Stata Data Cleaning
meleantonio/awesome-econ-ai-stuff
Clean and transform messy data in Stata with reproducible workflows
Load built-in CausalPy example datasets for demos, tutorials, tests, and quick causal-analysis prototypes.
Install Example Datasets
$ npx skills add pymc-labs/CausalPy --skill example-datasets -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install pymc-labs/CausalPy example-datasets --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/pymc-labs/CausalPy.git skills-src && mkdir -p .claude/skills && cp -r skills-src/causalpy/skills/example-datasets .claude/skills/example-datasets && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "example-datasets" agent skill from https://github.com/pymc-labs/CausalPy/tree/main/causalpy/skills/example-datasets into .claude/skills/example-datasets/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "example-datasets", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/pymc-labs/CausalPy/tree/main/causalpy/skills/example-datasetsType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add pymc-labs/CausalPy --skill example-datasets -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install pymc-labs/CausalPy example-datasets --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/pymc-labs/CausalPy.git skills-src && mkdir -p .agents/skills && cp -r skills-src/causalpy/skills/example-datasets .agents/skills/example-datasets && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "example-datasets" agent skill from https://github.com/pymc-labs/CausalPy/tree/main/causalpy/skills/example-datasets into .agents/skills/example-datasets/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "example-datasets", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add pymc-labs/CausalPy --skill example-datasets -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install pymc-labs/CausalPy example-datasets --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/pymc-labs/CausalPy.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/causalpy/skills/example-datasets .cursor/skills/example-datasets && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "example-datasets" agent skill from https://github.com/pymc-labs/CausalPy/tree/main/causalpy/skills/example-datasets into .cursor/skills/example-datasets/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "example-datasets", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/pymc-labs/CausalPy.git --path causalpy/skills/example-datasets--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add pymc-labs/CausalPy --skill example-datasets -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install pymc-labs/CausalPy example-datasets --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/pymc-labs/CausalPy.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/causalpy/skills/example-datasets .gemini/skills/example-datasets && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "example-datasets" agent skill from https://github.com/pymc-labs/CausalPy/tree/main/causalpy/skills/example-datasets into .gemini/skills/example-datasets/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "example-datasets", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install pymc-labs/CausalPy example-datasetsInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add pymc-labs/CausalPy --skill example-datasets -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/pymc-labs/CausalPy.git skills-src && mkdir -p .github/skills && cp -r skills-src/causalpy/skills/example-datasets .github/skills/example-datasets && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "example-datasets" agent skill from https://github.com/pymc-labs/CausalPy/tree/main/causalpy/skills/example-datasets into .github/skills/example-datasets/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "example-datasets", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add pymc-labs/CausalPy --skill example-datasets -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install pymc-labs/CausalPy example-datasets --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/pymc-labs/CausalPy.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/causalpy/skills/example-datasets .opencode/skills/example-datasets && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "example-datasets" agent skill from https://github.com/pymc-labs/CausalPy/tree/main/causalpy/skills/example-datasets into .opencode/skills/example-datasets/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "example-datasets", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
example-datasets- GitHub stars
- 1.2k
- Token cost
- ~587 tokens
- SKILL.md length
- 215 words
- Files
- 1
- Skills in repo
- 12
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
Load built-in CausalPy example datasets for demos, tutorials, tests, and quick causal-analysis prototypes.
- The user needs sample data
- SKILL.md covers Usage, Available Datasets and Guidance
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- Asks which demo datasets are available
What it does
Example Datasets is an agent skill from pymc-labs/CausalPy. Load built-in CausalPy example datasets for demos, tutorials, tests, and quick causal-analysis prototypes. Use when the user needs sample data or asks which demo datasets are available.
Its SKILL.md is about 590 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Research & Science, covering Econometrics and empirical research. The repository describes itself as: A Python package for causal inference in quasi-experimental settings. The licence is Apache-2.0.
When your agent uses it
- The user needs sample data
- Asks which demo datasets are available
Example prompts
- “/example-datasets”
Requirements
- Python 3
What it can do on your machine
Read from SKILL.md and the folder at commit f17b30f. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md (its code samples are python).
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Example Datasets loads about 587 tokens when it runs. Until then it costs about 51 tokens; SKILL.md has 215 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from pymc-labs/CausalPy at commit f17b30f, republished under its Apache-2.0 licence (© pymc-labs). 215 words, ~587 tokens.
Download SKILL.mdSave it as
.claude/skills/example-datasets/SKILL.md (or your agent's skills folder).- name
- example-datasets
- description
- Load built-in CausalPy example datasets for demos, tutorials, tests, and quick causal-analysis prototypes. Use when the user needs sample data or asks which demo datasets are available.
Example Datasets
CausalPy ships with built-in datasets that can be loaded with cp.load_data(...).
Usage
import causalpy as cp
df = cp.load_data("did")Available Datasets
| Key | Typical use | Description |
|---|---|---|
"did" | Difference-in-differences | Synthetic DiD example data |
"banks" | Difference-in-differences | Historic banking closures data |
"its" | Interrupted time series | Seasonal synthetic ITS data |
"its simple" | Interrupted time series | Simplified synthetic ITS data |
"covid" | Interrupted time series | Deaths and temperature data for England and Wales |
"sc" | Synthetic control | Synthetic control example data |
"brexit" | Synthetic control | UK GDP data for Brexit causal impact |
"california_prop99" | Synthetic control | California Proposition 99 cigarette sales panel |
"rd" | Regression discontinuity | Synthetic RD example data |
"drinking" | Regression discontinuity | Minimum legal drinking age data |
"geolift1" | Geo experiments | Single-treatment geo-lift data |
"geolift_multi_cell" | Geo experiments | Multi-cell geo-lift data |
"anova1" | PrePostNEGD | Pre/post nonequivalent groups example |
"risk" | Instrumental variables | Acemoglu, Johnson, and Robinson institutions data |
"schoolReturns" | Instrumental variables | Schooling returns data |
"nhefs" | Inverse propensity weighting | National Health and Nutrition Examination Survey data |
"lalonde" | Inverse propensity weighting | LaLonde propensity-score data |
"nets" | Inverse propensity weighting | National Supported Work Demonstration data |
"pisa18" | General examples | PISA 2018 sample data |
"nevo" | General examples | Berry, Levinsohn, and Pakes cereal data |
"zipcodes" | Geo experiments | Zipcode-level geo-experiment data |
Guidance
- Prefer these bundled datasets for examples and docs instead of fetching data at runtime.
- For method selection, use
choosing-causalpy-methodsafter identifying the data shape. - For fitting and plotting, use
running-causalpy-experiments.
© pymc-labs, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in causalpy/skills/example-datasets of pymc-labs/CausalPy.
Open the folder on GitHubat commit f17b30f
Compare with similar skills
Example Datasets next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Example Datasets this skillpymc-labs/CausalPy | 1.2k | — | ~587 | Automated safety check: Pass | Apache-2.0 | |
| Stata Data Cleaningmeleantonio/awesome-econ-ai-stuff | 642 | 2 repos | ~1.8k | Automated safety check: Pass | Custom licence | |
| Causal Inferencebrycewang-stanford/Auto-Empirical-Research-Skills | 4.5k | — | ~2k | Automated safety check: Pass | MIT | |
| Ols Regressionbrycewang-stanford/Auto-Empirical-Research-Skills | 4.5k | — | ~1.2k | Automated safety check: Pass | Custom licence | |
| Data Depositbrycewang-stanford/Auto-Empirical-Research-Skills | 4.5k | — | ~1.2k | Automated safety check: Notes | Custom licence | |
| Econometrics Juliabrycewang-stanford/Auto-Empirical-Research-Skills | 4.5k | — | ~1.4k | Automated safety check: Pass | Custom licence |
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Related
Categories
Questions about Example Datasets
What does Example Datasets do?
Load built-in CausalPy example datasets for demos, tutorials, tests, and quick causal-analysis prototypes. Example Datasets is an agent skill from pymc-labs/CausalPy. Load built-in CausalPy example datasets for demos, tutorials, tests, and quick causal-analysis prototypes.
When should I use Example Datasets?
Example Datasets fits situations like: the user needs sample data; asks which demo datasets are available.
How do I install Example Datasets in Claude Code?
Run `npx skills add pymc-labs/CausalPy --skill example-datasets -a claude-code`. Or copy the skill folder (causalpy/skills/example-datasets in pymc-labs/CausalPy) into .claude/skills/example-datasets in your project. Claude Code loads it when a task matches its description.
How do I install Example Datasets in Codex?
Run `npx skills add pymc-labs/CausalPy --skill example-datasets -a codex`. Or copy the skill folder (causalpy/skills/example-datasets in pymc-labs/CausalPy) into .agents/skills/example-datasets in your project. Codex loads it when a task matches its description.
Can I use Example Datasets in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add pymc-labs/CausalPy --skill example-datasets -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/example-datasets, .gemini/skills/example-datasets, .github/skills/example-datasets and .opencode/skills/example-datasets in your project.
What does Example Datasets need to run?
SKILL.md names no scripts, command-line tools or credentials: Example Datasets is instructions for the agent only. Our summary lists: Python 3.
Does Example Datasets access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Example Datasets safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Example Datasets use?
Example Datasets is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Example Datasets use?
About 587 tokens (SKILL.md is roughly 2.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Example Datasets?
Skills that share tags, products or a category with Example Datasets: Stata Data Cleaning (meleantonio/awesome-econ-ai-stuff, 642 stars), Causal Inference (brycewang-stanford/Auto-Empirical-Research-Skills, 4.5k stars), Ols Regression (brycewang-stanford/Auto-Empirical-Research-Skills, 4.5k stars) and Data Deposit (brycewang-stanford/Auto-Empirical-Research-Skills, 4.5k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Example Datasets?
pymc-labs (a GitHub organization) maintains it in pymc-labs/CausalPy, which has 1,200 GitHub stars. The repository holds 12 skills in this directory. The repository was last updated on October 6, 2026.
Source: pymc-labs/CausalPy on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.