Cleaning data accounts for 70-80% of an analyst’s time. This skill teaches you how to understand the nature of your data, identify problem areas, and then clean the data set to enable your analysis using R.
Alter data types to enable later analytics as well as altering and renaming columns in a dataframe for tidy data sets.
Clean string data, manage missing data values, duplicate data rows, and manage invalid data.
Validate data cleanliness using asserts.