exploratory-data-analysis SKILL.md skillA

exploratory-data-analysis from jpeetz/agent-skills is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.

mdr add jpeetz/agent-skills/exploratory-data-analysis@git:20261026.ddc2cce

Pins git:20261026.ddc2cce in mdr.lock. Pin the fingerprint instead.

Audit grade

A, 17 of 17 checks passed

Kind

SKILL.md skill

Repository

jpeetz/agent-skills

Path

skills/data/exploratory-data-analysis/SKILL.md

Versions recorded

1

Latest version

git:20261026.ddc2cce, committed Oct 26, 2026

Size

8,952 bytes

Repository stars

16

License

none declared

Use this skill when exploring an unfamiliar dataset, investigating data quality issues, validating data pipeline outputs before production use, reviewing SQL queries for correctness and performance, or producing a data quality scorecard for a data asset.

Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.

What the file says

# Exploratory Data Analysis

## Overview

Systematic framework for exploratory data analysis, data quality validation, and query correctness review. Designed for data analysts, data engineers, and AI agents who need to understand, validate, and document data assets before building on them.

## When to Use

- Exploring an unfamiliar dataset for the first time
- Investigating data quality concerns (wrong totals, unexpected nulls, stale data)
- Validating data pipeline outputs before downstream consumption
- Reviewing SQL or data transformation queries for correctness
- Onboarding a new data source and assessing its quality profile
- Producing a formal data quality scorecard
- Analysing root cause of metric changes (drops, spikes)
- Preparing data for reporting or dashboard consumption

## 1: Exploratory Data Analysis (EDA)

### Load and Profile
Start by understanding the data's shape and basic characteristics:

```python
import pandas as pd
import numpy as np

df = pd.read_parquet('data.parquet')  # or CSV, DB export, etc.

# Basic shape
print(f"Shape: {df.shape}")
print(f"Columns: {list(df.columns)}")
print(f"Dtypes:\n{df.dtypes}")

# Summary statistics for numeric columns
…

Read the whole file at its exact version.

How to install

mdr add jpeetz/agent-skills/exploratory-data-analysis@sha256:6d91eeefc54cf60e

[![mdr](https://markdownregistry.com/badge/art_xty7rv3jbk3k7b5z.svg)](https://markdownregistry.com/a/art_xty7rv3jbk3k7b5z)

Versions

The registry has recorded 1 version of this file, committed on Oct 26, 2026.

Audit of the latest version

Source

API

GET https://markdownregistry.com/api/v1/artifacts/art_xty7rv3jbk3k7b5z
GET https://markdownregistry.com/api/v1/resolve?ref=jpeetz/agent-skills/exploratory-data-analysis
GET https://markdownregistry.com/api/v1/blob/6d91eeefc54cf60e7561b51a8e6509db2de4e4dc40c515a6fed13118ce1731f8

Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.

Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.

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