Data Validation First

Before writing any analysis code, understand the data:

Always run these first

df.shape # rows x columns df.dtypes # column types df.isnull().sum() # missing values per column df.describe() # statistics for numeric columns df.head() # sample rows

Key questions:

• Are there nulls in columns you'll join or filter on?

• Are numeric columns stored as strings? (parse_dates, astype)

• Are there unexpected duplicates (check primary key uniqueness)?

• Does the row count match your expectation from the source?

Anti-pattern: Running .groupby().sum() without first checking for nulls in the groupby key.