README.Rmd

---
title: "README for package `sbwtools`"
author: "Author: S. Bryan West<br>"
output: 
  github_document
---

<!-- README.md is generated from README.Rmd. Please edit that file -->

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)
```

# sbwtools

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**sbwtools** is a package containing my most frequently used custom functions I have either written myself or borrowed from other, more skilled programmers.

### News

Updated `ci_df` and `ci_boot_df` functions to use `dplyr::reframe()` instead of `dplyr::summarize()`, 
as of `dplyr` [version 1.1.0](https://www.tidyverse.org/blog/2023/02/dplyr-1-1-0-pick-reframe-arrange/#reframe)

## System Information

Updated on `r Sys.time()`

```{r}
sessioninfo::platform_info()
```

## Installation

sbwtools is only available from [GitHub](https://github.com/). Install with:

```{r install info, eval = FALSE}
# install.packages("devtools")
devtools::install_github("sbw78/sbwtools")
```

## Credits

Credit to [Kevin Ushey](github.com/kevinushey/etc) for the functions [hh](#hh and ht),
[ht](#hh and ht), [last](#last), [se](#se). He created these functions for his 
.Rprofile dotfile, which you can find at his github repo.

Credit to [Jacob Long](https://jacob-long.com) for the `theme_apa` used in 
[`make_forest_plot`](#make_forest_plot).

## Function examples 

### `ci_df`

Build a dataframe with the mean and confidence intervals of a continuous 
variable, with optional grouping.

```{r ci_df}
library(sbwtools)
library(dplyr)
ci_data <- iris %>% 
  as_tibble() %>% 
  ci_df(., Petal.Length, Species)
```

****

### `ci_boot_df`

Same as `ci_df`, but with bootstrapped sampling

```{r ci_boot_df}
ci_boot_data <- iris %>% 
  as_tibble() %>% 
  ci_boot_df(., Petal.Length, Species)
```



****

### `custom_kable`

Customized `knitr::kable` output.

```{r custom_kable, eval = FALSE}
custom_kable(ci_data, caption = "Summarized data from iris",
             col.names = c("Species", "n", "Petal Length", "Lower CI", "Upper CI", "sd"))

custom_kable(ci_data, caption = "Summarized data from iris",
             col.names = c("Species", "n", "Petal Length", "Lower CI", "Upper CI", "sd")) %>% 
  kableExtra::footnote(general = "1000 bootstrapped samples")
```



****

### `format_pval`

Format p-values (i.e. "< .001" for values less than .001).

```{r format_pval}
fit <- lm(Sepal.Length ~ Species, data = iris)
summary_df <- broom::tidy(fit)

# Without formatting p-value
summary_df

# Formatted p-value
mutate(summary_df, p.value = format_pval(p.value))
```



****

### `hh` and `ht`

`hh`: Get first 5 rows and first 5 columns of a data frame or matrix

`ht`: Get the first 10 rows and last 10 rows of a data frame or matrix.

Credit: [Kevin Ushey](github.com/kevinushey/etc)

```{r hh ht}
hh(iris)

ht(iris)
```



****


****

### `last`

Get the last element of a vector or list.

Credit: [Kevin Ushey](github.com/kevinushey/etc)

```{r}
last(letters)
```


****

### `make_forest_plot`

Build a forest plot.

Credit: [Jacob Long](https://jacob-long.com), author of the 
[jtools package](https://jtools.jacob-long.com "jtools") 
([github](https://github.com/jacob-long/jtools "GitHub")) from which this function 
borrows the `ggplot2` theme `theme_apa()`.

```{r make_forest_plot}
p <- make_forest_plot(ci_data, mean_Petal.Length, Species, xlab = "Mean petal length",
                 ylab = "Species", ci_low, ci_high)

p
```


****

### `regex_build`

Combine a character vector into a single regex list.

```{r regex_build}
regex_build(c("apples", "oranges", "bananas"))
regex_build(c("apples", "passion fruit", "oranges"), modifier = "multi")
```


****

### `se`

Calculate standard error.

Credit: [Kevin Ushey](github.com/kevinushey/etc)

```{r se}
se(iris$Sepal.Length)
```