Going from Beginner to Advanced in the Tidyverse

Transform yourself from a beginner to an advanced Tidyverse user with the help of this PDF-book. The book contains a collection of the most fascinating and useful Tidyverse tricks. I have been gathering all Tidyverse tricks I could find since June 2022 and compiled them into this singular resource. To date, over 900 individuals have downloaded the eBook.

Purchasing this book grants you access to a 360-page PDF book that encompasses 10 chapters and 23 tutorials. Additionally, you receive lifelong access to book updates upon purchasing.

❗If you prefer to learn by watching videos, you should buy the PDF book with the video course. You can find the video course on Thinkific: https://christian-burkhart.thinkific.com/courses/advanced-tidyverse. This offering here on Gumroad only provides the PDF book.

Book chapters:

1. Improve reading files (How to improve reading files with read_* ; how to read many files into R)
2. Improve working with columns (How to better select colums; how to rename many columns at once )
3. Improve creating and modifying columns (How to count with count, add_count, and add_tally, How to extract multiple columns from one column; how to anonymize columns; how to improve lumping factor levels; how to order factor levels; how to apply functions across many columns)
4. Improve working with rows (How to filter rows based on multiple variables; how to slice rows, How to do rowwise calculations)
5. Improve grouping data (How to run many models with the new dplyr grouping functions)
6. Improve working with incomplete data (How to expand data frames and create complete combinations of values)
7. Improve converting data frames between longer and wider formats (How to make data frames longer; how to make data frames wider)
8. Improve your tidyverse fundamentals (How to make use of curly curly inside functions)
9. Improve your purrr skills (How to use the map function family effectively; how to use the map2 and pmap function family effectively; how to use the walk function family effectively
10. Improve your code's performance (How to utilize your computer's parallel processing capabilities using future and furrr; how to speed up your data analysis with dtplyr)

Do not hesitate to contact me if you wish to learn more about the book or get in touch with me. You can find me on LinkedIn and Twitter.

Changelog

• May 18, 2023: I have made a few minor revisions to correct several typos and inconsistencies