Individual skill

empirical-analysis-skill-python

Parameterized Python empirical-analysis and machine-learning workflow for applied economics, public health epidemiology, supervised ML, and ML causal inference. Use when the user asks for data cleaning, feature engineering, train/test/validation splits, feature matrix X and target y, Table 1, diagnostic tests, OLS/panel/IV-style formulas, LinearRegression, Ridge, Lasso, ElasticNet, decision trees, random forests, GBDT, regression/classification metrics, DID/event-study formulas, DML/double machine learning with LinearDML, causal forests, robustness checks, mechanism or heterogeneity analysis, mediation, publication-ready tables, figures, or an end-to-end empirical paper pipeline. The skill must route execution through fixed step scripts under scripts/ instead of writing ad hoc Python code in markdown.

本地Skills功能分类库/04_数据采集整合与实证Skills/empirical-analysis-skill-python/SKILL.md

Source commit aab113340d7eecc6a48308f57c44897f8c78dda4

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Last checked

Nov 4, 2026

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