Missing data and cleaning

Missing values show up as NaN. isna() flags them, dropna() removes rows and fillna() replaces them.

Fix types explicitly with astype or the to_ helpers, and remove exact repeats with drop_duplicates.

Chain your cleaning steps and reassign the result — most pandas methods return a new frame rather than editing in place.