Wickham, H. & Grolemund, G. R for Data Science. (O'Reilly Media, 2017).
This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible.
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Obtain a free copy of the book by visiting https://r4ds.had.co.nz/.
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If you don't already have them, install R and RStudio following these instructions.
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Sign up for a GitHub account (also free) and clone this repository. Don't know what that means? Follow this tutorial. The process in RStudio is documented here or there is a video here.
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Participate in bi-monthly meetings, the details of which are below.
Where: Zoom link
| Date | Chapter | Presenter |
|---|---|---|
| 2021-01-07 | Introduction | Daniela |
| 2021-01-21 | Workflows: Basics, scripts, projects | Liz |
| 2021-02-04 | Data Visualization | Marcel |
| 2021-02-18 | Data Visualization | Marcel |
| 2021-03-04 | Data Transformation | Igor |
| 2021-03-18 | Data Transformation | Igor |
| 2021-04-01 | Exploratory Data Analysis | Izabela |
| 2021-04-15 | Tibbles | Lais M. |
| 2021-04-29 | Data import | Franciele |
| 2021-05-13 | Tidy data | Loren |
| 2021-05-27 | Strings | Gladis |
| 2021-06-10 | Factors | Liz |
| 2021-06-24 | Dates and times | Igor |
| 2021-07-08 | Pipes | Marcel |
| 2021-07-22 | Functions | Lais M. |
| 2021-08-05 | Vectors | Loren |
| 2021-08-19 | Iteration | Izabela |
| 2021-09-02 | Model basics | Gladis |
| 2021-09-16 | Model building | Liz |
| 2021-09-30 | Many models | Igor |
| 2021-10-14 | R Markdown | Marcel |
| 2021-10-28 | Graphics for communication | Lais M |
| 2021-11-11 | R Markdown formats | Loren |
| 2021-11-25 | R Markdown workflow | Izabela |
| 2021-12-09 | Conclusion | Gladis |