Feols.tidy

tidy(alpha=0.05, inference_type='regular')

Tidy model outputs.

Return a tidy pd.DataFrame with the point estimates, standard errors, t-statistics, and p-values.

Parameters

Name	Type	Description	Default
alpha	float	The significance level for the confidence intervals. If None, computes a 95% confidence interval (`alpha = 0.05`).	`0.05`
inference_type	regular	Type of coefficient-wise inference to report. Only `"regular"` is currently available. Defaults to `"regular"`.	`"regular"`

Name	Type	Description
tidy_df	pd.DataFrame	A tidy pd.DataFrame containing the regression results, including point estimates, standard errors, t-statistics, and p-values.

import pyfixest as pf

fit = pf.feols("Y ~ X1 + X2 | f1", pf.get_data())
fit.tidy()

	Estimate	Std. Error	t value	Pr(>\|t\|)	2.5%	97.5%
Coefficient
X1	-0.949526	0.066373	-14.305943	0.0	-1.079777	-0.819274
X2	-0.174225	0.017596	-9.901590	0.0	-0.208755	-0.139695

Changing the variance estimator changes the standard errors, t-values and p-values reported by tidy().

fit.vcov("hetero").tidy()

	Estimate	Std. Error	t value	Pr(>\|t\|)	2.5%	97.5%
Coefficient
X1	-0.949526	0.065020	-14.603584	0.0	-1.077123	-0.821929
X2	-0.174225	0.018247	-9.548359	0.0	-0.210033	-0.138418