# Data Validation First

> Use this skill before any data analysis, transformation, or modeling. Always inspect and validate the data before drawing conclusions or writing transformations.

- Skill: `gabrielmoreira/data-validation-first` (Agent Skill)
- Install (CLI): `npx skillmds@latest add gabrielmoreira/data-validation-first`
- Raw SKILL.md: https://api.skillmd.com/api/skills/gabrielmoreira/data-validation-first/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: gabrielmoreira (https://skillmd.com/u/gabrielmoreira)
- Updated: 2026-09-09
- Page: https://skillmd.com/skills/gabrielmoreira/data-validation-first

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# 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.