R is a versatile programming language, best suited for a variety of data science needs. Whether you need to run some statistical analyses, create publication-worthy data visualizations, or even publish a website, R has a multitude of tools to help you get what you need done. This workshop is intended to get interested users up to speed with the R language and the RStudio interactive developing environment. By the end, you'll be able to install and load packages, read in data, do basic data wrangling and visualization, and navigate the RStudio environment.
In this workshop, participants will:
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Learn the basics of R and RStudio
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Learn useful techniques for wrangling data
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Begin creating publication-quality data visualizations
2 hours.
- None, other than a stable internet connection
None
There are too many to count. However, a great place to find inspiration is to follow the #tidytuesday hashtag on Twitter!
Unfortunately, there is no code of ethics for programming. However, given that the goal for most R users is data analysis and communication, there are some fast and loose rules. My favorite list comes from Blast analytics. Although they come from a business perspective, these guidelines can be applied to most analysis scenarios.
R for Data Science by Hadley Wickham and Garrett Grolemound
Workshop leader: Connor French, Graduate Center Digital Fellow
[Creative Commons Attribution-ShareAlike 4.0 International License](http://creativecommons.org/licenses/by-sa/4.0/)