37f1544cb19794294029aa64e7b119b69ef09f51,category_encoders/basen.py,BaseNEncoder,fit,#BaseNEncoder#Any#Any#,92

Before Change

        // drop all output columns with 0 variance.
        if self.drop_invariant:
            self.drop_cols = []
            X_temp = self.transform(X)
            generated_cols = util.get_generated_cols(X, X_temp, self.cols)
            self.drop_cols = [x for x in generated_cols if X_temp[x].var() <= 10e-5]

        return self

After Change

            self.drop_cols = []
            generated_cols = util.get_generated_cols(X, X_temp, self.cols)
            self.drop_cols = [x for x in generated_cols if X_temp[x].var() <= 10e-5]
            try:
                [self.feature_names.remove(x) for x in self.drop_cols]
            except KeyError as e:
                if self.verbose > 0:
                    print("Could not remove column from feature names."
                          "Not found in generated cols.\n{}".format(e))

        return self

    def transform(self, X, override_return_df=False):
        Perform the transformation to new categorical data.

Instances