3 docs tagged with "data-cleaning"

Duplicate rows are common in real-world data. _pandas_ provides simple methods to find and remove them.

Missing data appears as NaN (Not a Number), None, or NaT (Not a Time) in pandas. Handling it correctly is crucial for data analysis.

pandas provides string methods through the .str accessor. These methods work on Series containing strings and are essential for text data cleaning.