Panel data analysis with Python using linearmodels and pandas.
The skill file stays in the publisher's repository.
Paste the copied command in a terminal. It installs this SKILL.md into that agent.
npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill python-panel-data -a cursor -y
Panel data analysis with Python using linearmodels and pandas.
name: python-panel-data description: Panel data analysis with Python using linearmodels and pandas. workflow_stage: analysis compatibility:
This skill helps economists run panel data models in Python using pandas, statsmodels, and linearmodels, with correct fixed effects, clustering, and diagnostics.
Follow these steps to complete the task:
Before generating any code, ask the user:
Based on the context, generate Python code that:
pandaslinearmodels.PanelOLS or RandomEffectsAfter generating output:
# ============================================
# Panel Data Analysis in Python
# ============================================
import pandas as pd
from linearmodels.panel import PanelOLS
# Load data
df = pd.read_csv("panel_data.csv")
# Set panel index
df = df.set_index(["firm_id", "year"])
# Create treatment indicator
df["treat_post"] = df["treated"] * df["post"]
# Two-way fixed effects model
model = PanelOLS.from_formula(
"outcome ~ 1 + treat_post + EntityEffects + TimeEffects",
data=df
)
results = model.fit(cov_type="clustered", cluster_entity=True)
print(results.summary)
pandaslinearmodelsstatsmodelsInstall with:
pip install pandas linearmodels statsmodels