CLiREN-LMS
Data Cleaning and Preparation in R

Common Cleaning Risks and How to Avoid Them

Overview

30-45 minutes Applied Step 1 of 9
Overview

Overview

1 / 9
R makes data manipulation efficient, but efficiency can magnify errors. A single incorrect line of code can affect every record. For that reason, cleaning scripts should be developed cautiously, reviewed, and tested. The goal is not to be afraid of R, but to use it with professional discipline.