example-datasets - SKILL.md Agent Skill

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.

CausalPy ships with built-in datasets that can be loaded with cp.load_data(...).

import causalpy as cp

df = cp.load_data("did")

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

Prefer these bundled datasets for examples and docs instead of fetching data at runtime.
For method selection, use choosing-causalpy-methods after identifying the data shape.
For fitting and plotting, use running-causalpy-experiments.