https://github.com/jmestret/DOYPAColors

R package DOYPAColors - Don't Overthink Your Palette of Colors
https://github.com/jmestret/DOYPAColors

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R package DOYPAColors - Don't Overthink Your Palette of Colors

• Host: GitHub
• URL: https://github.com/jmestret/DOYPAColors
• Owner: jmestret
• License: other
• Created: 2022-05-17T17:18:09.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2024-04-30T06:49:10.000Z (7 months ago)
• Last Synced: 2024-05-12T08:41:49.584Z (6 months ago)
• Language: R
• Homepage:
• Size: 666 KB
• Stars: 3
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • Changelog: NEWS.md
  • License: LICENSE

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README

        


# DOYPAColors 

[![CRAN_Status_Badge](https://www.r-pkg.org/badges/version/DOYPAColors?color=blue)](https://cran.r-project.org/package=DOYPAColors)

[![R-CMD-check](https://github.com/jmestret/DOYPAColors/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/jmestret/DOYPAColors/actions/workflows/R-CMD-check.yaml)

[![codecov](https://codecov.io/gh/jmestret/DOYPAColors/graph/badge.svg?token=IU6UAU5F3K)](https://codecov.io/gh/jmestret/DOYPAColors)

## Overview

Tired of agonizing over color choices for your data visualizations? Let

**DOYPAColors** do the heavy lifting for you! Our R package provides a

delightful array of color palettes, each meticulously crafted to enhance

your plots. With **DOYPAColors**, you can even let us surprise you with

a palette choice, so you can focus on what matters most—telling your

data’s unique story. Say goodbye to color selection headaches and hello

to vibrant, eye-catching visuals! 🎨

## Installation

To install **DOYPAColors** from CRAN, use:

``` r

install.packages("DOYPAColors")

```

For the development version from GitHub, use:

``` r

if (!require("devtools")) {

  install.packages("devtools")

}

devtools::install_github("jmestret/DOYPAColors")

```

## How to use

Using **DOYPAColors** is straightforward. Access and utilize our

palettes in your R plots with a single line of code:

``` r

library(DOYPAColors)

color_palette <- doypa()

```

You can then apply these palettes to your `ggplot2` plots using the

functions `scale_fill_doypa()` and `scale_color_doypa()`:

``` r

library(ggplot2)

# Create a bar plot with a DOYPAColors palette

ggplot(iris, aes(x = Species, y = Sepal.Length, fill = Species)) +

    geom_boxplot() +

    scale_fill_doypa(discrete = TRUE) +

    theme_classic()

```

You can explore how specific palettes fit different types of data using

the `preview_pal()` function:

``` r

preview_pal("doypa")

```







### Available palettes

Here’s a visualization of all available palettes in **DOYPAColors**:







For more advanced usage and options, check out our

[web](https://jmestret.github.io/DOYPAColors/) to get the most out of

**DOYPAColors** palettes!

## Contributing

We welcome contributions from the community! If you have a new color

palette you’d like to share, we’d be thrilled to consider it for

inclusion in **DOYPAColors**. To submit your palette:

1.  Provide a name for your palette.

2.  Specify the type of palette (sequential, diverging, or qualitative).

3.  List the HEX color codes for your palette.

You can submit your palette details by opening an issue or a pull

request on our [GitHub

repository](https://github.com/jmestret/DOYPAColors). We will review

your submission and, if it meets our criteria, we’ll be glad to include

it in the package!

## How to cite

If you use **DOYPAColors**, please reference the R package as follows:

Jorge Mestre (2023). DOYPAColors: Don’t Overthink Your Palette of

Colors. R package version 0.0.2,