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# (PART) References (Yellow) {-}
# General Resources {#general}
This is a long list of helpful general resources related to EDAV. If you have come across a good resource you don't see here, consider adding it with a pull request (see the [contribute page](contribute.html) for more info).
## Books
A lot of these are available for students through [Columbia Libraries](http://library.columbia.edu/){target="_blank"}, in both physical and e-book formats.
- [Graphical Data Analysis with R](http://rosuda.org/GDA){target="_blank"}: This book systematically goes through the different types of data, including categorical variables, continuous variables, and time series. The author shows different examples of plotting techniques using ggplot and promoting the "grammar of graphics" model. Code snippets included and available at the [book's website](http://rosuda.org/GDA){target="_blank"}.
- [R for Data Science](http://r4ds.had.co.nz/){target="_blank"}: The classic. Everything from data types, programming, modeling, communicating, and those keyboard shortcuts you keep forgetting. To quote the book, "this book will teach you how to do data science with R." Nuff said.
## Cheatsheets
- [Cheatsheet of cheatsheets](https://paulvanderlaken.com/author/lakenp/){target="_blank"}: Paul van der Laken has put together a large collection of R resource links, including cheat sheets, style guides, package info, blogs, and other helpful resources.
- [RStudio Cheatsheet Collection](https://www.rstudio.com/resources/cheatsheets/){target="_blank"}: Collection of downloadable cheatsheets from RStudio. Includes ones on R Markdown, Data Transformation (`dplyr`), and Data Visualization (`ggplot2`). They also have a R Markdown Reference Guide, which is great for remembering that one chunk option that's on the tip of your tongue.
- [R Base Graphics Cheatsheet](https://github.com/jtr13/codehelp/blob/master/R/BaseGraphicsCheatsheet.pdf){target="_blank"}: Oddly enough, despite the length of time it's been around, it's hard to find a base graphics cheatsheet. Joyce put this one together to help you out if you're using base graphics.
## Articles
- [Ten Simple Rules for Better Figures](https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1003833){target="_blank"}: A helpful article discussing how to make the best figures possible by following ten basic rules such as "Avoid 'chartjunk'" and "Know Your Audience". Good to keep these rules in mind.
## Meetups
- [New York Open Statistical Programming Meetup](https://www.meetup.com/nyhackr/){target="_blank"}: Meetups hosted by [Jared Lander](https://www.jaredlander.com/about/){target="_blank"} and [Wes McKinney](http://wesmckinney.com/){target="_blank"} on a variety of topics in statistical programming, but with a focus on the R language. Past speakers have included [J.J. Allaire](https://en.wikipedia.org/wiki/Joseph_J._Allaire){target="_blank"} (founder of RStudio) and [Hadley Wickham](http://hadley.nz/){target="_blank"} (core tidyverse developer). Other attendees are generally eager to welcome newcomers and all of their talks are available on the [Lander Analytics Youtube channel](https://www.youtube.com/channel/UC2-hKemnrmVCH_29duyJ26A){target="_blank"}.