Cleaning Data with R and the Tidyverse in Swirl
Author(s): Rachel Hartnett
Mount St. Mary's University
1228 total view(s), 983 download(s)
Summary:
The overall goal is to help students learn common data cleaning procedures on a dataset once they’ve collected measurements and before they are able to start their analysis. This swirl lesson is designed specifically to deal with missing data.
Contents:
Cleaning_Data.swc(SWC | 12 KB)
Final Swirl Lesson Plan_Cleaning Data.pdf(PDF | 141 KB)- GitHub - swirldev/R_Programming_E: Team swirl's R Programming Course with Email Notifications
- DataDryad link to dataset used
- Blog post on data cleaning with R and the tidyverse: detecting missing values
- QUBES - Resources: Importing Data into R
- QUBES - Resources: Sampling Distributions and Null Distributions: two swirl lessons in R
- License terms
Supporting Docs
- Cleaning_Data.swc(SWC | 12 KB)
- Final Swirl Lesson Plan_Cleaning Data.pdf(PDF | 141 KB)
- GitHub - swirldev/R_Programming_E: Team swirl's R Programming Course with Email Notifications
- DataDryad link to dataset used
- Blog post on data cleaning with R and the tidyverse: detecting missing values
- QUBES - Resources: Importing Data into R
- QUBES - Resources: Sampling Distributions and Null Distributions: two swirl lessons in R