Core pandas · Lesson 7 of 10

Data types and missing values

Types and missing data

Two things trip up every new analyst: data types and missing values.

Every column has a type, its dtype: whole numbers, decimals, text, and so on. Check them with df.dtypes.
Missing values show up as NaN. Find them with isnull(), and handle them with fillna() or dropna().

Python

Whether to drop missing data or fill it is a real judgment call you make as the analyst.

Exercise — check your understanding

The scores DataFrame has a missing value. Replace every missing value with 0 and store the new DataFrame in fixed.

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