Immediate result: A commented pandas script that loads your file, does the analysis and saves a chart and summary.
Problem it solvesRepeating the same analysis in a spreadsheet every week is slow and error-prone.
sales.csv (date, region, product, units, price) · weekly revenue by region + chart
df['revenue'] = df.units * df.price
weekly = df.groupby([pd.Grouper(key='date', freq='W-MON'), 'region']).revenue.sum().unstack()
weekly.plot(); plt.savefig('weekly_revenue.png', dpi=200)
Repeating the same analysis in a spreadsheet every week is slow and prone to error. This skill writes a commented pandas script that loads your file, checks the expected columns exist, performs the analysis step by step and saves the outputs — a CSV or Excel table and a PNG chart. It explains how to run the script and which parameters to change, and fails with a clear message when the data doesn't match. Run it each week and the analysis takes seconds instead of an afternoon. To use it, paste the skill into your assistant and send the file type and columns, the analysis you want and the output (table, chart, Excel).
![Python analysis script AI skill for Data analyst: you paste "sales.csv (date, region, product, units, price) · weekly revenue by region + chart" and get "df['revenue'] = df.units * df.price"](/skills/img/python-analysis-script-ai-skill.jpg)
# Skill: Python analysis script
You are running the "Python analysis script" skill for me. I work as: Data analyst. What I need from you: a commented pandas script that loads my file, does the analysis and saves a chart and summary.
## When I send you the file type and columns, the analysis I want and the output (table, chart, Excel)
1. Write a script that loads the data and validates columns.
2. Perform the analysis step by step with comments.
3. Save outputs (CSV/Excel and a PNG chart).
4. Explain how to run it and change the parameters.
## Reply in this format
- Script (code)
- How to run
- Parameters to change
- Assumptions
## Rules
- Use pandas and matplotlib only unless asked.
- Fail with a clear message if a column is missing.
- Use only the facts I give you; mark anything you had to assume with [ASSUMPTION].
- If something essential is missing, ask me one short question, then continue.
- No preamble or filler: start with the result.
Confirm you're ready in one line, then wait for me to send the file type and columns, the analysis I want and the output (table, chart, Excel).Then sendThe file type and columns, the analysis you want and the output (table, chart, Excel). For example: sales.csv (date, region, product, units, price) · weekly revenue by region + chart
Upload it to Claude, add it to ChatGPT's Codex app, clone it into Claude Code, or download the SKILL.md for any agent. Full guide with screenshots →
Download the ZIP and upload it in Claude. Claude then uses the skill on its own whenever a request matches.
Download ZIP
OpenAI's Codex app reads the same SKILL.md format. Copy the skill into your Codex skills folder:
$ git -c http.version=HTTP/1.1 clone https://scienceofapps.com/skills/ai-skills.git
$ cp -r ai-skills/python-analysis-script ~/.codex/skills/
Clone the library and copy this skill into your Claude Code skills folder.
$ git -c http.version=HTTP/1.1 clone https://scienceofapps.com/skills/ai-skills.git
$ cp -r ai-skills/python-analysis-script ~/.claude/skills/~/.claude/skills/ for all projects, or .claude/skills/ inside one project.Download the skill file and put it in a folder named after the skill.
Download SKILL.md~/.claude/skills/python-analysis-script/SKILL.md.Repositoryscienceofapps.com/skills/ai-skills.git · all 200 skills, one folder each, plain git over HTTPS
Repeating the same analysis in a spreadsheet every week is slow and error-prone. The skill fixes that: a commented pandas script that loads your file, does the analysis and saves a chart and summary.
Copy the skill and paste it as the first message of a new chat, then send your input. To keep it, paste it into a ChatGPT Project or custom GPT, a Claude Project or a Gemini Gem, or upload the SKILL.md file as a Claude Skill.
Send the file type and columns, the analysis you want and the output (table, chart, Excel). If something essential is missing, the skill asks you one short question and then continues.
Yes. It's free to copy, use and adapt, with no sign-up, and works in the free versions of ChatGPT, Claude, Gemini and Copilot.
ProblemA key number dropped overnight and everyone has a theory.
Checkout conversion fell from 3.1% to 2.2% on Tuesday
Check 1: did the analytics event or app version change Tuesday?
Decompose: sessions → add-to-cart → checkout start → payment success
If only Android 5.12 dropped: the release is the prime suspect.
Immediate resultA structured investigation plan that rules out data issues first, then segments to find the cause.
ProblemAnalysis gets presented as charts with no story, and leaders can't act on it.
Findings: repeat customers 22% of buyers but 51% of revenue; repeat rate fell 4 pts
Headline: Repeat customers are a fifth of buyers but half our revenue — and we're losing them.
Recommendation: fund a 6-week retention test before more acquisition spend.
Caveat: one quarter of data.
Immediate resultA one-page summary: the headline, three supporting points, the 'so what' and a recommendation.
ProblemTeams need a forecast by Friday and either guess or overbuild a model.
Monthly orders Oct 2025–Sep 2026, forecast Oct–Dec 2026
History: +3% a month, with a Diwali spike (Oct–Nov ≈ 1.4× normal).
Method: seasonal naive × trend — simple and explainable.
Base Nov 2026: 18,900 · low 16,800 · high 21,000
Immediate resultA transparent forecast with method, formulas, base, high and low cases.
All 14 data & analytics skillsAll 200 skillsRead it in the articleProve it: AI for Data Analysts Certification (free test)
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110 real paywalls from top apps, taken apart, rated out of 5 and decoded with the Laws of UX — plus the frameworks, copy and checklists to ship your own. By Sushant Singh, founder of Science of Apps.