From cb84ef02910b90110420e61023ae70b5d9490e6c Mon Sep 17 00:00:00 2001 From: Kyle Husmann Date: Thu, 29 Feb 2024 20:22:13 -0800 Subject: [PATCH] changed language, remove term 'valid' --- README.Rmd | 6 +++--- README.md | 18 +++++++++--------- 2 files changed, 12 insertions(+), 12 deletions(-) diff --git a/README.Rmd b/README.Rmd index 212d021..6e01e63 100644 --- a/README.Rmd +++ b/README.Rmd @@ -19,7 +19,7 @@ library(dplyr) When a value is missing in your data, sometimes you want to know *why* it is missing. Many textual tabular data sources will encode missing reasons as -special values *interlaced* with the valid values in a column (e.g. `N/A`, +special values *interlaced* with the regular values in a column (e.g. `N/A`, `REFUSED`, `-99`, etc.). Unfortunately, the missing reasons are lost when these values are all converted into a single `NA` type. Working with missing reasons has traditionally required loading all variables as @@ -83,7 +83,7 @@ As you can see, each source variable is loaded into two columns: one for vaild values, and the other for missing reasons. Missing reason columns are denoted by column names surrounded by dots (e.g. `.age.` is the missing reason for the `age` column). When a value is `NA`, it always has a reason in the missing -reason column. Similarly, when a missing reason is `NA`, it always has a valid +reason column. Similarly, when a missing reason is `NA`, it always has a value in the value column. This allows us to separately reference values and missing reasons @@ -101,7 +101,7 @@ ex |> ``` (Note that the `` category in the result refers to the mean age of responses -*without* missing color values, i.e. with valid favorite color responses). +*without* missing color values, i.e. with available favorite color responses). But this just scratches the surface of what can be done with interlacer... check out `vignette("interlacer")` for a more complete overview! diff --git a/README.md b/README.md index b3e2805..6b49994 100644 --- a/README.md +++ b/README.md @@ -7,12 +7,12 @@ When a value is missing in your data, sometimes you want to know *why* it is missing. Many textual tabular data sources will encode missing -reasons as special values *interlaced* with the valid values in a column -(e.g. `N/A`, `REFUSED`, `-99`, etc.). Unfortunately, the missing reasons -are lost when these values are all converted into a single `NA` type. -Working with missing reasons has traditionally required loading all -variables as character vectors and doing a bunch of string operations -and type conversions to make sense of them. +reasons as special values *interlaced* with the regular values in a +column (e.g. `N/A`, `REFUSED`, `-99`, etc.). Unfortunately, the missing +reasons are lost when these values are all converted into a single `NA` +type. Working with missing reasons has traditionally required loading +all variables as character vectors and doing a bunch of string +operations and type conversions to make sense of them. Interlacer was created based on the insight that values and missing reasons can be handled as separate *channels* of the same variable. @@ -88,7 +88,7 @@ vaild values, and the other for missing reasons. Missing reason columns are denoted by column names surrounded by dots (e.g. `.age.` is the missing reason for the `age` column). When a value is `NA`, it always has a reason in the missing reason column. Similarly, when a missing -reason is `NA`, it always has a valid value in the value column. +reason is `NA`, it always has a value in the value column. This allows us to separately reference values and missing reasons in a tidy and type-aware manner. For example, if I wanted to get a breakdown @@ -112,8 +112,8 @@ ex |> ``` (Note that the `` category in the result refers to the mean age of -responses *without* missing color values, i.e. with valid favorite color -responses). +responses *without* missing color values, i.e. with available favorite +color responses). But this just scratches the surface of what can be done with interlacer… check out `vignette("interlacer")` for a more complete overview!