SpillPanel

data.SpillPanel(
    df,
    spatial_w,
    spatial_W,
    outcome,
    unitid,
    time,
    treat,
    covariates,
    treated_unit,
    treatment_time,
    description,
    column_map=dict(),
)

A bundled case study, ready to feed :class:scspill.SCSPILLConfig.

Attributes

Name	Type	Description
df	pd.DataFrame	Long panel with a 0/1 treated indicator column (1 for the treated unit in post-treatment periods).
spatial_w	pd.Series	Treated-to-control exposure weights, indexed by donor unit label. Raw (unnormalized); the estimator scales it to sum to one.
spatial_W	pd.DataFrame	Control-to-control spatial weights, indexed and columned by donor unit label. Raw (unnormalized); the estimator row-normalizes it.
outcome, unitid, time, treat	str	Column names in df.
covariates	tuple of str	Covariate column names in df.
treated_unit	str	Label of the treated unit.
treatment_time	int	First treated period.
description	str	One-paragraph provenance note.
column_map	dict	Mapping from original CSV headers to the column names in df (empty when no renaming was applied).

Methods

Name	Description
config_kwargs	Keyword arguments ready to splat into :class:scspill.SCSPILLConfig.

config_kwargs

data.SpillPanel.config_kwargs()

Keyword arguments ready to splat into :class:scspill.SCSPILLConfig.

Returns

Name	Type	Description
	dict	df, outcome, treat, unitid, time, spatial_w, spatial_W, and covariates.

Examples

from scspill import SCSPILL
from scspill.data import load_california

panel = load_california()
result = SCSPILL({**panel.config_kwargs(), "seed": 1}).fit()