Resources
A collection of helpful resources for learning R and data analysis.
Books
R for Data Science (2nd edition) by Hadley Wickham: The go-to book for data analysis with the tidyverse.
ModernDive: Statistical Inference via Data Science: Beginner-friendly introduction to R and data analysis with the tidyverse.
What They Forgot to Teach You About R by J. Bryan and J. Hester: Good practice tips for R code and R projects.
Big Book of R: Directory of free R books sorted by topic.
Other
- Tidyverse style guide: How to style your R code according to good practice.
- Curated collection of R learning resources: Books, websites, tutorials, help channels and more.
Cheatsheets
Posit cheatsheets overview: Full collection of all available cheatsheets.
Individual cheatsheets relevant to this workshop:
Packages
The tidyverse website links to all tidyverse packages with examples and documentation.
Packages used in this workshop
| Package | Description |
|---|---|
| tidyverse | Collection of packages designed for data analysis, all working smoothly together |
| dplyr | Data manipulation: filtering, selecting, arranging, summarizing data |
| ggplot2 | Data visualization |
| tidyr | Transforming tables into tidy format for analysis |
| readr | Import and export CSV, TXT and other delimited files |
| readxl | Import Excel files from multiple sheets as tibbles |
Other useful packages
| Package | Description |
|---|---|
| haven | Import SPSS, Stata and SAS files |
| stringr | String manipulation: extracting, finding and replacing patterns |
| forcats | Working with factors (categorical data): renaming, reordering categories |
| lubridate | Working with dates and times: parsing, calculating intervals, plotting time series |
| patchwork | Combine multiple plots into one with easy layout control |
| here | Simple and robust file path handling in R projects |
| usethis | Utility functions for project setup, Git, GitHub and package development |
| styler | Automatically format your code according to the tidyverse style guide |