data-validation-first

# Data Validation First Before writing any analysis code, understand the data: ```python # 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.