Useful R Resources

A compilation of R resources that helped me. Go to this link if you want to learn how to style your own README. The following are books or courses that cover almost everything: (1) Advanced R, (2) Albert Rapp data science book and (3) a fantastic syllabus by John Paul Helveston.

Setting up yourself

1. A collection of short tutorials on basic R features. I recommend the ones on installing R and RStudio and on how to use R Projects: link

RStudio shorcuts

1. Create a new script: CRTL + SHIFT + n
2. Save a script: CTRL + s
3. Pipe operator %>%: CTRL + SHIFT + m
4. This operator ~: ALT GR + 4 + SPACE.

Git and GitHub

Git and GitHub

1. A wonderful book to show how to use Git and GitHub to R users. I followed the first chapters when I started to work with Git.
2. A video tutorial to get started with Git and GitHub in RStudio: link.
3. A nice interactive website to learn Git branching: link.

GitHub Actions

1. A bookdown on GitHub Actions for R users.
2. The latest update on GitHub Actions for R developers.
3. A comprehensive list of every action.

Data Wrangling

Tidyverse

1. This four-part series on Data Wrangling by RStudio. Recommended even for more advanced R users: (1) Introduction, (2) Tidy Data and tidyr, (3) Data Manipulation Tools: dplyr and (4) Working with Two Datasets.
2. Some use cases and tricks on dplyr::filter: 1 and 2.
3. Ten tricks in the tidyverse: video.

Complementary to tidyverse

1. Function apply and derivatives (to avoid loops): link
2. In janitor, the function tabyl.

Advanced Data Wrangling with Tidyverse

Common cases

1. How to use dplyr::across to perform operations on multiple columns: documentation and nice blogpost.
2. Difference between across and c_across: link.
3. Create new variables with case_when (and mutate): link and a nice advice and to solve problems with UTF-8 characters.

Specific cases

1. Fill empty cells with NA (with tidyverse): Link.
2. Add empty columns to a dataframe with add_column(): link.

Data Visualization (with ggplot)

Theory

1. Some tricks on how to effectively use color: link.

Basic

Advanced

1. Multi panel plots with facet_wrap and facet_grid: link.
2. A bunch of graphics with some data wrangling tricks: link.

Maps

1. A nice video with USA voting data.
2. A thorough tutorial to create maps of Spain.

Tables

gt package

1. Various links from RStudio Youtube channel with live coding battles: 1, 2, 3.
2. Rich Iannone introduces the package and presents new features (more features here).

reactable

1. A long video from the reactable package mantainer, which helps you create interactive tables.

Web Scraping

1. A thorough and beautiful tutorial, by Andrew Heiss: link.
2. Web scraping with GitHub Actions video tutorial: link.
3. There are several examples in this very GitHub.

RMarkdown & Quarto

RMarkdown

The starting point to RMarkdown: book.

Parametrized reports

1. A nice video tutorial focused on the params option: video.
2. This video covers a lot more options to make parametrized reports.
3. Financial reports example.

Styling

1. Make awesome tables with kable.
2. A video tutorial which is also useful for theming Shiny apps.

Quarto

1. Some slides by a prominent RStudio worker: link.

Shiny Apps

Examples

1. An incredible example with U.S. gas prices: link.

Other interesting videos

1. The creator of tidyverse showing an example of a data science project: video.