"R for Data Science" teaches how to do data science with R. Chapters cover how to import, tidy, transform, visualize, model, and communicate data. The general philosophy is to teach the most useful skills first, using an abundance of examples and exercises. Solutions to the exercises can be found in a community-contributed book by Jeffrey Arnold: https://jrnold.github.io/r4ds-exercise-solutions/. License: CC BY-NC-ND 3.0 US
About this resource
| Keywords | data science, R |
|---|---|
| Added by | Sébastien on 31 Jan, 2021 |
| Popularity | Used in 4 learning circles |
| Format | Online Course |
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| Creator | Hadley Wickham and Garrett Grolemund |
| Website | https://r4ds.had.co.nz/ |
| Language | English |
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Reviews
The texbook used for the learning circle is constructed in a logical way and provides clear explanations with an abundance of coding examples that can be discussed during the learning circle. Some topics, however, may be too detailed for a beginner audience.
The order in which topics are presented keep participants interested and wanting to learn more. Each new concept is illustrated by well-designed coding examples and exercises, which help to make the learning circle hands-on and interactive.