Guided Notes

Cleaning Empty Cells

Finding missing values, removing rows with dropna, and filling gaps with fillna, mean, median, and mode.

Why data needs cleaning

Slide 1 / 5

Bad data leads to wrong answers. The four most common problems are:

β€’ Empty cells β€” values that are missing. β€’ Data in the wrong format β€” dates stored as text, numbers with symbols. β€’ Wrong data β€” values that can't be true, like a 450-minute workout. β€’ Duplicates β€” the same row recorded twice.

This chapter handles empty cells; the next handles the other three.

← Selecting, Filtering & Sorting