Steps for effective data cleaning:
Removing columns and rows
Setting the first row as header
Changing data types, replacing values, and removing spaces
Handling errors, renaming and optimizing steps
Filling down missing values, splitting columns, and removing duplicates
Tips and tricks to automate data cleaning
