This is the repository for the LinkedIn Learning course R Tidyverse Applications. The full course is available from LinkedIn Learning.
Are you an R programmer looking to take your R tidyverse knowledge to the next level? In this course, Megan Silvey aims to provide R programmers with a better overall understanding of the R tidyverse and how to utilize its packages. Megan uses practical, real-world examples that showcase concepts that you can use in your own work. Using a dataset from KinetEco’s sales, customer, and product data, Megan shows you how you can use the R tidyverse packages to load, clean, analyze, and visualize this data in an efficient manner with these packages.
There is one branch for this course containing four chapter folders corresponding to the four chapters in the course. Inside these chapter folders are the coding exercise files. The naming convention for the exercise files is CHAPTER#_MOVIE#. As an example, the branch named 02_03 corresponds to the second chapter and the third video in that chapter.
All coding exercise files will have a beginning and an end state, for example '02_03e' would be the ending file for the third movie in the second chapter. These are marked with the letters b for "beginning" and e for "end". The b file contains the code as it is at the beginning of the movie. The e file contains the code as it is at the end of the movie.
Instructor Megan Silvey
Data Scientist
Check out my other courses on LinkedIn Learning.