++++----
 R/tm_g_distribution.R                |  36 +++-
 R/tm_g_response.R                    |  23 ++-
 R/tm_g_scatterplot.R                 |  45 +++--
 R/tm_g_scatterplotmatrix.R           |  12 ++
 R/tm_missing_data.R                  |  16 +-
 R/tm_outliers.R                      |  21 +-
 R/tm_t_crosstable.R                  |  15 +-
 R/tm_variable_browser.R              |   8 +
 R/utils.R                            |  12 ++
 tests/testthat/helper-functions.R    |  22 ++
 tests/testthat/test-tm_g_bivariate.R | 287 +++++++++++++++++++++++++++
 18 files changed, 567 insertions(+), 111 deletions(-)
 create mode 100644 tests/testthat/helper-functions.R
 create mode 100644 tests/testthat/test-tm_g_bivariate.R

diff --git a/R/tm_a_pca.R b/R/tm_a_pca.R
index 8d7ef14e2..f2073ee2c 100644
--- a/R/tm_a_pca.R
+++ b/R/tm_a_pca.R
@@ -106,14 +106,38 @@ tm_a_pca <- function(label = "Principal Component Analysis",
                      pre_output = NULL,
                      post_output = NULL) {
   logger::log_info("Initializing tm_a_pca")
+
+  # Normalize the parameters
   if (inherits(dat, "data_extract_spec")) dat <- list(dat)
   if (inherits(ggplot2_args, "ggplot2_args")) ggplot2_args <- list(default = ggplot2_args)
 
+  # Start of assertions
   checkmate::assert_string(label)
   checkmate::assert_list(dat, types = "data_extract_spec")
+
+  checkmate::assert_numeric(plot_height, len = 3, any.missing = FALSE, finite = TRUE)
+  checkmate::assert_numeric(plot_height[1], lower = plot_height[2], upper = plot_height[3], .var.name = "plot_height")
+  checkmate::assert_numeric(plot_width, len = 3, any.missing = FALSE, null.ok = TRUE, finite = TRUE)
+  checkmate::assert_numeric(
+    plot_width[1],
+    lower = plot_width[2], upper = plot_width[3], null.ok = TRUE, .var.name = "plot_width"
+  )
+
   ggtheme <- match.arg(ggtheme)
+
+  plot_choices <- c("Elbow plot", "Circle plot", "Biplot", "Eigenvector plot")
+  checkmate::assert_list(ggplot2_args, types = "ggplot2_args")
+  checkmate::assert_subset(names(ggplot2_args), c("default", plot_choices))
+
   checkmate::assert_flag(rotate_xaxis_labels)
 
+  if (length(font_size) == 1) {
+    checkmate::assert_numeric(font_size, any.missing = FALSE, finite = TRUE, lower = 8, upper = 20)
+  } else {
+    checkmate::assert_numeric(font_size, len = 3, any.missing = FALSE, finite = TRUE, lower = 8, upper = 20)
+    checkmate::assert_numeric(font_size[1], lower = font_size[2], upper = font_size[3], .var.name = "font_size")
+  }
+
   if (length(alpha) == 1) {
     checkmate::assert_numeric(alpha, any.missing = FALSE, finite = TRUE, lower = 0, upper = 1)
   } else {
@@ -128,25 +152,11 @@ tm_a_pca <- function(label = "Principal Component Analysis",
     checkmate::assert_numeric(size[1], lower = size[2], upper = size[3], .var.name = "size")
   }
 
-  if (length(font_size) == 1) {
-    checkmate::assert_numeric(font_size, any.missing = FALSE, finite = TRUE, lower = 8, upper = 20)
-  } else {
-    checkmate::assert_numeric(font_size, len = 3, any.missing = FALSE, finite = TRUE, lower = 8, upper = 20)
-    checkmate::assert_numeric(font_size[1], lower = font_size[2], upper = font_size[3], .var.name = "font_size")
-  }
-
-  checkmate::assert_numeric(plot_height, len = 3, any.missing = FALSE, finite = TRUE)
-  checkmate::assert_numeric(plot_height[1], lower = plot_height[2], upper = plot_height[3], .var.name = "plot_height")
-  checkmate::assert_numeric(plot_width, len = 3, any.missing = FALSE, null.ok = TRUE, finite = TRUE)
-  checkmate::assert_numeric(
-    plot_width[1],
-    lower = plot_width[2], upper = plot_width[3], null.ok = TRUE, .var.name = "plot_width"
-  )
-
-  plot_choices <- c("Elbow plot", "Circle plot", "Biplot", "Eigenvector plot")
-  checkmate::assert_list(ggplot2_args, types = "ggplot2_args")
-  checkmate::assert_subset(names(ggplot2_args), c("default", plot_choices))
+  checkmate::assert_multi_class(pre_output, c("shiny.tag", "shiny.tag.list", "html"), null.ok = TRUE)
+  checkmate::assert_multi_class(post_output, c("shiny.tag", "shiny.tag.list", "html"), null.ok = TRUE)
+  # End of assertions
 
+  # Make UI args
   args <- as.list(environment())
 
   data_extract_list <- list(dat = dat)
diff --git a/R/tm_a_regression.R b/R/tm_a_regression.R
index 9093d3919..dc06b8ef0 100644
--- a/R/tm_a_regression.R
+++ b/R/tm_a_regression.R
@@ -162,9 +162,7 @@ tm_a_regression <- function(label = "Regression Analysis",
   checkmate::assert_list(regressor, types = "data_extract_spec")
 
   checkmate::assert_list(response, types = "data_extract_spec")
-  if (!all(vapply(response, function(x) !(x$select$multiple), logical(1)))) {
-    stop("'response' should not allow multiple selection")
-  }
+  assert_single_selection(response)
 
   checkmate::assert_numeric(plot_height, len = 3, any.missing = FALSE, finite = TRUE)
   checkmate::assert_numeric(plot_height[1], lower = plot_height[2], upper = plot_height[3], .var.name = "plot_height")
@@ -203,7 +201,7 @@ tm_a_regression <- function(label = "Regression Analysis",
 
   checkmate::assert_multi_class(pre_output, c("shiny.tag", "shiny.tag.list", "html"), null.ok = TRUE)
   checkmate::assert_multi_class(post_output, c("shiny.tag", "shiny.tag.list", "html"), null.ok = TRUE)
-  checkmate::assert_integerish(default_plot_type, lower = 1, upper = 7)
+  checkmate::assert_choice(default_plot_type, seq.int(1L, length(plot_choices)))
   checkmate::assert_string(default_outlier_label)
 
   if (length(label_segment_threshold) == 1) {
@@ -219,7 +217,7 @@ tm_a_regression <- function(label = "Regression Analysis",
   }
   # End of assertions
 
-  # Send ui args
+  # Make UI args
   args <- as.list(environment())
   args[["plot_choices"]] <- plot_choices
   data_extract_list <- list(
diff --git a/R/tm_data_table.R b/R/tm_data_table.R
index 33a88db34..9116fd34d 100644
--- a/R/tm_data_table.R
+++ b/R/tm_data_table.R
@@ -91,7 +91,10 @@ tm_data_table <- function(label = "Data Table",
                           pre_output = NULL,
                           post_output = NULL) {
   logger::log_info("Initializing tm_data_table")
+
+  # Start of assertions
   checkmate::assert_string(label)
+
   checkmate::assert_list(variables_selected, min.len = 0, types = "character", names = "named")
   if (length(variables_selected) > 0) {
     lapply(seq_along(variables_selected), function(i) {
@@ -101,14 +104,17 @@ tm_data_table <- function(label = "Data Table",
       }
     })
   }
+
   checkmate::assert_character(datasets_selected, min.len = 0, min.chars = 1)
-  checkmate::assert_list(dt_options, names = "named")
   checkmate::assert(
     checkmate::check_list(dt_args, len = 0),
     checkmate::check_subset(names(dt_args), choices = names(formals(DT::datatable)))
   )
-
+  checkmate::assert_list(dt_options, names = "named")
   checkmate::assert_flag(server_rendering)
+  checkmate::assert_multi_class(pre_output, c("shiny.tag", "shiny.tag.list", "html"), null.ok = TRUE)
+  checkmate::assert_multi_class(post_output, c("shiny.tag", "shiny.tag.list", "html"), null.ok = TRUE)
+  # End of assertions
 
   module(
     label,
diff --git a/R/tm_file_viewer.R b/R/tm_file_viewer.R
index edcc354d4..48ec04162 100644
--- a/R/tm_file_viewer.R
+++ b/R/tm_file_viewer.R
@@ -42,25 +42,24 @@
 tm_file_viewer <- function(label = "File Viewer Module",
                            input_path = list("Current Working Directory" = ".")) {
   logger::log_info("Initializing tm_file_viewer")
-  if (length(label) == 0 || identical(label, "")) {
-    label <- " "
-  }
-  if (length(input_path) == 0 || identical(input_path, "")) {
-    input_path <- list()
-  }
 
+  # Normalize the parameters
+  if (length(label) == 0 || identical(label, "")) label <- " "
+  if (length(input_path) == 0 || identical(input_path, "")) input_path <- list()
+
+  # Start of assertions
   checkmate::assert_string(label)
+
   checkmate::assert(
     checkmate::check_list(input_path, types = "character", min.len = 0),
     checkmate::check_character(input_path, min.len = 1)
   )
-
   if (length(input_path) > 0) {
     valid_url <- function(url_input, timeout = 2) {
       con <- try(url(url_input), silent = TRUE)
       check <- suppressWarnings(try(open.connection(con, open = "rt", timeout = timeout), silent = TRUE)[1])
       try(close.connection(con), silent = TRUE)
-      ifelse(is.null(check), TRUE, FALSE)
+      is.null(check)
     }
     idx <- vapply(input_path, function(x) file.exists(x) || valid_url(x), logical(1))
 
@@ -78,8 +77,9 @@ tm_file_viewer <- function(label = "File Viewer Module",
       "No file or url paths were provided."
     )
   }
+  # End of assertions
 
-
+  # Make UI args
   args <- as.list(environment())
 
   module(
diff --git a/R/tm_front_page.R b/R/tm_front_page.R
index 6371a069a..ab251fc1d 100644
--- a/R/tm_front_page.R
+++ b/R/tm_front_page.R
@@ -67,14 +67,18 @@ tm_front_page <- function(label = "Front page",
                           additional_tags = tagList(),
                           footnotes = character(0),
                           show_metadata = FALSE) {
+  logger::log_info("Initializing tm_front_page")
+
+  # Start of assertions
   checkmate::assert_string(label)
   checkmate::assert_character(header_text, min.len = 0, any.missing = FALSE)
   checkmate::assert_list(tables, types = "data.frame", names = "named", any.missing = FALSE)
   checkmate::assert_multi_class(additional_tags, classes = c("shiny.tag.list", "html"))
   checkmate::assert_character(footnotes, min.len = 0, any.missing = FALSE)
   checkmate::assert_flag(show_metadata)
+  # End of assertions
 
-  logger::log_info("Initializing tm_front_page")
+  # Make UI args
   args <- as.list(environment())
 
   module(
diff --git a/R/tm_g_association.R b/R/tm_g_association.R
index 6e93f4a24..eb47b00d7 100644
--- a/R/tm_g_association.R
+++ b/R/tm_g_association.R
@@ -133,17 +133,23 @@ tm_g_association <- function(label = "Association",
                              post_output = NULL,
                              ggplot2_args = teal.widgets::ggplot2_args()) {
   logger::log_info("Initializing tm_g_association")
+
+  # Normalize the parameters
   if (inherits(ref, "data_extract_spec")) ref <- list(ref)
   if (inherits(vars, "data_extract_spec")) vars <- list(vars)
   if (inherits(ggplot2_args, "ggplot2_args")) ggplot2_args <- list(default = ggplot2_args)
 
+  # Start of assertions
   checkmate::assert_string(label)
+
   checkmate::assert_list(ref, types = "data_extract_spec")
   if (!all(vapply(ref, function(x) !x$select$multiple, logical(1)))) {
     stop("'ref' should not allow multiple selection")
   }
+
   checkmate::assert_list(vars, types = "data_extract_spec")
   checkmate::assert_flag(show_association)
+
   checkmate::assert_numeric(plot_height, len = 3, any.missing = FALSE, finite = TRUE)
   checkmate::assert_numeric(plot_height[1], lower = plot_height[2], upper = plot_height[3], .var.name = "plot_height")
   checkmate::assert_numeric(plot_width, len = 3, any.missing = FALSE, null.ok = TRUE, finite = TRUE)
@@ -151,12 +157,19 @@ tm_g_association <- function(label = "Association",
     plot_width[1],
     lower = plot_width[2], upper = plot_width[3], null.ok = TRUE, .var.name = "plot_width"
   )
+
   distribution_theme <- match.arg(distribution_theme)
   association_theme <- match.arg(association_theme)
+
+  checkmate::assert_multi_class(pre_output, c("shiny.tag", "shiny.tag.list", "html"), null.ok = TRUE)
+  checkmate::assert_multi_class(post_output, c("shiny.tag", "shiny.tag.list", "html"), null.ok = TRUE)
+
   plot_choices <- c("Bivariate1", "Bivariate2")
   checkmate::assert_list(ggplot2_args, types = "ggplot2_args")
   checkmate::assert_subset(names(ggplot2_args), c("default", plot_choices))
+  # End of assertions
 
+  # Make UI args
   args <- as.list(environment())
 
   data_extract_list <- list(
diff --git a/R/tm_g_bivariate.R b/R/tm_g_bivariate.R
index a879c3e1b..122d2e1b2 100644
--- a/R/tm_g_bivariate.R
+++ b/R/tm_g_bivariate.R
@@ -194,6 +194,8 @@ tm_g_bivariate <- function(label = "Bivariate Plots",
                            pre_output = NULL,
                            post_output = NULL) {
   logger::log_info("Initializing tm_g_bivariate")
+
+  # Normalize the parameters
   if (inherits(x, "data_extract_spec")) x <- list(x)
   if (inherits(y, "data_extract_spec")) y <- list(y)
   if (inherits(row_facet, "data_extract_spec")) row_facet <- list(row_facet)
@@ -202,52 +204,36 @@ tm_g_bivariate <- function(label = "Bivariate Plots",
   if (inherits(fill, "data_extract_spec")) fill <- list(fill)
   if (inherits(size, "data_extract_spec")) size <- list(size)
 
+  # Start of assertions
+  checkmate::assert_string(label)
+
   checkmate::assert_list(x, types = "data_extract_spec")
-  if (!all(vapply(x, function(x) !x$select$multiple, logical(1)))) {
-    stop("'x' should not allow multiple selection")
-  }
+  assert_single_selection(x)
+
   checkmate::assert_list(y, types = "data_extract_spec")
-  if (!all(vapply(y, function(x) !x$select$multiple, logical(1)))) {
-    stop("'y' should not allow multiple selection")
-  }
+  assert_single_selection(y)
+
   checkmate::assert_list(row_facet, types = "data_extract_spec", null.ok = TRUE)
-  if (!all(vapply(row_facet, function(x) !x$select$multiple, logical(1)))) {
-    stop("'row_facet' should not allow multiple selection")
-  }
+  assert_single_selection(row_facet)
+
   checkmate::assert_list(col_facet, types = "data_extract_spec", null.ok = TRUE)
-  if (!all(vapply(col_facet, function(x) !x$select$multiple, logical(1)))) {
-    stop("'col_facet' should not allow multiple selection")
-  }
+  assert_single_selection(col_facet)
+
+  checkmate::assert_flag(facet)
+
   checkmate::assert_list(color, types = "data_extract_spec", null.ok = TRUE)
-  if (!all(vapply(color, function(x) !x$select$multiple, logical(1)))) {
-    stop("'color' should not allow multiple selection")
-  }
+  assert_single_selection(color)
+
   checkmate::assert_list(fill, types = "data_extract_spec", null.ok = TRUE)
-  if (!all(vapply(fill, function(x) !x$select$multiple, logical(1)))) {
-    stop("'fill' should not allow multiple selection")
-  }
+  assert_single_selection(fill)
+
   checkmate::assert_list(size, types = "data_extract_spec", null.ok = TRUE)
-  if (!all(vapply(size, function(x) !x$select$multiple, logical(1)))) {
-    stop("'size' should not allow multiple selection")
-  }
+  assert_single_selection(size)
 
-  ggtheme <- match.arg(ggtheme)
-  checkmate::assert_string(label)
   checkmate::assert_flag(use_density)
-  checkmate::assert_flag(color_settings)
-  checkmate::assert_flag(free_x_scales)
-  checkmate::assert_flag(free_y_scales)
-  checkmate::assert_flag(rotate_xaxis_labels)
-  checkmate::assert_flag(swap_axes)
-  checkmate::assert_numeric(plot_height, len = 3, any.missing = FALSE, finite = TRUE)
-  checkmate::assert_numeric(plot_height[1], lower = plot_height[2], upper = plot_height[3], .var.name = "plot_height")
-  checkmate::assert_numeric(plot_width, len = 3, any.missing = FALSE, null.ok = TRUE, finite = TRUE)
-  checkmate::assert_numeric(
-    plot_width[1],
-    lower = plot_width[2], upper = plot_width[3], null.ok = TRUE, .var.name = "plot_width"
-  )
-  checkmate::assert_class(ggplot2_args, "ggplot2_args")
 
+  # Determines color, fill & size if they are not explicitly set
+  checkmate::assert_flag(color_settings)
   if (color_settings) {
     if (is.null(color)) {
       color <- x
@@ -267,6 +253,28 @@ tm_g_bivariate <- function(label = "Bivariate Plots",
     }
   }
 
+  checkmate::assert_flag(free_x_scales)
+  checkmate::assert_flag(free_y_scales)
+
+  checkmate::assert_numeric(plot_height, len = 3, any.missing = FALSE, finite = TRUE)
+  checkmate::assert_numeric(plot_height[1], lower = plot_height[2], upper = plot_height[3], .var.name = "plot_height")
+  checkmate::assert_numeric(plot_width, len = 3, any.missing = FALSE, null.ok = TRUE, finite = TRUE)
+  checkmate::assert_numeric(
+    plot_width[1],
+    lower = plot_width[2], upper = plot_width[3], null.ok = TRUE, .var.name = "plot_width"
+  )
+
+  checkmate::assert_flag(rotate_xaxis_labels)
+  checkmate::assert_flag(swap_axes)
+
+  ggtheme <- match.arg(ggtheme)
+  checkmate::assert_class(ggplot2_args, "ggplot2_args")
+
+  checkmate::assert_multi_class(pre_output, c("shiny.tag", "shiny.tag.list", "html"), null.ok = TRUE)
+  checkmate::assert_multi_class(post_output, c("shiny.tag", "shiny.tag.list", "html"), null.ok = TRUE)
+  # End of assertions
+
+  # Make UI args
   args <- as.list(environment())
 
   data_extract_list <- list(
diff --git a/R/tm_g_distribution.R b/R/tm_g_distribution.R
index edac703e8..66d524784 100644
--- a/R/tm_g_distribution.R
+++ b/R/tm_g_distribution.R
@@ -121,6 +121,7 @@ tm_g_distribution <- function(label = "Distribution Module",
                               post_output = NULL) {
   logger::log_info("Initializing tm_g_distribution")
 
+  # Requires Suggested packages
   extra_packages <- c("ggpmisc", "ggpp", "goftest", "MASS", "broom")
   missing_packages <- Filter(function(x) !requireNamespace(x, quietly = TRUE), extra_packages)
   if (length(missing_packages) > 0L) {
@@ -130,28 +131,47 @@ tm_g_distribution <- function(label = "Distribution Module",
     ))
   }
 
+  # Normalize the parameters
   if (inherits(dist_var, "data_extract_spec")) dist_var <- list(dist_var)
   if (inherits(strata_var, "data_extract_spec")) strata_var <- list(strata_var)
   if (inherits(group_var, "data_extract_spec")) group_var <- list(group_var)
   if (inherits(ggplot2_args, "ggplot2_args")) ggplot2_args <- list(default = ggplot2_args)
 
-  ggtheme <- match.arg(ggtheme)
-  if (length(bins) == 1) {
-    checkmate::assert_numeric(bins, any.missing = FALSE, lower = 1)
-  } else {
-    checkmate::assert_numeric(bins, len = 3, any.missing = FALSE, lower = 1)
-    checkmate::assert_numeric(bins[1], lower = bins[2], upper = bins[3], .var.name = "bins")
-  }
+  # Start of assertions
   checkmate::assert_string(label)
+
   checkmate::assert_list(dist_var, "data_extract_spec")
-  checkmate::assert_false(dist_var[[1]]$select$multiple)
+  checkmate::assert_false(dist_var[[1L]]$select$multiple)
+
   checkmate::assert_list(strata_var, types = "data_extract_spec", null.ok = TRUE)
   checkmate::assert_list(group_var, types = "data_extract_spec", null.ok = TRUE)
   checkmate::assert_flag(freq)
+  ggtheme <- match.arg(ggtheme)
+
   plot_choices <- c("Histogram", "QQplot")
   checkmate::assert_list(ggplot2_args, types = "ggplot2_args")
   checkmate::assert_subset(names(ggplot2_args), c("default", plot_choices))
 
+  if (length(bins) == 1) {
+    checkmate::assert_numeric(bins, any.missing = FALSE, lower = 1)
+  } else {
+    checkmate::assert_numeric(bins, len = 3, any.missing = FALSE, lower = 1)
+    checkmate::assert_numeric(bins[1], lower = bins[2], upper = bins[3], .var.name = "bins")
+  }
+
+  checkmate::assert_numeric(plot_height, len = 3, any.missing = FALSE, finite = TRUE)
+  checkmate::assert_numeric(plot_height[1], lower = plot_height[2], upper = plot_height[3], .var.name = "plot_height")
+  checkmate::assert_numeric(plot_width, len = 3, any.missing = FALSE, null.ok = TRUE, finite = TRUE)
+  checkmate::assert_numeric(
+    plot_width[1],
+    lower = plot_width[2], upper = plot_width[3], null.ok = TRUE, .var.name = "plot_width"
+  )
+
+  checkmate::assert_multi_class(pre_output, c("shiny.tag", "shiny.tag.list", "html"), null.ok = TRUE)
+  checkmate::assert_multi_class(post_output, c("shiny.tag", "shiny.tag.list", "html"), null.ok = TRUE)
+  # End of assertions
+
+  # Make UI args
   args <- as.list(environment())
 
   data_extract_list <- list(
diff --git a/R/tm_g_response.R b/R/tm_g_response.R
index 3abba6266..12beb4f94 100644
--- a/R/tm_g_response.R
+++ b/R/tm_g_response.R
@@ -152,32 +152,35 @@ tm_g_response <- function(label = "Response Plot",
                           pre_output = NULL,
                           post_output = NULL) {
   logger::log_info("Initializing tm_g_response")
+
+  # Normalize the parameters
   if (inherits(response, "data_extract_spec")) response <- list(response)
   if (inherits(x, "data_extract_spec")) x <- list(x)
   if (inherits(row_facet, "data_extract_spec")) row_facet <- list(row_facet)
   if (inherits(col_facet, "data_extract_spec")) col_facet <- list(col_facet)
+
+  # Start of assertions
   checkmate::assert_string(label)
-  ggtheme <- match.arg(ggtheme)
+
   checkmate::assert_list(response, types = "data_extract_spec")
   if (!all(vapply(response, function(x) !("" %in% x$select$choices), logical(1)))) {
     stop("'response' should not allow empty values")
   }
-  if (!all(vapply(response, function(x) !x$select$multiple, logical(1)))) {
-    stop("'response' should not allow multiple selection")
-  }
+  assert_single_selection(response)
+
   checkmate::assert_list(x, types = "data_extract_spec")
   if (!all(vapply(x, function(x) !("" %in% x$select$choices), logical(1)))) {
     stop("'x' should not allow empty values")
   }
-  if (!all(vapply(x, function(x) !x$select$multiple, logical(1)))) {
-    stop("'x' should not allow multiple selection")
-  }
+  assert_single_selection(x)
+
   checkmate::assert_list(row_facet, types = "data_extract_spec", null.ok = TRUE)
   checkmate::assert_list(col_facet, types = "data_extract_spec", null.ok = TRUE)
   checkmate::assert_flag(coord_flip)
   checkmate::assert_flag(count_labels)
   checkmate::assert_flag(rotate_xaxis_labels)
   checkmate::assert_flag(freq)
+
   checkmate::assert_numeric(plot_height, len = 3, any.missing = FALSE, finite = TRUE)
   checkmate::assert_numeric(plot_height[1], lower = plot_height[2], upper = plot_height[3], .var.name = "plot_height")
   checkmate::assert_numeric(plot_width, len = 3, any.missing = FALSE, null.ok = TRUE, finite = TRUE)
@@ -186,8 +189,14 @@ tm_g_response <- function(label = "Response Plot",
     lower = plot_width[2], upper = plot_width[3], null.ok = TRUE, .var.name = "plot_width"
   )
 
+  ggtheme <- match.arg(ggtheme)
   checkmate::assert_class(ggplot2_args, "ggplot2_args")
 
+  checkmate::assert_multi_class(pre_output, c("shiny.tag", "shiny.tag.list", "html"), null.ok = TRUE)
+  checkmate::assert_multi_class(post_output, c("shiny.tag", "shiny.tag.list", "html"), null.ok = TRUE)
+  # End of assertions
+
+  # Make UI args
   args <- as.list(environment())
 
   data_extract_list <- list(
diff --git a/R/tm_g_scatterplot.R b/R/tm_g_scatterplot.R
index 00efed7cf..d90f6c43a 100644
--- a/R/tm_g_scatterplot.R
+++ b/R/tm_g_scatterplot.R
@@ -229,6 +229,7 @@ tm_g_scatterplot <- function(label = "Scatterplot",
                              ggplot2_args = teal.widgets::ggplot2_args()) {
   logger::log_info("Initializing tm_g_scatterplot")
 
+  # Requires Suggested packages
   extra_packages <- c("ggpmisc", "ggExtra", "colourpicker")
   missing_packages <- Filter(function(x) !requireNamespace(x, quietly = TRUE), extra_packages)
   if (length(missing_packages) > 0L) {
@@ -238,6 +239,7 @@ tm_g_scatterplot <- function(label = "Scatterplot",
     ))
   }
 
+  # Normalize the parameters
   if (inherits(x, "data_extract_spec")) x <- list(x)
   if (inherits(y, "data_extract_spec")) y <- list(y)
   if (inherits(color_by, "data_extract_spec")) color_by <- list(color_by)
@@ -246,26 +248,27 @@ tm_g_scatterplot <- function(label = "Scatterplot",
   if (inherits(col_facet, "data_extract_spec")) col_facet <- list(col_facet)
   if (is.double(max_deg)) max_deg <- as.integer(max_deg)
 
-  ggtheme <- match.arg(ggtheme)
+  # Start of assertions
   checkmate::assert_string(label)
   checkmate::assert_list(x, types = "data_extract_spec")
   checkmate::assert_list(y, types = "data_extract_spec")
   checkmate::assert_list(color_by, types = "data_extract_spec", null.ok = TRUE)
   checkmate::assert_list(size_by, types = "data_extract_spec", null.ok = TRUE)
+
   checkmate::assert_list(row_facet, types = "data_extract_spec", null.ok = TRUE)
+  assert_single_selection(row_facet)
+
   checkmate::assert_list(col_facet, types = "data_extract_spec", null.ok = TRUE)
-  checkmate::assert_list(row_facet, types = "data_extract_spec", null.ok = TRUE)
-  if (!all(vapply(row_facet, function(x) !x$select$multiple, logical(1)))) {
-    stop("'row_facet' should not allow multiple selection")
-  }
-  if (!all(vapply(col_facet, function(x) !x$select$multiple, logical(1)))) {
-    stop("'col_facet' should not allow multiple selection")
-  }
-  checkmate::assert_character(shape)
+  assert_single_selection(col_facet)
+
+  checkmate::assert_numeric(plot_height, len = 3, any.missing = FALSE, finite = TRUE)
+  checkmate::assert_numeric(plot_height[1], lower = plot_height[2], upper = plot_height[3], .var.name = "plot_height")
+  checkmate::assert_numeric(plot_width, len = 3, any.missing = FALSE, null.ok = TRUE, finite = TRUE)
+  checkmate::assert_numeric(
+    plot_width[1],
+    lower = plot_width[2], upper = plot_width[3], null.ok = TRUE, .var.name = "plot_width"
+  )
 
-  checkmate::assert_int(max_deg, lower = 1L)
-  checkmate::assert_scalar(table_dec)
-  checkmate::assert_flag(rotate_xaxis_labels)
   if (length(alpha) == 1) {
     checkmate::assert_numeric(alpha, any.missing = FALSE, finite = TRUE)
   } else {
@@ -273,6 +276,8 @@ tm_g_scatterplot <- function(label = "Scatterplot",
     checkmate::assert_numeric(alpha[1], lower = alpha[2], upper = alpha[3], .var.name = "alpha")
   }
 
+  checkmate::assert_character(shape)
+
   if (length(size) == 1) {
     checkmate::assert_numeric(size, any.missing = FALSE, finite = TRUE)
   } else {
@@ -280,16 +285,18 @@ tm_g_scatterplot <- function(label = "Scatterplot",
     checkmate::assert_numeric(size[1], lower = size[2], upper = size[3], .var.name = "size")
   }
 
-  checkmate::assert_numeric(plot_height, len = 3, any.missing = FALSE, finite = TRUE)
-  checkmate::assert_numeric(plot_height[1], lower = plot_height[2], upper = plot_height[3], .var.name = "plot_height")
-  checkmate::assert_numeric(plot_width, len = 3, any.missing = FALSE, null.ok = TRUE, finite = TRUE)
-  checkmate::assert_numeric(
-    plot_width[1],
-    lower = plot_width[2], upper = plot_width[3], null.ok = TRUE, .var.name = "plot_width"
-  )
+  checkmate::assert_int(max_deg, lower = 1L)
+  checkmate::assert_flag(rotate_xaxis_labels)
+  ggtheme <- match.arg(ggtheme)
 
+  checkmate::assert_multi_class(pre_output, c("shiny.tag", "shiny.tag.list", "html"), null.ok = TRUE)
+  checkmate::assert_multi_class(post_output, c("shiny.tag", "shiny.tag.list", "html"), null.ok = TRUE)
+
+  checkmate::assert_scalar(table_dec)
   checkmate::assert_class(ggplot2_args, "ggplot2_args")
+  # End of assertions
 
+  # Make UI args
   args <- as.list(environment())
 
   data_extract_list <- list(
diff --git a/R/tm_g_scatterplotmatrix.R b/R/tm_g_scatterplotmatrix.R
index 68115ddff..a9af072ac 100644
--- a/R/tm_g_scatterplotmatrix.R
+++ b/R/tm_g_scatterplotmatrix.R
@@ -163,13 +163,19 @@ tm_g_scatterplotmatrix <- function(label = "Scatterplot Matrix",
                                    pre_output = NULL,
                                    post_output = NULL) {
   logger::log_info("Initializing tm_g_scatterplotmatrix")
+
+  # Requires Suggested packages
   if (!requireNamespace("lattice", quietly = TRUE)) {
     stop("Cannot load lattice - please install the package or restart your session.")
   }
+
+  # Normalize the parameters
   if (inherits(variables, "data_extract_spec")) variables <- list(variables)
 
+  # Start of assertions
   checkmate::assert_string(label)
   checkmate::assert_list(variables, types = "data_extract_spec")
+
   checkmate::assert_numeric(plot_height, len = 3, any.missing = FALSE, finite = TRUE)
   checkmate::assert_numeric(plot_height[1], lower = plot_height[2], upper = plot_height[3], .var.name = "plot_height")
   checkmate::assert_numeric(plot_width, len = 3, any.missing = FALSE, null.ok = TRUE, finite = TRUE)
@@ -178,7 +184,13 @@ tm_g_scatterplotmatrix <- function(label = "Scatterplot Matrix",
     lower = plot_width[2], upper = plot_width[3], null.ok = TRUE, .var.name = "plot_width"
   )
 
+  checkmate::assert_multi_class(pre_output, c("shiny.tag", "shiny.tag.list", "html"), null.ok = TRUE)
+  checkmate::assert_multi_class(post_output, c("shiny.tag", "shiny.tag.list", "html"), null.ok = TRUE)
+  # End of assertions
+
+  # Make UI args
   args <- as.list(environment())
+
   module(
     label = label,
     server = srv_g_scatterplotmatrix,
diff --git a/R/tm_missing_data.R b/R/tm_missing_data.R
index 9af5189f5..a0c60829e 100644
--- a/R/tm_missing_data.R
+++ b/R/tm_missing_data.R
@@ -89,17 +89,22 @@ tm_missing_data <- function(label = "Missing data",
                             ),
                             pre_output = NULL,
                             post_output = NULL) {
+  logger::log_info("Initializing tm_missing_data")
+
+  # Requires Suggested packages
   if (!requireNamespace("gridExtra", quietly = TRUE)) {
     stop("Cannot load gridExtra - please install the package or restart your session.")
   }
   if (!requireNamespace("rlang", quietly = TRUE)) {
     stop("Cannot load rlang - please install the package or restart your session.")
   }
-  logger::log_info("Initializing tm_missing_data")
+
+  # Normalize the parameters
   if (inherits(ggplot2_args, "ggplot2_args")) ggplot2_args <- list(default = ggplot2_args)
 
+  # Start of assertions
   checkmate::assert_string(label)
-  checkmate::assert_character(parent_dataname, min.len = 0, max.len = 1)
+
   checkmate::assert_numeric(plot_height, len = 3, any.missing = FALSE, finite = TRUE)
   checkmate::assert_numeric(plot_height[1], lower = plot_height[2], upper = plot_height[3], .var.name = "plot_height")
   checkmate::assert_numeric(plot_width, len = 3, any.missing = FALSE, null.ok = TRUE, finite = TRUE)
@@ -107,11 +112,18 @@ tm_missing_data <- function(label = "Missing data",
     plot_width[1],
     lower = plot_width[2], upper = plot_width[3], null.ok = TRUE, .var.name = "plot_width"
   )
+
+  checkmate::assert_character(parent_dataname, min.len = 0, max.len = 1)
   ggtheme <- match.arg(ggtheme)
+
   plot_choices <- c("Summary Obs", "Summary Patients", "Combinations Main", "Combinations Hist", "By Subject")
   checkmate::assert_list(ggplot2_args, types = "ggplot2_args")
   checkmate::assert_subset(names(ggplot2_args), c("default", plot_choices))
 
+  checkmate::assert_multi_class(pre_output, c("shiny.tag", "shiny.tag.list", "html"), null.ok = TRUE)
+  checkmate::assert_multi_class(post_output, c("shiny.tag", "shiny.tag.list", "html"), null.ok = TRUE)
+  # End of assertions
+
   module(
     label,
     server = srv_page_missing_data,
diff --git a/R/tm_outliers.R b/R/tm_outliers.R
index b09b680ed..52031ce98 100644
--- a/R/tm_outliers.R
+++ b/R/tm_outliers.R
@@ -132,13 +132,16 @@ tm_outliers <- function(label = "Outliers Module",
                         pre_output = NULL,
                         post_output = NULL) {
   logger::log_info("Initializing tm_outliers")
+
+  # Normalize the parameters
   if (inherits(outlier_var, "data_extract_spec")) outlier_var <- list(outlier_var)
   if (inherits(categorical_var, "data_extract_spec")) categorical_var <- list(categorical_var)
   if (inherits(ggplot2_args, "ggplot2_args")) ggplot2_args <- list(default = ggplot2_args)
 
-  ggtheme <- match.arg(ggtheme)
+  # Start of assertions
   checkmate::assert_string(label)
   checkmate::assert_list(outlier_var, types = "data_extract_spec")
+
   checkmate::assert_list(categorical_var, types = "data_extract_spec", null.ok = TRUE)
   if (is.list(categorical_var)) {
     lapply(categorical_var, function(x) {
@@ -147,10 +150,26 @@ tm_outliers <- function(label = "Outliers Module",
       }
     })
   }
+
+  ggtheme <- match.arg(ggtheme)
+
   plot_choices <- c("Boxplot", "Density Plot", "Cumulative Distribution Plot")
   checkmate::assert_list(ggplot2_args, types = "ggplot2_args")
   checkmate::assert_subset(names(ggplot2_args), c("default", plot_choices))
 
+  checkmate::assert_numeric(plot_height, len = 3, any.missing = FALSE, finite = TRUE)
+  checkmate::assert_numeric(plot_height[1], lower = plot_height[2], upper = plot_height[3], .var.name = "plot_height")
+  checkmate::assert_numeric(plot_width, len = 3, any.missing = FALSE, null.ok = TRUE, finite = TRUE)
+  checkmate::assert_numeric(
+    plot_width[1],
+    lower = plot_width[2], upper = plot_width[3], null.ok = TRUE, .var.name = "plot_width"
+  )
+
+  checkmate::assert_multi_class(pre_output, c("shiny.tag", "shiny.tag.list", "html"), null.ok = TRUE)
+  checkmate::assert_multi_class(post_output, c("shiny.tag", "shiny.tag.list", "html"), null.ok = TRUE)
+  # End of assertions
+
+  # Make UI args
   args <- as.list(environment())
 
   data_extract_list <- list(
diff --git a/R/tm_t_crosstable.R b/R/tm_t_crosstable.R
index 102c93176..ccd442129 100644
--- a/R/tm_t_crosstable.R
+++ b/R/tm_t_crosstable.R
@@ -139,22 +139,31 @@ tm_t_crosstable <- function(label = "Cross Table",
                             post_output = NULL,
                             basic_table_args = teal.widgets::basic_table_args()) {
   logger::log_info("Initializing tm_t_crosstable")
+
+  # Requires Suggested packages
   if (!requireNamespace("rtables", quietly = TRUE)) {
     stop("Cannot load rtables - please install the package or restart your session.")
   }
+
+  # Normalize the parameters
   if (inherits(x, "data_extract_spec")) x <- list(x)
   if (inherits(y, "data_extract_spec")) y <- list(y)
 
+  # Start of assertions
   checkmate::assert_string(label)
   checkmate::assert_list(x, types = "data_extract_spec")
+
   checkmate::assert_list(y, types = "data_extract_spec")
-  if (any(vapply(y, function(x) x$select$multiple, logical(1)))) {
-    stop("'y' should not allow multiple selection")
-  }
+  assert_single_selection(y)
+
   checkmate::assert_flag(show_percentage)
   checkmate::assert_flag(show_total)
+  checkmate::assert_multi_class(pre_output, c("shiny.tag", "shiny.tag.list", "html"), null.ok = TRUE)
+  checkmate::assert_multi_class(post_output, c("shiny.tag", "shiny.tag.list", "html"), null.ok = TRUE)
   checkmate::assert_class(basic_table_args, classes = "basic_table_args")
+  # End of assertions
 
+  # Make UI args
   ui_args <- as.list(environment())
 
   server_args <- list(
diff --git a/R/tm_variable_browser.R b/R/tm_variable_browser.R
index c90b029c5..6d602bcdb 100644
--- a/R/tm_variable_browser.R
+++ b/R/tm_variable_browser.R
@@ -77,6 +77,8 @@ tm_variable_browser <- function(label = "Variable Browser",
                                 post_output = NULL,
                                 ggplot2_args = teal.widgets::ggplot2_args()) {
   logger::log_info("Initializing tm_variable_browser")
+
+  # Requires Suggested packages
   if (!requireNamespace("sparkline", quietly = TRUE)) {
     stop("Cannot load sparkline - please install the package or restart your session.")
   }
@@ -86,10 +88,16 @@ tm_variable_browser <- function(label = "Variable Browser",
   if (!requireNamespace("jsonlite", quietly = TRUE)) {
     stop("Cannot load jsonlite - please install the package or restart your session.")
   }
+
+  # Start of assertions
   checkmate::assert_string(label)
   checkmate::assert_character(datasets_selected)
   checkmate::assert_character(parent_dataname, min.len = 0, max.len = 1)
+  checkmate::assert_multi_class(pre_output, c("shiny.tag", "shiny.tag.list", "html"), null.ok = TRUE)
+  checkmate::assert_multi_class(post_output, c("shiny.tag", "shiny.tag.list", "html"), null.ok = TRUE)
   checkmate::assert_class(ggplot2_args, "ggplot2_args")
+  # End of assertions
+
   datasets_selected <- unique(datasets_selected)
 
   module(
diff --git a/R/utils.R b/R/utils.R
index 71f822ff4..d4b155cf3 100644
--- a/R/utils.R
+++ b/R/utils.R
@@ -266,3 +266,15 @@ is_tab_active_js <- function(id, name) {
     id, name
   )
 }
+
+#' Assert single selection on `data_extract_spec` object
+#' Helper to reduce code in assertions
+#' @noRd
+#'
+assert_single_selection <- function(x,
+                                    .var.name = checkmate::vname(x)) { # nolint: object_name.
+  if (any(vapply(x, function(.x) .x$select$multiple, logical(1)))) {
+    stop("'", .var.name, "' should not allow multiple selection")
+  }
+  invisible(TRUE)
+}
diff --git a/tests/testthat/helper-functions.R b/tests/testthat/helper-functions.R
new file mode 100644
index 000000000..8ae39cb2a
--- /dev/null
+++ b/tests/testthat/helper-functions.R
@@ -0,0 +1,22 @@
+local_logger_threshold <- function(threshold, envir = parent.frame()) {
+  old <- logger::log_threshold(namespace = "teal.modules.general")
+
+  # Equivalent to withr::defer
+  thunk <- as.call(list(function() logger::log_threshold(old, namespace = "teal.modules.general")))
+  do.call(base::on.exit, list(thunk, TRUE, FALSE), envir = envir)
+  logger::log_threshold(threshold, namespace = "teal.modules.general")
+  invisible(old)
+}
+
+# Create a mock data extact spec for tests
+mock_data_extract_spec <- function(dataname = "MOCK_DATASET",
+                                   select_choices = sample(LETTERS, sample(2:10, 1)),
+                                   select_multiple = FALSE) {
+  teal.transform::data_extract_spec(
+    dataname = dataname,
+    select = teal.transform::select_spec(
+      choices = select_choices,
+      multiple = select_multiple
+    )
+  )
+}
diff --git a/tests/testthat/test-tm_g_bivariate.R b/tests/testthat/test-tm_g_bivariate.R
new file mode 100644
index 000000000..1d97a37fc
--- /dev/null
+++ b/tests/testthat/test-tm_g_bivariate.R
@@ -0,0 +1,287 @@
+testthat::test_that("tm_g_bivariate creates a `teal_module` object", {
+  local_logger_threshold(logger::FATAL) # Suppress logger messages
+
+  testthat::expect_s3_class(
+    tm_g_bivariate(
+      "a label",
+      mock_data_extract_spec(select_multiple = FALSE),
+      mock_data_extract_spec(select_multiple = FALSE),
+      row_facet = mock_data_extract_spec(select_multiple = FALSE),
+      col_facet = mock_data_extract_spec(select_multiple = FALSE),
+      facet = TRUE,
+      color_setting = TRUE,
+      use_density = TRUE,
+      free_x_scales = TRUE,
+      free_y_scales = TRUE,
+      plot_height = c(400, 100, 600),
+      plot_width = c(600, 100, 600),
+      rotate_xaxis_labels = TRUE,
+      swap_axes = TRUE
+    ),
+    "teal_module"
+  )
+})
+
+testthat::test_that("tm_g_bivariate creates a `teal_module` object with default options", {
+  local_logger_threshold(logger::FATAL) # Suppress logger messages
+
+  testthat::expect_s3_class(
+    tm_g_bivariate(
+      "a label",
+      mock_data_extract_spec(select_multiple = FALSE),
+      mock_data_extract_spec(select_multiple = FALSE)
+    ),
+    "teal_module"
+  )
+})
+
+testthat::test_that("tm_g_bivariate creates a `teal_module` object with multiple data extract specs", {
+  local_logger_threshold(logger::FATAL) # Suppress logger messages
+
+  testthat::expect_s3_class(
+    tm_g_bivariate(
+      "a label",
+      list(mock_data_extract_spec(select_multiple = FALSE), mock_data_extract_spec(select_multiple = FALSE)),
+      list(mock_data_extract_spec(select_multiple = FALSE), mock_data_extract_spec(select_multiple = FALSE)),
+      plot_height = c(400, 100, 600),
+      plot_width = c(600, 100, 600)
+    ),
+    "teal_module"
+  )
+})
+
+testthat::test_that("tm_g_bivariate creates a module with datanames taken from data extracts", {
+  local_logger_threshold(logger::FATAL) # Suppress logger messages
+
+  mod <- tm_g_bivariate(
+    "a label",
+    list(
+      mock_data_extract_spec(dataname = "A", select_multiple = FALSE),
+      mock_data_extract_spec(dataname = "B", select_multiple = FALSE)
+    ),
+    mock_data_extract_spec(dataname = "C", select_multiple = FALSE)
+  )
+
+  expect_setequal(
+    mod$datanames,
+    c("A", "B", "C")
+  )
+})
+
+# Test `x` and `y` arguments with invalid data_extract_spec
+
+testthat::test_that("tm_g_bivariate fails when `x` contains a spec with multiple selection", {
+  local_logger_threshold(logger::FATAL) # Suppress logger messages
+
+  testthat::expect_error(
+    tm_g_bivariate(
+      "a label",
+      list(
+        mock_data_extract_spec(select_multiple = TRUE)
+      ),
+      list()
+    ),
+    "'x' should not allow multiple selection"
+  )
+})
+
+testthat::test_that("tm_g_bivariate fails when `x` contains multiple spec with (at least one ) multiple selection", {
+  local_logger_threshold(logger::FATAL) # Suppress logger messages
+
+  testthat::expect_error(
+    tm_g_bivariate(
+      "a label",
+      list(
+        mock_data_extract_spec(select_multiple = FALSE),
+        mock_data_extract_spec(select_multiple = TRUE)
+      ),
+      list(mock_data_extract_spec(select_multiple = FALSE))
+    ),
+    "'x' should not allow multiple selection"
+  )
+})
+
+testthat::test_that("tm_g_bivariate fails when `x` contains multiple spec with (at least one ) multiple selection", {
+  local_logger_threshold(logger::FATAL) # Suppress logger messages
+
+  testthat::expect_error(
+    tm_g_bivariate(
+      "a label",
+      mock_data_extract_spec(select_multiple = FALSE),
+      list(
+        mock_data_extract_spec(select_multiple = FALSE),
+        mock_data_extract_spec(select_multiple = TRUE)
+      )
+    ),
+    "'y' should not allow multiple selection"
+  )
+})
+
+testthat::test_that("tm_g_bivariate fails when `y` contains multiple spec with (at least one ) multiple selection", {
+  local_logger_threshold(logger::FATAL) # Suppress logger messages
+
+  testthat::expect_error(
+    tm_g_bivariate(
+      "a label",
+      mock_data_extract_spec(select_multiple = FALSE),
+      list(
+        mock_data_extract_spec(select_multiple = FALSE),
+        mock_data_extract_spec(select_multiple = TRUE)
+      )
+    ),
+    "'y' should not allow multiple selection"
+  )
+})
+
+# Test `plot_height` and `plot_width` arguments
+
+testthat::test_that("tm_g_bivariate fails when `plot_height` is not valid", {
+  local_logger_threshold(logger::FATAL) # Suppress logger messages
+
+  testthat::expect_error(
+    tm_g_bivariate(
+      "a label",
+      mock_data_extract_spec(select_multiple = FALSE),
+      mock_data_extract_spec(select_multiple = FALSE),
+      plot_height = c(100, 10, 20)
+    ),
+    "Assertion on 'plot_height' failed: Element 1 is not <= 20"
+  )
+})
+
+testthat::test_that("tm_g_bivariate fails when `plot_height` is not valid", {
+  local_logger_threshold(logger::FATAL) # Suppress logger messages
+
+  testthat::expect_error(
+    tm_g_bivariate(
+      "a label",
+      mock_data_extract_spec(select_multiple = FALSE),
+      mock_data_extract_spec(select_multiple = FALSE),
+      plot_height = c(1, 10, 20)
+    ),
+    "Assertion on 'plot_height' failed: Element 1 is not >= 10"
+  )
+})
+
+testthat::test_that("tm_g_bivariate fails when `plot_height` is not valid", {
+  local_logger_threshold(logger::FATAL) # Suppress logger messages
+
+  testthat::expect_error(
+    tm_g_bivariate(
+      "a label",
+      mock_data_extract_spec(select_multiple = FALSE),
+      mock_data_extract_spec(select_multiple = FALSE),
+      plot_height = 100
+    ),
+    "Assertion on 'plot_height' failed: Must have length 3, but has length 1"
+  )
+})
+
+testthat::test_that("tm_g_bivariate fails when `plot_width` is not valid", {
+  local_logger_threshold(logger::FATAL) # Suppress logger messages
+
+  testthat::expect_error(
+    tm_g_bivariate(
+      "a label",
+      mock_data_extract_spec(select_multiple = FALSE),
+      mock_data_extract_spec(select_multiple = FALSE),
+      plot_width = c(100, 10, 20)
+    ),
+    "Assertion on 'plot_width' failed: Element 1 is not <= 20"
+  )
+})
+
+testthat::test_that("tm_g_bivariate fails when `plot_width` is not valid", {
+  local_logger_threshold(logger::FATAL) # Suppress logger messages
+
+  testthat::expect_error(
+    tm_g_bivariate(
+      "a label",
+      mock_data_extract_spec(select_multiple = FALSE),
+      mock_data_extract_spec(select_multiple = FALSE),
+      plot_width = c(1, 10, 20)
+    ),
+    "Assertion on 'plot_width' failed: Element 1 is not >= 10"
+  )
+})
+
+testthat::test_that("tm_g_bivariate fails when `plot_width` is not valid", {
+  local_logger_threshold(logger::FATAL) # Suppress logger messages
+
+  testthat::expect_error(
+    tm_g_bivariate(
+      "a label",
+      mock_data_extract_spec(select_multiple = FALSE),
+      mock_data_extract_spec(select_multiple = FALSE),
+      plot_width = 100
+    ),
+    "Assertion on 'plot_width' failed: Must have length 3, but has length 1"
+  )
+})
+
+# Test `color_settings` argument
+
+testthat::test_that("tm_g_bivariate fails when `color_setting` is FALSE and `color` is supplied", {
+  local_logger_threshold(logger::FATAL) # Suppress logger messages
+
+  testthat::expect_error(
+    tm_g_bivariate(
+      "a label",
+      mock_data_extract_spec(select_multiple = FALSE),
+      mock_data_extract_spec(select_multiple = FALSE),
+      color_setting = FALSE,
+      color = mock_data_extract_spec()
+    ),
+    "'color_settings' argument needs to be set to TRUE if 'color', 'fill', and/or 'size' is/are supplied."
+  )
+})
+
+testthat::test_that("tm_g_bivariate fails when `color_setting` is FALSE and `size` is supplied", {
+  local_logger_threshold(logger::FATAL) # Suppress logger messages
+
+  testthat::expect_error(
+    tm_g_bivariate(
+      "a label",
+      mock_data_extract_spec(select_multiple = FALSE),
+      mock_data_extract_spec(select_multiple = FALSE),
+      color_setting = FALSE,
+      size = mock_data_extract_spec()
+    ),
+    "'color_settings' argument needs to be set to TRUE if 'color', 'fill', and/or 'size' is/are supplied."
+  )
+})
+
+testthat::test_that("tm_g_bivariate fails when `color_setting` is FALSE and `fill` is supplied", {
+  local_logger_threshold(logger::FATAL) # Suppress logger messages
+
+  testthat::expect_error(
+    tm_g_bivariate(
+      "a label",
+      mock_data_extract_spec(select_multiple = FALSE),
+      mock_data_extract_spec(select_multiple = FALSE),
+      color_setting = FALSE,
+      fill = mock_data_extract_spec()
+    ),
+    "'color_settings' argument needs to be set to TRUE if 'color', 'fill', and/or 'size' is/are supplied."
+  )
+})
+
+testthat::test_that("tm_g_bivariate determines `color`, `size` and `fill` when `color_setting` is TRUE", {
+  local_logger_threshold(logger::FATAL) # Suppress logger messages
+
+  mod <- tm_g_bivariate(
+    "a label",
+    mock_data_extract_spec(select_multiple = FALSE),
+    mock_data_extract_spec(select_multiple = FALSE),
+    color_setting = TRUE
+  )
+
+  testthat::expect_contains(
+    vapply(
+      unlist(mod$ui_args[c("color", "size", "fill")], recursive = FALSE),
+      class,
+      character(1)
+    ),
+    "data_extract_spec"
+  )
+})

From e209bf3f4b20b8ade0e1cde2cf98c019b4bf9933 Mon Sep 17 00:00:00 2001
From: m7pr <marcin.kosinski.mk1@roche.com>
Date: Fri, 1 Mar 2024 10:53:04 +0100
Subject: [PATCH 56/62] remove `latest-tag` from REPO url. this should onl stay
 in WEBSITE url

---
 .github/ISSUE_TEMPLATE/bug.yml      | 2 +-
 .github/ISSUE_TEMPLATE/feature.yml  | 2 +-
 .github/ISSUE_TEMPLATE/question.yml | 2 +-
 .github/workflows/check.yaml        | 2 +-
 .github/workflows/release.yaml      | 2 +-
 5 files changed, 5 insertions(+), 5 deletions(-)

diff --git a/.github/ISSUE_TEMPLATE/bug.yml b/.github/ISSUE_TEMPLATE/bug.yml
index ac82deccd..406469fc4 100644
--- a/.github/ISSUE_TEMPLATE/bug.yml
+++ b/.github/ISSUE_TEMPLATE/bug.yml
@@ -49,7 +49,7 @@ body:
     id: security-policy
     attributes:
       label: Security Policy
-      description: By submitting this issue, you agree to follow our [Security Policy.](https://github.com/insightsengineering/teal.modules.general/latest-tag/security/policy)
+      description: By submitting this issue, you agree to follow our [Security Policy.](https://github.com/insightsengineering/teal.modules.general/security/policy)
       options:
         - label: I agree to follow this project's Security Policy.
           required: true
diff --git a/.github/ISSUE_TEMPLATE/feature.yml b/.github/ISSUE_TEMPLATE/feature.yml
index f47d69400..c2731f8d6 100644
--- a/.github/ISSUE_TEMPLATE/feature.yml
+++ b/.github/ISSUE_TEMPLATE/feature.yml
@@ -29,7 +29,7 @@ body:
     id: security-policy
     attributes:
       label: Security Policy
-      description: By submitting this issue, you agree to follow our [Security Policy.](https://github.com/insightsengineering/teal.modules.general/latest-tag/security/policy)
+      description: By submitting this issue, you agree to follow our [Security Policy.](https://github.com/insightsengineering/teal.modules.general/security/policy)
       options:
         - label: I agree to follow this project's Security Policy.
           required: true
diff --git a/.github/ISSUE_TEMPLATE/question.yml b/.github/ISSUE_TEMPLATE/question.yml
index a70c47bb8..f6ad4b62b 100644
--- a/.github/ISSUE_TEMPLATE/question.yml
+++ b/.github/ISSUE_TEMPLATE/question.yml
@@ -29,7 +29,7 @@ body:
     id: security-policy
     attributes:
       label: Security Policy
-      description: By submitting this issue, you agree to follow our [Security Policy.](https://github.com/insightsengineering/teal.modules.general/latest-tag/security/policy)
+      description: By submitting this issue, you agree to follow our [Security Policy.](https://github.com/insightsengineering/teal.modules.general/security/policy)
       options:
         - label: I agree to follow this project's Security Policy.
           required: true
diff --git a/.github/workflows/check.yaml b/.github/workflows/check.yaml
index bc9b9786f..0e6ced7b2 100644
--- a/.github/workflows/check.yaml
+++ b/.github/workflows/check.yaml
@@ -40,7 +40,7 @@ jobs:
         checking for unstated dependencies in vignettes .* NOTE
         checking top-level files .* NOTE
       unit-test-report-brand: >-
-        https://raw.githubusercontent.com/insightsengineering/hex-stickers/latest-tag/thumbs/teal.png
+        https://raw.githubusercontent.com/insightsengineering/hex-stickers/thumbs/teal.png
   coverage:
     name: Coverage 📔
     uses: insightsengineering/r.pkg.template/.github/workflows/test-coverage.yaml@main
diff --git a/.github/workflows/release.yaml b/.github/workflows/release.yaml
index 557076b4f..ec4080080 100644
--- a/.github/workflows/release.yaml
+++ b/.github/workflows/release.yaml
@@ -54,7 +54,7 @@ jobs:
         checking Rd line widths .* NOTE
         checking top-level files .* NOTE
       unit-test-report-brand: >-
-        https://raw.githubusercontent.com/insightsengineering/hex-stickers/latest-tag/thumbs/teal.png
+        https://raw.githubusercontent.com/insightsengineering/latest-tag/thumbs/teal.png
   coverage:
     name: Coverage 📔
     needs: [release, docs]

From 92a25a581c665f91bf1827dfdc46db4bc3f456e0 Mon Sep 17 00:00:00 2001
From: Marcin <133694481+m7pr@users.noreply.github.com>
Date: Fri, 1 Mar 2024 10:54:53 +0100
Subject: [PATCH 57/62] Update .pre-commit-config.yaml

Co-authored-by: kartikeya kirar <kirar.kartikeya1@gmail.com>
Signed-off-by: Marcin <133694481+m7pr@users.noreply.github.com>
---
 .pre-commit-config.yaml | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index 60f063c05..7c6a34ca8 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -18,8 +18,8 @@ repos:
           - ggmosaic
           - ggplot2
           - shiny
-          - insightsengineering/teal
-          - insightsengineering/teal.transform
+          - teal
+          - teal.transform
           - checkmate
           - dplyr
           - DT

From 2aa7e857f4e7b53de96df3f3c905f4e48df389c3 Mon Sep 17 00:00:00 2001
From: Marcin <133694481+m7pr@users.noreply.github.com>
Date: Fri, 1 Mar 2024 11:04:09 +0100
Subject: [PATCH 58/62] Update .github/workflows/check.yaml
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

Co-authored-by: André Veríssimo <211358+averissimo@users.noreply.github.com>
Signed-off-by: Marcin <133694481+m7pr@users.noreply.github.com>
---
 .github/workflows/check.yaml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/check.yaml b/.github/workflows/check.yaml
index 0e6ced7b2..57b2feee5 100644
--- a/.github/workflows/check.yaml
+++ b/.github/workflows/check.yaml
@@ -40,7 +40,7 @@ jobs:
         checking for unstated dependencies in vignettes .* NOTE
         checking top-level files .* NOTE
       unit-test-report-brand: >-
-        https://raw.githubusercontent.com/insightsengineering/hex-stickers/thumbs/teal.png
+        https://raw.githubusercontent.com/insightsengineering/hex-stickers/main/thumbs/teal.png
   coverage:
     name: Coverage 📔
     uses: insightsengineering/r.pkg.template/.github/workflows/test-coverage.yaml@main

From 8f95a49ee0bb9f2bab34ecfa676ec3ebdc0bd2bc Mon Sep 17 00:00:00 2001
From: Marcin <133694481+m7pr@users.noreply.github.com>
Date: Fri, 1 Mar 2024 11:05:34 +0100
Subject: [PATCH 59/62] Update .github/workflows/release.yaml

Signed-off-by: Marcin <133694481+m7pr@users.noreply.github.com>
---
 .github/workflows/release.yaml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/release.yaml b/.github/workflows/release.yaml
index ec4080080..0fa4a06c8 100644
--- a/.github/workflows/release.yaml
+++ b/.github/workflows/release.yaml
@@ -54,7 +54,7 @@ jobs:
         checking Rd line widths .* NOTE
         checking top-level files .* NOTE
       unit-test-report-brand: >-
-        https://raw.githubusercontent.com/insightsengineering/latest-tag/thumbs/teal.png
+        https://raw.githubusercontent.com/insightsengineering/hex-stickers/main/thumbs/teal.png
   coverage:
     name: Coverage 📔
     needs: [release, docs]

From f3981401f742e0afcba4063b4837d6cddf9d46a9 Mon Sep 17 00:00:00 2001
From: Marcin <133694481+m7pr@users.noreply.github.com>
Date: Fri, 1 Mar 2024 11:11:53 +0100
Subject: [PATCH 60/62] Update DESCRIPTION

Signed-off-by: Marcin <133694481+m7pr@users.noreply.github.com>
---
 DESCRIPTION | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/DESCRIPTION b/DESCRIPTION
index f2fb0242a..d345d5641 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -38,7 +38,7 @@ Imports:
     logger (>= 0.2.0),
     scales,
     shinyjs,
-    shinyTree,
+    shinyTree (>= 0.2.8),
     shinyvalidate,
     shinyWidgets (>= 0.5.1),
     stats,

From 4dea7f3ae8a19c4f27d6d1f2c73d76fcc1ea0867 Mon Sep 17 00:00:00 2001
From: Marcin <133694481+m7pr@users.noreply.github.com>
Date: Fri, 1 Mar 2024 11:16:03 +0100
Subject: [PATCH 61/62] Update vignettes/teal-modules-general.Rmd

Signed-off-by: Marcin <133694481+m7pr@users.noreply.github.com>
---
 vignettes/teal-modules-general.Rmd | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/vignettes/teal-modules-general.Rmd b/vignettes/teal-modules-general.Rmd
index 594475b0c..3d8c9a007 100644
--- a/vignettes/teal-modules-general.Rmd
+++ b/vignettes/teal-modules-general.Rmd
@@ -20,7 +20,7 @@ other `shiny` modules to build a large `teal` / `shiny` app.
 
 The concepts presented here require knowledge about the core features of `teal`, specifically on how to launch a `teal`
 application and how to pass data into it. Therefore, it is highly recommended to refer to the [`README`](https://insightsengineering.github.io/teal/index.html) file and 
-the introductory [vignette](https://insightsengineering.github.io/teal/latest-tag/articles/teal.html) of the `teal` package.
+the introductory [vignette](https://insightsengineering.github.io/teal/latest-tag/articles/getting-started-with-teal.html) of the `teal` package.
 
 See also `teal.modules.clinical`'s [`README`](https://insightsengineering.github.io/teal.modules.clinical/latest-tag/index.html).
 

From 92bdf31a0c2f69a5a813f4a4a7dfdd645c9ac5a6 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Andr=C3=A9=20Ver=C3=ADssimo?=
 <211358+averissimo@users.noreply.github.com>
Date: Fri, 1 Mar 2024 12:04:57 +0100
Subject: [PATCH 62/62] Removes unnecessary `# nolint ` after
 `object_name_linter` was changed (#703)

# Pull Request

<!--- Replace `#nnn` with your issue link for reference. -->

- Part of #624
- Extends ANL rule to allow `ANL_OUTLIERS` and others variables that are
prefixed with `ANL_` (in all caps)
---
 .lintr                     |  2 +-
 R/tm_a_pca.R               |  8 +++---
 R/tm_a_regression.R        |  4 +--
 R/tm_g_association.R       |  2 +-
 R/tm_g_bivariate.R         |  2 +-
 R/tm_g_distribution.R      | 10 +++----
 R/tm_g_response.R          |  6 ++--
 R/tm_g_scatterplot.R       | 12 ++++----
 R/tm_g_scatterplotmatrix.R |  8 +++---
 R/tm_missing_data.R        |  8 +++---
 R/tm_outliers.R            | 56 +++++++++++++++++++-------------------
 R/tm_t_crosstable.R        |  4 +--
 data-raw/data.R            | 10 +++----
 13 files changed, 66 insertions(+), 66 deletions(-)

diff --git a/.lintr b/.lintr
index fff479777..b2279e658 100644
--- a/.lintr
+++ b/.lintr
@@ -2,5 +2,5 @@ linters: linters_with_defaults(
   line_length_linter = line_length_linter(120),
   cyclocomp_linter = NULL,
   object_usage_linter = NULL,
-  object_name_linter = object_name_linter(styles = c("snake_case", "symbols"), regexes = c(ANL = "^ANL_?[0-9]*$", ADaM = "^r?AD[A-Z]{2,3}_?[0-9]*$"))
+  object_name_linter = object_name_linter(styles = c("snake_case", "symbols"), regexes = c(ANL = "^ANL_?[0-9A-Z_]*$", ADaM = "^r?AD[A-Z]{2,3}_?[0-9]*$"))
   )
diff --git a/R/tm_a_pca.R b/R/tm_a_pca.R
index f2073ee2c..e629b7b25 100644
--- a/R/tm_a_pca.R
+++ b/R/tm_a_pca.R
@@ -391,7 +391,7 @@ srv_a_pca <- function(id, data, reporter, filter_panel_api, dat, plot_height, pl
       standardization <- input$standardization
       center <- standardization %in% c("center", "center_scale")
       scale <- standardization == "center_scale"
-      ANL <- merged$anl_q_r()[["ANL"]] # nolint: object_name.
+      ANL <- merged$anl_q_r()[["ANL"]]
 
       teal::validate_has_data(ANL, 10)
       validate(need(
@@ -422,7 +422,7 @@ srv_a_pca <- function(id, data, reporter, filter_panel_api, dat, plot_height, pl
       standardization <- input$standardization
       center <- standardization %in% c("center", "center_scale")
       scale <- standardization == "center_scale"
-      ANL <- merged$anl_q_r()[["ANL"]] # nolint: object_name.
+      ANL <- merged$anl_q_r()[["ANL"]]
 
       qenv <- teal.code::eval_code(
         merged$anl_q_r(),
@@ -435,7 +435,7 @@ srv_a_pca <- function(id, data, reporter, filter_panel_api, dat, plot_height, pl
       if (na_action == "drop") {
         qenv <- teal.code::eval_code(
           qenv,
-          quote(ANL <- tidyr::drop_na(ANL, keep_columns)) # nolint: object_name.
+          quote(ANL <- tidyr::drop_na(ANL, keep_columns))
         )
       }
 
@@ -657,7 +657,7 @@ srv_a_pca <- function(id, data, reporter, filter_panel_api, dat, plot_height, pl
     plot_biplot <- function(base_q) {
       qenv <- base_q
 
-      ANL <- qenv[["ANL"]] # nolint: object_name.
+      ANL <- qenv[["ANL"]]
 
       resp_col <- as.character(merged$anl_input_r()$columns_source$response)
       dat_cols <- as.character(merged$anl_input_r()$columns_source$dat)
diff --git a/R/tm_a_regression.R b/R/tm_a_regression.R
index dc06b8ef0..f2e1f8220 100644
--- a/R/tm_a_regression.R
+++ b/R/tm_a_regression.R
@@ -436,7 +436,7 @@ srv_a_regression <- function(id,
 
     # sets qenv object and populates it with data merge call and fit expression
     fit_r <- reactive({
-      ANL <- anl_merged_q()[["ANL"]] # nolint: object_name.
+      ANL <- anl_merged_q()[["ANL"]]
       teal::validate_has_data(ANL, 10)
 
       validate(need(is.numeric(ANL[regression_var()$response][[1]]), "Response variable should be numeric."))
@@ -546,7 +546,7 @@ srv_a_regression <- function(id,
 
       plot_type_0 <- function() {
         fit <- fit_r()[["fit"]]
-        ANL <- anl_merged_q()[["ANL"]] # nolint: object_name.
+        ANL <- anl_merged_q()[["ANL"]]
 
         stopifnot(ncol(fit$model) == 2)
 
diff --git a/R/tm_g_association.R b/R/tm_g_association.R
index eb47b00d7..f0cfc6479 100644
--- a/R/tm_g_association.R
+++ b/R/tm_g_association.R
@@ -326,7 +326,7 @@ srv_tm_g_association <- function(id,
     output_q <- reactive({
       teal::validate_inputs(iv_r())
 
-      ANL <- merged$anl_q_r()[["ANL"]] # nolint: object_name.
+      ANL <- merged$anl_q_r()[["ANL"]]
       teal::validate_has_data(ANL, 3)
 
       vars_names <- merged$anl_input_r()$columns_source$vars
diff --git a/R/tm_g_bivariate.R b/R/tm_g_bivariate.R
index 122d2e1b2..e9a7b111b 100644
--- a/R/tm_g_bivariate.R
+++ b/R/tm_g_bivariate.R
@@ -535,7 +535,7 @@ srv_g_bivariate <- function(id,
     output_q <- reactive({
       teal::validate_inputs(iv_r())
 
-      ANL <- merged$anl_q_r()[["ANL"]] # nolint: object_name.
+      ANL <- merged$anl_q_r()[["ANL"]]
       teal::validate_has_data(ANL, 3)
 
       x_col_vec <- as.vector(merged$anl_input_r()$columns_source$x)
diff --git a/R/tm_g_distribution.R b/R/tm_g_distribution.R
index 66d524784..0044eafdd 100644
--- a/R/tm_g_distribution.R
+++ b/R/tm_g_distribution.R
@@ -518,7 +518,7 @@ srv_distribution <- function(id,
             )
           }
 
-          ANL <- merged$anl_q_r()[[as.character(dist_var[[1]]$dataname)]] # nolint: object_name.
+          ANL <- merged$anl_q_r()[[as.character(dist_var[[1]]$dataname)]]
           params <- get_dist_params(as.numeric(stats::na.omit(ANL[[dist_var2]])), input$t_dist)
           params_vec <- round(unname(unlist(params)), 2)
           params_names <- names(params)
@@ -558,7 +558,7 @@ srv_distribution <- function(id,
     common_q <- reactive({
       # Create a private stack for this function only.
 
-      ANL <- merged$anl_q_r()[["ANL"]] # nolint: object_name.
+      ANL <- merged$anl_q_r()[["ANL"]]
       dist_var <- merge_vars()$dist_var
       s_var <- merge_vars()$s_var
       g_var <- merge_vars()$g_var
@@ -585,7 +585,7 @@ srv_distribution <- function(id,
         qenv <- teal.code::eval_code(
           qenv,
           substitute(
-            expr = ANL[[g_var]] <- forcats::fct_na_value_to_level(as.factor(ANL[[g_var]]), "NA"), # nolint: object_name.
+            expr = ANL[[g_var]] <- forcats::fct_na_value_to_level(as.factor(ANL[[g_var]]), "NA"),
             env = list(g_var = g_var)
           )
         )
@@ -601,7 +601,7 @@ srv_distribution <- function(id,
         qenv <- teal.code::eval_code(
           qenv,
           substitute(
-            expr = ANL[[s_var]] <- forcats::fct_na_value_to_level(as.factor(ANL[[s_var]]), "NA"), # nolint: object_name.
+            expr = ANL[[s_var]] <- forcats::fct_na_value_to_level(as.factor(ANL[[s_var]]), "NA"),
             env = list(s_var = s_var)
           )
         )
@@ -1024,7 +1024,7 @@ srv_distribution <- function(id,
       },
       valueExpr = {
         # Create a private stack for this function only.
-        ANL <- common_q()[["ANL"]] # nolint: object_name.
+        ANL <- common_q()[["ANL"]]
 
         dist_var <- merge_vars()$dist_var
         s_var <- merge_vars()$s_var
diff --git a/R/tm_g_response.R b/R/tm_g_response.R
index 12beb4f94..f8dd3010b 100644
--- a/R/tm_g_response.R
+++ b/R/tm_g_response.R
@@ -372,7 +372,7 @@ srv_g_response <- function(id,
       teal::validate_inputs(iv_r())
 
       qenv <- merged$anl_q_r()
-      ANL <- qenv[["ANL"]] # nolint: object_name.
+      ANL <- qenv[["ANL"]]
       resp_var <- as.vector(merged$anl_input_r()$columns_source$response)
       x <- as.vector(merged$anl_input_r()$columns_source$x)
 
@@ -409,7 +409,7 @@ srv_g_response <- function(id,
         qenv <- teal.code::eval_code(
           qenv,
           substitute(
-            expr = ANL[[x]] <- with(ANL, forcats::fct_rev(x_cl)), # nolint: object_name.
+            expr = ANL[[x]] <- with(ANL, forcats::fct_rev(x_cl)),
             env = list(x = x, x_cl = x_cl)
           )
         )
@@ -418,7 +418,7 @@ srv_g_response <- function(id,
       qenv <- teal.code::eval_code(
         qenv,
         substitute(
-          expr = ANL[[resp_var]] <- factor(ANL[[resp_var]]), # nolint: object_name.
+          expr = ANL[[resp_var]] <- factor(ANL[[resp_var]]),
           env = list(resp_var = resp_var)
         )
       ) %>%
diff --git a/R/tm_g_scatterplot.R b/R/tm_g_scatterplot.R
index d90f6c43a..50bf2f05b 100644
--- a/R/tm_g_scatterplot.R
+++ b/R/tm_g_scatterplot.R
@@ -568,7 +568,7 @@ srv_g_scatterplot <- function(id,
     )
 
     trend_line_is_applicable <- reactive({
-      ANL <- merged$anl_q_r()[["ANL"]] # nolint: object_name.
+      ANL <- merged$anl_q_r()[["ANL"]]
       x_var <- as.vector(merged$anl_input_r()$columns_source$x)
       y_var <- as.vector(merged$anl_input_r()$columns_source$y)
       length(x_var) > 0 && length(y_var) > 0 && is.numeric(ANL[[x_var]]) && is.numeric(ANL[[y_var]])
@@ -595,7 +595,7 @@ srv_g_scatterplot <- function(id,
 
     output$num_na_removed <- renderUI({
       if (add_trend_line()) {
-        ANL <- merged$anl_q_r()[["ANL"]] # nolint: object_name.
+        ANL <- merged$anl_q_r()[["ANL"]]
         x_var <- as.vector(merged$anl_input_r()$columns_source$x)
         y_var <- as.vector(merged$anl_input_r()$columns_source$y)
         if ((num_total_na <- nrow(ANL) - nrow(stats::na.omit(ANL[, c(x_var, y_var)]))) > 0) {
@@ -621,7 +621,7 @@ srv_g_scatterplot <- function(id,
     output_q <- reactive({
       teal::validate_inputs(iv_r(), iv_facet)
 
-      ANL <- merged$anl_q_r()[["ANL"]] # nolint: object_name.
+      ANL <- merged$anl_q_r()[["ANL"]]
 
       x_var <- as.vector(merged$anl_input_r()$columns_source$x)
       y_var <- as.vector(merged$anl_input_r()$columns_source$y)
@@ -724,7 +724,7 @@ srv_g_scatterplot <- function(id,
         plot_q <- teal.code::eval_code(
           object = plot_q,
           code = substitute(
-            expr = ANL[, log_x_var] <- log_x_fn(ANL[, x_var]), # nolint: object_name.
+            expr = ANL[, log_x_var] <- log_x_fn(ANL[, x_var]),
             env = list(
               x_var = x_var,
               log_x_fn = as.name(log_x_fn),
@@ -739,7 +739,7 @@ srv_g_scatterplot <- function(id,
         plot_q <- teal.code::eval_code(
           object = plot_q,
           code = substitute(
-            expr = ANL[, log_y_var] <- log_y_fn(ANL[, y_var]), # nolint: object_name.
+            expr = ANL[, log_y_var] <- log_y_fn(ANL[, y_var]),
             env = list(
               y_var = y_var,
               log_y_fn = as.name(log_y_fn),
@@ -872,7 +872,7 @@ srv_g_scatterplot <- function(id,
             plot_q <- teal.code::eval_code(
               plot_q,
               substitute(
-                expr = ANL <- dplyr::filter(ANL, !is.na(x_var) & !is.na(y_var)), # nolint: object_name.
+                expr = ANL <- dplyr::filter(ANL, !is.na(x_var) & !is.na(y_var)),
                 env = list(x_var = as.name(x_var), y_var = as.name(y_var))
               )
             )
diff --git a/R/tm_g_scatterplotmatrix.R b/R/tm_g_scatterplotmatrix.R
index a9af072ac..180b7a7bf 100644
--- a/R/tm_g_scatterplotmatrix.R
+++ b/R/tm_g_scatterplotmatrix.R
@@ -299,7 +299,7 @@ srv_g_scatterplotmatrix <- function(id, data, reporter, filter_panel_api, variab
       teal::validate_inputs(iv_r())
 
       qenv <- merged$anl_q_r()
-      ANL <- qenv[["ANL"]] # nolint: object_name.
+      ANL <- qenv[["ANL"]]
 
       cols_names <- merged$anl_input_r()$columns_source$variables
       alpha <- input$alpha
@@ -326,7 +326,7 @@ srv_g_scatterplotmatrix <- function(id, data, reporter, filter_panel_api, variab
         qenv <- teal.code::eval_code(
           qenv,
           substitute(
-            expr = ANL <- ANL[, cols_names] %>% # nolint: object_name.
+            expr = ANL <- ANL[, cols_names] %>%
               dplyr::mutate_if(is.character, as.factor) %>%
               droplevels(),
             env = list(cols_names = cols_names)
@@ -336,7 +336,7 @@ srv_g_scatterplotmatrix <- function(id, data, reporter, filter_panel_api, variab
         qenv <- teal.code::eval_code(
           qenv,
           substitute(
-            expr = ANL <- ANL[, cols_names] %>% # nolint: object_name.
+            expr = ANL <- ANL[, cols_names] %>%
               droplevels(),
             env = list(cols_names = cols_names)
           )
@@ -421,7 +421,7 @@ srv_g_scatterplotmatrix <- function(id, data, reporter, filter_panel_api, variab
     output$message <- renderText({
       shiny::req(iv_r()$is_valid())
       req(selector_list()$variables())
-      ANL <- merged$anl_q_r()[["ANL"]] # nolint: object_name.
+      ANL <- merged$anl_q_r()[["ANL"]]
       cols_names <- unique(unname(do.call(c, merged$anl_input_r()$columns_source)))
       check_char <- vapply(ANL[, cols_names], is.character, logical(1))
       if (any(check_char)) {
diff --git a/R/tm_missing_data.R b/R/tm_missing_data.R
index a0c60829e..9e5e95229 100644
--- a/R/tm_missing_data.R
+++ b/R/tm_missing_data.R
@@ -478,14 +478,14 @@ srv_missing_data <- function(id, data, reporter, filter_panel_api, dataname, par
         teal.code::eval_code(
           data(),
           substitute(
-            expr = ANL <- anl_name[, selected_vars, drop = FALSE], # nolint: object_name.
+            expr = ANL <- anl_name[, selected_vars, drop = FALSE],
             env = list(anl_name = as.name(dataname), selected_vars = selected_vars())
           )
         )
       } else {
         teal.code::eval_code(
           data(),
-          substitute(expr = ANL <- anl_name, env = list(anl_name = as.name(dataname))) # nolint: object_name.
+          substitute(expr = ANL <- anl_name, env = list(anl_name = as.name(dataname)))
         )
       }
 
@@ -493,7 +493,7 @@ srv_missing_data <- function(id, data, reporter, filter_panel_api, dataname, par
         qenv <- teal.code::eval_code(
           qenv,
           substitute(
-            expr = ANL[[group_var]] <- anl_name[[group_var]], # nolint: object_name.
+            expr = ANL[[group_var]] <- anl_name[[group_var]],
             env = list(group_var = group_var, anl_name = as.name(dataname))
           )
         )
@@ -645,7 +645,7 @@ srv_missing_data <- function(id, data, reporter, filter_panel_api, dataname, par
         qenv <- teal.code::eval_code(
           qenv,
           substitute(
-            expr = ANL[[new_col_name]] <- ifelse(rowSums(is.na(ANL)) > 0, NA, FALSE), # nolint: object_name.
+            expr = ANL[[new_col_name]] <- ifelse(rowSums(is.na(ANL)) > 0, NA, FALSE),
             env = list(new_col_name = new_col_name)
           )
         )
diff --git a/R/tm_outliers.R b/R/tm_outliers.R
index 52031ce98..e484a4f4c 100644
--- a/R/tm_outliers.R
+++ b/R/tm_outliers.R
@@ -389,7 +389,7 @@ srv_outliers <- function(id, data, reporter, filter_panel_api, outlier_var,
     n_outlier_missing <- reactive({
       shiny::req(iv_r()$is_valid())
       outlier_var <- as.vector(merged$anl_input_r()$columns_source$outlier_var)
-      ANL <- merged$anl_q_r()[["ANL"]] # nolint: object_name.
+      ANL <- merged$anl_q_r()[["ANL"]]
       sum(is.na(ANL[[outlier_var]]))
     })
 
@@ -399,7 +399,7 @@ srv_outliers <- function(id, data, reporter, filter_panel_api, outlier_var,
     common_code_q <- reactive({
       shiny::req(iv_r()$is_valid())
 
-      ANL <- merged$anl_q_r()[["ANL"]] # nolint: object_name.
+      ANL <- merged$anl_q_r()[["ANL"]]
       qenv <- merged$anl_q_r()
 
       outlier_var <- as.vector(merged$anl_input_r()$columns_source$outlier_var)
@@ -428,7 +428,7 @@ srv_outliers <- function(id, data, reporter, filter_panel_api, outlier_var,
           qenv <- teal.code::eval_code(
             qenv,
             substitute(
-              expr = ANL <- ANL %>% dplyr::filter(!is.na(outlier_var_name)), # nolint: object_name.
+              expr = ANL <- ANL %>% dplyr::filter(!is.na(outlier_var_name)),
               env = list(outlier_var_name = as.name(outlier_var))
             )
           )
@@ -445,7 +445,7 @@ srv_outliers <- function(id, data, reporter, filter_panel_api, outlier_var,
           qenv <- teal.code::eval_code(
             qenv,
             substitute(
-              expr = ANL <- ANL %>% dplyr::filter(!is.na(outlier_var_name)), # nolint: object_name.
+              expr = ANL <- ANL %>% dplyr::filter(!is.na(outlier_var_name)),
               env = list(outlier_var_name = as.name(outlier_var))
             )
           )
@@ -477,7 +477,7 @@ srv_outliers <- function(id, data, reporter, filter_panel_api, outlier_var,
         qenv,
         substitute(
           expr = {
-            ANL_OUTLIER <- ANL %>% # nolint: object_name.
+            ANL_OUTLIER <- ANL %>%
               group_expr %>% # styler: off
               dplyr::mutate(is_outlier = {
                 q1_q3 <- stats::quantile(outlier_var_name, probs = c(0.25, 0.75))
@@ -545,7 +545,7 @@ srv_outliers <- function(id, data, reporter, filter_panel_api, outlier_var,
         qenv,
         substitute(
           expr = {
-            ANL_OUTLIER_EXTENDED <- dplyr::left_join( # nolint: object_name.
+            ANL_OUTLIER_EXTENDED <- dplyr::left_join(
               ANL_OUTLIER,
               dplyr::select(
                 dataname,
@@ -624,13 +624,13 @@ srv_outliers <- function(id, data, reporter, filter_panel_api, outlier_var,
               # In order for geom_rug to work properly when reordering takes place inside facet_grid,
               # all tables must have the column used for reording.
               # In this case, the column used for reordering is `order`.
-              ANL_OUTLIER <- dplyr::left_join( # nolint: object_name.
+              ANL_OUTLIER <- dplyr::left_join(
                 ANL_OUTLIER,
                 summary_table_pre[, c("order", categorical_var)],
                 by = categorical_var
               )
               # so that x axis of plot aligns with columns of summary table, from most outliers to least by percentage
-              ANL <- ANL %>% # nolint: object_name.
+              ANL <- ANL %>%
                 dplyr::left_join(
                   dplyr::select(summary_table_pre, categorical_var_name, order),
                   by = categorical_var
@@ -685,8 +685,8 @@ srv_outliers <- function(id, data, reporter, filter_panel_api, outlier_var,
     # boxplot/violinplot # nolint commented_code
     boxplot_q <- reactive({
       req(common_code_q())
-      ANL <- common_code_q()[["ANL"]] # nolint: object_name.
-      ANL_OUTLIER <- common_code_q()[["ANL_OUTLIER"]] # nolint: object_name.
+      ANL <- common_code_q()[["ANL"]]
+      ANL_OUTLIER <- common_code_q()[["ANL_OUTLIER"]]
 
       outlier_var <- as.vector(merged$anl_input_r()$columns_source$outlier_var)
       categorical_var <- as.vector(merged$anl_input_r()$columns_source$categorical_var)
@@ -777,8 +777,8 @@ srv_outliers <- function(id, data, reporter, filter_panel_api, outlier_var,
 
     # density plot
     density_plot_q <- reactive({
-      ANL <- common_code_q()[["ANL"]] # nolint: object_name.
-      ANL_OUTLIER <- common_code_q()[["ANL_OUTLIER"]] # nolint: object_name.
+      ANL <- common_code_q()[["ANL"]]
+      ANL_OUTLIER <- common_code_q()[["ANL_OUTLIER"]]
 
       outlier_var <- as.vector(merged$anl_input_r()$columns_source$outlier_var)
       categorical_var <- as.vector(merged$anl_input_r()$columns_source$categorical_var)
@@ -837,8 +837,8 @@ srv_outliers <- function(id, data, reporter, filter_panel_api, outlier_var,
 
     # Cumulative distribution plot
     cumulative_plot_q <- reactive({
-      ANL <- common_code_q()[["ANL"]] # nolint: object_name.
-      ANL_OUTLIER <- common_code_q()[["ANL_OUTLIER"]] # nolint: object_name.
+      ANL <- common_code_q()[["ANL"]]
+      ANL_OUTLIER <- common_code_q()[["ANL_OUTLIER"]]
 
       qenv <- common_code_q()
 
@@ -882,7 +882,7 @@ srv_outliers <- function(id, data, reporter, filter_panel_api, outlier_var,
               all_categories <- lapply(
                 unique(ANL[[categorical_var]]),
                 function(x) {
-                  ANL <- ANL %>% dplyr::filter(get(categorical_var) == x) # nolint: object_name.
+                  ANL <- ANL %>% dplyr::filter(get(categorical_var) == x)
                   anl_outlier2 <- ANL_OUTLIER %>% dplyr::filter(get(categorical_var) == x)
                   ecdf_df <- ANL %>%
                     dplyr::mutate(y = stats::ecdf(ANL[[outlier_var]])(ANL[[outlier_var]]))
@@ -1059,7 +1059,7 @@ srv_outliers <- function(id, data, reporter, filter_panel_api, outlier_var,
     choices <- teal.transform::variable_choices(data()[[dataname_first]])
 
     observeEvent(common_code_q(), {
-      ANL_OUTLIER <- common_code_q()[["ANL_OUTLIER"]] # nolint: object_name.
+      ANL_OUTLIER <- common_code_q()[["ANL_OUTLIER"]]
       teal.widgets::updateOptionalSelectInput(
         session,
         inputId = "table_ui_columns",
@@ -1076,9 +1076,9 @@ srv_outliers <- function(id, data, reporter, filter_panel_api, outlier_var,
         outlier_var <- as.vector(merged$anl_input_r()$columns_source$outlier_var)
         categorical_var <- as.vector(merged$anl_input_r()$columns_source$categorical_var)
 
-        ANL_OUTLIER <- common_code_q()[["ANL_OUTLIER"]] # nolint: object_name.
-        ANL_OUTLIER_EXTENDED <- common_code_q()[["ANL_OUTLIER_EXTENDED"]] # nolint: object_name.
-        ANL <- common_code_q()[["ANL"]] # nolint: object_name.
+        ANL_OUTLIER <- common_code_q()[["ANL_OUTLIER"]]
+        ANL_OUTLIER_EXTENDED <- common_code_q()[["ANL_OUTLIER_EXTENDED"]]
+        ANL <- common_code_q()[["ANL"]]
 
         plot_brush <- if (tab == "Boxplot") {
           boxplot_r()
@@ -1092,7 +1092,7 @@ srv_outliers <- function(id, data, reporter, filter_panel_api, outlier_var,
         }
 
         # removing unused column ASAP
-        ANL_OUTLIER$order <- ANL$order <- NULL # nolint: object_name.
+        ANL_OUTLIER$order <- ANL$order <- NULL
 
         display_table <- if (!is.null(plot_brush)) {
           if (length(categorical_var) > 0) {
@@ -1108,7 +1108,7 @@ srv_outliers <- function(id, data, reporter, filter_panel_api, outlier_var,
             if (tab == "Boxplot") {
               # in boxplot with no categorical variable, there is no column in ANL that would correspond to x-axis
               # so a column needs to be inserted with the value "Entire dataset" because that's the label used in plot
-              ANL[[plot_brush$mapping$x]] <- "Entire dataset" # nolint: object_name.
+              ANL[[plot_brush$mapping$x]] <- "Entire dataset"
             }
           }
 
@@ -1116,16 +1116,16 @@ srv_outliers <- function(id, data, reporter, filter_panel_api, outlier_var,
           # so they need to be computed and attached to ANL
           if (tab == "Density Plot") {
             plot_brush$mapping$y <- "density"
-            ANL$density <- plot_brush$ymin # nolint: object_name.
+            ANL$density <- plot_brush$ymin
             # either ymin or ymax will work
           } else if (tab == "Cumulative Distribution Plot") {
             plot_brush$mapping$y <- "cdf"
             if (length(categorical_var) > 0) {
-              ANL <- ANL %>% # nolint: object_name.
+              ANL <- ANL %>%
                 dplyr::group_by(!!as.name(plot_brush$mapping$panelvar1)) %>%
                 dplyr::mutate(cdf = stats::ecdf(!!as.name(outlier_var))(!!as.name(outlier_var)))
             } else {
-              ANL$cdf <- stats::ecdf(ANL[[outlier_var]])(ANL[[outlier_var]]) # nolint: object_name.
+              ANL$cdf <- stats::ecdf(ANL[[outlier_var]])(ANL[[outlier_var]])
             }
           }
 
@@ -1170,10 +1170,10 @@ srv_outliers <- function(id, data, reporter, filter_panel_api, outlier_var,
 
     output$total_outliers <- renderUI({
       shiny::req(iv_r()$is_valid())
-      ANL <- merged$anl_q_r()[["ANL"]] # nolint: object_name.
-      ANL_OUTLIER <- common_code_q()[["ANL_OUTLIER"]] # nolint: object_name.
+      ANL <- merged$anl_q_r()[["ANL"]]
+      ANL_OUTLIER <- common_code_q()[["ANL_OUTLIER"]]
       teal::validate_has_data(ANL, 1)
-      ANL_OUTLIER_SELECTED <- ANL_OUTLIER[ANL_OUTLIER$is_outlier_selected, ] # nolint: object_name.
+      ANL_OUTLIER_SELECTED <- ANL_OUTLIER[ANL_OUTLIER$is_outlier_selected, ]
       h5(
         sprintf(
           "%s %d / %d [%.02f%%]",
@@ -1187,7 +1187,7 @@ srv_outliers <- function(id, data, reporter, filter_panel_api, outlier_var,
 
     output$total_missing <- renderUI({
       if (n_outlier_missing() > 0) {
-        ANL <- merged$anl_q_r()[["ANL"]] # nolint: object_name.
+        ANL <- merged$anl_q_r()[["ANL"]]
         helpText(
           sprintf(
             "%s %d / %d [%.02f%%]",
diff --git a/R/tm_t_crosstable.R b/R/tm_t_crosstable.R
index ccd442129..6859e6487 100644
--- a/R/tm_t_crosstable.R
+++ b/R/tm_t_crosstable.R
@@ -302,7 +302,7 @@ srv_t_crosstable <- function(id, data, reporter, filter_panel_api, label, x, y,
 
     output_q <- reactive({
       teal::validate_inputs(iv_r())
-      ANL <- merged$anl_q_r()[["ANL"]] # nolint: object_name.
+      ANL <- merged$anl_q_r()[["ANL"]]
 
       # As this is a summary
       x_name <- as.vector(merged$anl_input_r()$columns_source$x)
@@ -386,7 +386,7 @@ srv_t_crosstable <- function(id, data, reporter, filter_panel_api, label, x, y,
         teal.code::eval_code(
           substitute(
             expr = {
-              ANL <- tern::df_explicit_na(ANL) # nolint: object_name.
+              ANL <- tern::df_explicit_na(ANL)
               tbl <- rtables::build_table(lyt = lyt, df = ANL[order(ANL[[y_name]]), ])
               tbl
             },
diff --git a/data-raw/data.R b/data-raw/data.R
index 10d16120e..37c73cef8 100644
--- a/data-raw/data.R
+++ b/data-raw/data.R
@@ -1,16 +1,16 @@
 ## code to prepare `data` for testing examples
 library(scda)
-rADAE <- synthetic_cdisc_data("latest")$adae # nolint: object_name.
+rADAE <- synthetic_cdisc_data("latest")$adae
 usethis::use_data(rADAE)
 
-rADLB <- synthetic_cdisc_data("latest")$adlb # nolint: object_name.
+rADLB <- synthetic_cdisc_data("latest")$adlb
 usethis::use_data(rADLB)
 
-rADRS <- synthetic_cdisc_data("latest")$adrs # nolint: object_name.
+rADRS <- synthetic_cdisc_data("latest")$adrs
 usethis::use_data(rADRS)
 
-rADSL <- synthetic_cdisc_data("latest")$adsl # nolint: object_name.
+rADSL <- synthetic_cdisc_data("latest")$adsl
 usethis::use_data(rADSL)
 
-rADTTE <- synthetic_cdisc_data("latest")$adtte # nolint: object_name.
+rADTTE <- synthetic_cdisc_data("latest")$adtte
 usethis::use_data(rADTTE)