f49809322491c857d435bb12f5de7b09aac2d181,linearmodels/panel/data.py,PanelData,mean,#PanelData#Any#Any#,378

Before Change

            mu /= np.nansum(w, axis=axis)

        index = self.panel.minor_axis if group == "entity" else self.panel.major_axis
        out = DataFrame(mu.T, index=index, columns=self.vars)
        reindex = self.entities if group == "entity" else self.time
        out = out.loc[reindex]
        return out

After Change

        
        level = 0 if group == "entity" else 1
        if weights is None:
            mu = self._frame.groupby(level=level).mean()
        else:
            w = weights.values2d
            frame = self._frame.copy()
            frame = w * frame

Instances