README.Rmd

---
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%"
)
```

# yawp

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A collection of documented, tested, and packaged helper functions.

## Installation

```{r, eval = FALSE}
devtools::install_github("vpnagraj/yawp", branch = "main", build_vignettes = TRUE)
```

Note that the install command above will install the package from GitHub *and* build vignettes. If you would prefer not to build vignettes upon install then set `build_vignettes = FALSE`, which is the default in `devtools::install_github()`.

## Features

- `betwixt()`: Find values between lower and upper bounds of a range
- `bound()`: Bound a vector
- `f1()`: Calculate F1 score
- `first_char()`: Extract the first character from a string
- `get_mode()`: Find the mode
- `gg_zoom()`: Zoom in on a ggplot2 plot (*EXPERIMENTAL*)
- `mav()`: Calculate moving average
- `medf()`: Format median
- `more()`: Add filler rows to a data frame
- `propf()`: Calculate and format proportion
- `read_repo()`: Read files directly from a GitHub repository (*EXPERIMENTAL*)
- `summary_se()`: Calculate mean and standard error
- `theme_mathbook()`: Custom "math book" ggplot2 theme

## Usage

The function documentation includes examples of usage, as do the package vignettes:

```{r,eval = FALSE}
browseVignettes(package = "yawp")
```

## Inspiration and Related Work

`yawp` is a utility package, and the functionality it provides is by no means unique. In fact, some of the functions were directly inspired by other tools. For example:

- `betwixt()` builds on the concept originally implemented in the `between()` function in [dplyr](https://CRAN.R-project.org/package=dplyr) but adds a feature to ignore specific values
- `summary_se()` re-implements `summarySE()` from ["The Cookbook for R"](http://www.cookbook-r.com/Manipulating_data/Summarizing_data/) with tidy eval syntax
- The moving average functionality in `mav()` is available elsewhere, including for example in `slide()` from [slider](https://CRAN.R-project.org/package=slider)
- While `f1()` calculates the F1 score, other available functions such as `f_meas()` from [yardstick](https://CRAN.R-project.org/package=yardstick) may accommodate more generic applications (i.e. applying weights to precision and recall)