| name | data-validation-first |
| description | Use this skill before any data analysis, transformation, or modeling. Always inspect and validate the data before drawing conclusions or writing transformations. |
| category | data_analysis |
Data Validation First
Before writing any analysis code, understand the data:
df.shape
df.dtypes
df.isnull().sum()
df.describe()
df.head()
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.