Statsmodels Cheat Sheet

import statsmodels.api as smX = sm.add_constant(X)               # adds an intercept columnmodel = sm.OLS(y, X).fit()print(model.summary())               # coefficients, R-squared, p-values, F-statprint(model.params, model.pvalues, model.rsquared)

import statsmodels.formula.api as smfmodel = smf.ols("sales ~ tv + radio + newspaper", data=df).fit()print(model.summary())logit = smf.logit("churn ~ tenure + monthly_charges", data=df).fit()print(logit.params)

from statsmodels.tsa.arima.model import ARIMAfrom statsmodels.tsa.stattools import adfullerresult = adfuller(series)             # test for stationarityprint("p-value:", result[1])model = ARIMA(series, order=(1, 1, 1))fitted = model.fit()forecast = fitted.forecast(steps=12)