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Analytics & Data Analysis Best Practices

Gives Claude a disciplined pandas/matplotlib/seaborn workflow for exploratory analysis, visualization, and reproducible Jupyter notebooks.

Data & AnalyticsIntermediate★ 270⑂ 42AI score 8/10Last updated: Oct 8, 2026

What it does

  • Installs a 6-step EDA pipeline: load & inspect → clean & transform → explore relationships → visualize → validate → document and share.
  • Enforces pandas conventions: method chaining, explicit loc/iloc selection, vectorized ops over loops, categorical dtypes, memory-aware types.
  • Applies visualization standards: axis labels and titles always, colorblind-safe palettes, consistent schemes, correct export DPI.
  • Adds notebook hygiene (markdown structure, clear outputs before sharing, pinned requirements) and statistical caution (confidence intervals, effect sizes, assumption checks).

Who it's for

  • Data analysts and scientists working in Python
  • Teams that share notebooks and need reproducibility
  • Growth/marketing practitioners who build their own metric reports

Example uses

  1. "Run an EDA on this CSV" → shape/dtype/null audit, groupby summaries, and a saved boxplot figure.
  2. "Build a cleaning pipeline for revenue data" → chained dropna/assign/fillna code with post-transform validation checks.
  3. "Prep this notebook for sharing" → markdown sections, imports consolidated at top, outputs cleared, requirements.txt pinned.

· · · Install guide · · ·

Try it now, no install

Paste this into Claude to use the skill without installing anything.

Read the instructions in this file and follow them to help me:
https://raw.githubusercontent.com/Mindrally/skills/HEAD/analytics-data-analysis/SKILL.md

What I want: (describe your task here)

If Claude can't open the link, open it yourself and paste the contents instead.

↓ If it works for you, download the ZIP below and install it. Then it runs on its own — no pasting each time.

Install in the Claude app (no terminal)
  1. Download the ZIP with the button below.
  2. In Claude, open Settings → Capabilities and turn on 'Code execution and file creation'. (one time)
  3. Go to Customize → Skills → + → 'Upload a skill' and upload the ZIP.
↓ Download ZIP
Install in Claude Code

Let Claude do it — paste this into Claude Code

Install the skill I found on Claude Skill Mart.
Copy the analytics-data-analysis folder from the GitHub repo Mindrally/skills into my ~/.claude/skills/analytics-data-analysis/.
When it's done, tell me in one line what this skill can do.

Install with a command instead

git clone https://github.com/Mindrally/skills.git /tmp/mindrally-skills && mkdir -p ~/.claude/skills && cp -r /tmp/mindrally-skills/analytics-data-analysis ~/.claude/skills/

⚠ This is a third-party skill. Check the source repository before installing.

  1. Open a terminal.
  2. Clone the repo: git clone https://github.com/Mindrally/skills.git
  3. Create the skills directory: mkdir -p ~/.claude/skills
  4. Copy the skill: cp -r skills/analytics-data-analysis ~/.claude/skills/
  5. Restart Claude Code and ask something like "do an exploratory analysis of this dataset" to trigger it.
  6. Install the runtime deps if needed: pip install pandas numpy matplotlib seaborn jupyter.
View source on GitHub ↗License: Apache-2.0