tidyverse / ggplot2

# ggplot2 
## Overview
ggplot2 is a system for declaratively creating graphics, based on The
Grammar of
Graphics. 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
 [code] 
## 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()`).
 [code] 
## Lifecycle
ggplot2 is now 18 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 and
 Communication chapters in R
 for Data Science. R for Data Science is
 designed to give you a comprehensive introduction to the
 tidyverse, 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
 by Kara Woo.
3. If you’d like to follow a webinar, try Plotting Anything with
 ggplot2 by Thomas Lin Pedersen.
4. If you want to dive into making common graphics as quickly as
 possible, I recommend The R Graphics
 Cookbook 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. 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.
## Getting help
There are two main places to get help with ggplot2:
1. The Posit Community (formerly RStudio
 Community) is a friendly place to ask any questions about ggplot2.
2. Stack
 Overflow
 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.