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

What you’ll 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

Requirements
Basic Tidyverse skills
Basic knowledge of R and R-Studio
Ability to run scripts in R-Studio

Description
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 filesHow to change the naming conventions of columns when reading in dataHow to read many files into R that are in the same folderHow to read many files into R that are in nested foldersImprove working with columnsHow to select columns with tidyselectHow to select columns with tidyselect and regular expressionsHow to rename many columns at onceImprove creating and modifying columnsHow to bin continuous variablesHow to create many columns from one columnHow to anonymize columnsHow to mask valuesHow to lump factor levelsHow to order factor levelsHow to apply a function across many columnsImprove working with rowsHow to filter rows based on a condition across multiple columnsHow to improve slicing rowsHow to do rowwise calculationsImprove working with incomplete dataHow to expand data frames and create complete combinations of valuesImprove converting data frames between longer and wider formatsHow to make a data frame longerHow to make a data frame widerImprove your Tidyverse fundamentalsHow to make use of curly curly inside functionsImprove your purrr skillsHow to make sense of vectors, lists, and data framesHow to use the map function family effectivelyHow to use safely and possiblyHow to use map_vecHow to use the map2 and pmap function family effectivelyHow to create plots from a nested tibbleHow to fit models from a nested tibbleHow to use the walk function family effectivelyHow to do intermediate tests with walk in between pipesI 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.

Overview
Section 1: Introduction

Lecture 1 Welcome

Lecture 2 Technical setup

Lecture 3 Get your PDF-book

Section 2: Improve Reading Files

Lecture 4 How to change the naming conventions of columns when reading in data

Lecture 5 How to read many files into R that are in nested folders

Lecture 6 How to read many files into R that are in the same folder

Section 3: Improve Working With Columns

Lecture 7 How to select columns with tidyselect

Lecture 8 How to select columns with tidyselect and regular expressions

Lecture 9 How to rename many columns at once

Section 4: Improve Creating and Modifying Columns

Lecture 10 How to bin continuous variables

Lecture 11 How to create many columns from one column

Lecture 12 How to anonymize columns

Lecture 13 How to mask values (e.g. credit card numbers)

Lecture 14 How to lump factor levels

Lecture 15 How to order factor levels

Lecture 16 How to apply a function across many columns

Section 5: Improve Working With Rows

Lecture 17 How to filter rows based on a condition across multiple columns

Lecture 18 How to improve slicing rows

Lecture 19 How to do rowwise calculations

Section 6: Improve Working With Incomplete Data

Lecture 20 How to expand data frames and create complete combinations of values

Section 7: Improve Converting Data Frames Between Longer and Wider Formats

Lecture 21 How to make a data frame longer

Lecture 22 How to make a data frame wider

Section 8: Improve Your Tidyverse Fundamentals

Lecture 23 How to make use of curly curly inside functions

Section 9: Improve Your Purrr Skills

Lecture 24 How to make sense of vectors, lists, and data frames

Lecture 25 How to use the map function family effectively

Lecture 26 How to use safely and possibly

Lecture 27 How to use map_vec

Lecture 28 How to use the map2 and pmap function family effectively

Lecture 29 How to use map, map2, and pmap functions with nested data frames

Lecture 30 How to create plots from a nested tibble

Lecture 31 How to fit models from a nested tibble

Lecture 32 How to use the walk function family effectively

Lecture 33 How to do intermediate tests with walk in between pipes

Beginners in Tidyverse programming who want to improve their skills,Data Scientists who want to improve their data transformation skills,Data journalists who want to gain more insights from data,Scientists and researchers who work with quantitative data