diff --git a/README.md b/README.md index 3683108c63..a73892afa0 100644 --- a/README.md +++ b/README.md @@ -1,121 +1,4 @@ -# ggplot2 ggplot2 website - - - -[![R-CMD-check](https://github.com/tidyverse/ggplot2/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/tidyverse/ggplot2/actions/workflows/R-CMD-check.yaml) -[![CRAN_Status_Badge](https://www.r-pkg.org/badges/version/ggplot2)](https://cran.r-project.org/package=ggplot2) -[![Codecov test -coverage](https://codecov.io/gh/tidyverse/ggplot2/graph/badge.svg)](https://app.codecov.io/gh/tidyverse/ggplot2) - - -## Overview - -ggplot2 is a system for declaratively creating graphics, based on [The -Grammar of -Graphics](https://www.amazon.com/Grammar-Graphics-Statistics-Computing/dp/0387245448/ref=as_li_ss_tl). -You provide the data, tell ggplot2 how to map variables to aesthetics, -what graphical primitives to use, and it takes care of the details. - -## Installation - -``` r -# The easiest way to get ggplot2 is to install the whole tidyverse: -install.packages("tidyverse") - -# Alternatively, install just ggplot2: -install.packages("ggplot2") - -# Or the development version from GitHub: -# install.packages("pak") -pak::pak("tidyverse/ggplot2") -``` - -## Cheatsheet - -ggplot2 cheatsheet - -## Usage - -It’s hard to succinctly describe how ggplot2 works because it embodies a -deep philosophy of visualisation. However, in most cases you start with -`ggplot()`, supply a dataset and aesthetic mapping (with `aes()`). You -then add on layers (like `geom_point()` or `geom_histogram()`), scales -(like `scale_colour_brewer()`), faceting specifications (like -`facet_wrap()`) and coordinate systems (like `coord_flip()`). - -``` r -library(ggplot2) - -ggplot(mpg, aes(displ, hwy, colour = class)) + - geom_point() -``` - -Scatterplot of engine displacement versus highway miles per gallon, for 234 cars coloured by 7 'types' of car. The displacement and miles per gallon are inversely correlated. - -## Lifecycle - -[![lifecycle](https://img.shields.io/badge/lifecycle-stable-brightgreen.svg)](https://lifecycle.r-lib.org/articles/stages.html) - -ggplot2 is now over 10 years old and is used by hundreds of thousands of -people to make millions of plots. That means, by-and-large, ggplot2 -itself changes relatively little. When we do make changes, they will be -generally to add new functions or arguments rather than changing the -behaviour of existing functions, and if we do make changes to existing -behaviour we will do them for compelling reasons. - -If you are looking for innovation, look to ggplot2’s rich ecosystem of -extensions. See a community maintained list at -. - -## Learning ggplot2 - -If you are new to ggplot2 you are better off starting with a systematic -introduction, rather than trying to learn from reading individual -documentation pages. Currently, there are several good places to start: - -1. The [Data Visualization](https://r4ds.hadley.nz/data-visualize) and - [Communication](https://r4ds.hadley.nz/communication) chapters in [R - for Data Science](https://r4ds.hadley.nz). R for Data Science is - designed to give you a comprehensive introduction to the - [tidyverse](https://www.tidyverse.org), and these two chapters will - get you up to speed with the essentials of ggplot2 as quickly as - possible. - -2. If you’d like to take an online course, try [Data Visualization in R - With - ggplot2](https://learning.oreilly.com/videos/data-visualization-in/9781491963661/) - by Kara Woo. - -3. If you’d like to follow a webinar, try [Plotting Anything with - ggplot2](https://youtu.be/h29g21z0a68) by Thomas Lin Pedersen. - -4. If you want to dive into making common graphics as quickly as - possible, I recommend [The R Graphics - Cookbook](https://r-graphics.org) by Winston Chang. It provides a - set of recipes to solve common graphics problems. - -5. If you’ve mastered the basics and want to learn more, read [ggplot2: - Elegant Graphics for Data Analysis](https://ggplot2-book.org). It - describes the theoretical underpinnings of ggplot2 and shows you how - all the pieces fit together. This book helps you understand the - theory that underpins ggplot2, and will help you create new types of - graphics specifically tailored to your needs. - -6. For articles about announcements and deep-dives you can visit the - [tidyverse blog](https://www.tidyverse.org/tags/ggplot2/). - -## Getting help - -There are two main places to get help with ggplot2: - -1. The [RStudio community](https://forum.posit.co/) is a friendly place - to ask any questions about ggplot2. - -2. [Stack - Overflow](https://stackoverflow.com/questions/tagged/ggplot2?sort=frequent&pageSize=50) - is a great source of answers to common ggplot2 questions. It is also - a great place to get help, once you have created a reproducible - example that illustrates your problem. +# TDs dataviz ENSAI