Data Cleaning
Missing Data: Drop, Impute, or Flag
8 min+70 XPStep 1/10
Three different kinds of missing
A blank cell isn't one problem — it's three, and they need different responses:
- Missing at random: a sensor dropped packets — the gaps have no pattern. The safest case.
- Missing for a reason: high earners skip the income question; patients who feel fine skip follow-up tests. The blank itself carries information — it correlates with what you're studying.
- Missing because of the answer: a churned customer simply stops appearing. The absence is the outcome.
Before touching anything, ask why it's blank. Fill in a systematic gap carelessly and you can erase the very pattern that explains your result.
warning
If sicker patients miss follow-up appointments more often, a column of blank results is a symptom column — not a data problem to scrub away.