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Going From Beginner to Advanced in the Tidyverse

Go beyond mutate, select or filter and learn the skills that will make you a Tidyverse expert

     
  • 4.7
  •  |
  • Reviews ( 3 )
₹1799

This Course Includes

  • iconudemy
  • icon4.7 (3 reviews )
  • icon8.5 total hours
  • iconenglish
  • iconOnline - Self Paced
  • iconcourse
  • iconUdemy

About Going From Beginner to Advanced in the Tidyverse

I have created the course for all Tidyverse learners who feel they have reached a plateau in their skills. If you are familiar with the basic functions such as mutate, filter, select or arrange and want to improve, this course is for you.

While the basics of Tidyverse are covered very well in dozens of good offerings, it's hard to find the tricks and features that separate Tidyverse beginners from very good programmers. Most of the tricks are scattered in hundreds of forums, blog posts and documentation. That's why in June 2022 I started to bundle all the tricks into a single resource. This course is, in my opinion, the most dense and best resource to learn all the good parts of the Tidyverse. You don't have to take this course, but investing in it will save you a lot of time researching online. I've spent 300 hours searching the internet and compiling all the tricks I could find into this unique resource so you don't have to.

This is not just a video course! The course comes with a 360-page PDF book that accompanies the chapters of this book. The book goes into much more detail than the videos and includes some topics not covered in the videos.

The online course includes 30 concrete tips structured along specific improvements:

Improve reading files

How to change the naming conventions of columns when reading in data

How to read many files into R that are in the same folder

How to read many files into R that are in nested folders

Improve working with columns

How to select columns with tidyselect

How to select columns with tidyselect and regular expressions

How to rename many columns at once

Improve creating and modifying columns

How to bin continuous variables

How to create many columns from one column

How to anonymize columns

How to mask values

How to lump factor levels

How to order factor levels

How to apply a function across many columns

Improve working with rows

How to filter rows based on a condition across multiple columns

How to improve slicing rows

How to do rowwise calculations

Improve working with incomplete data

How to expand data frames and create complete combinations of values

Improve converting data frames between longer and wider formats

How to make a data frame longer

How to make a data frame wider

Improve your Tidyverse fundamentals

How to make use of curly curly inside functions

Improve your purrr skills

How to make sense of vectors, lists, and data frames

How to use the map function family effectively

How to use safely and possibly

How to use map_vec

How to use the map2 and pmap function family effectively

How to create plots from a nested tibble

How to fit models from a nested tibble

How to use the walk function family effectively

How to do intermediate tests with walk in between pipes

I really hope this course makes a difference to you and can improve your Tidyverse game. Take 10 to 15 hours to study the content and I promise you'll be a much better Tidyverse programmer by the end of the journey. Join us.

What You Will Learn?

  • How to change the naming conventions of columns when reading in data.
  • How to read many files into R that are in nested folders.
  • How to read many files into R that are in the same folder.
  • How to select columns with tidyselect.
  • How to select columns with tidyselect and regular expressions.
  • How to rename many columns at once.
  • How to bin continuous variables.
  • How to create many columns from one column.
  • How to anonymize columns.
  • How to mask values (e.g. credit card numbers).
  • How to lump factor levels.
  • How to order factor levels.
  • How to apply a function across many columns.
  • How to filter rows based on a condition across multiple columns.
  • How to improve slicing rows.
  • How to do rowwise calculations.
  • How to expand data frames and create complete combinations of values.
  • How to make a data frame longer.
  • How to make a data frame wider.
  • How to make use of curly curly inside functions.
  • How to make sense of vectors, lists, and data frames.
  • How to use the map function family effectively.
  • How to use safely and possibly.
  • How to use map_vec.
  • How to use the map2 and pmap function family effectively.
  • How to use map, map2, and pmap functions with nested data frames.
  • How to create plots from a nested tibble.
  • How to fit models from a nested tibble.
  • How to use the walk function family effectively.
  • How to do intermediate tests with walk in between pipes.