45c9fcd8b1df849a0c3b19403d13da38b7cd68c3,tpot/operators/preprocessors/zero_count.py,ZeroCount,transform,#ZeroCount#Any#,34

Before Change

        num_features = len(feature_cols_only.columns.values)

        modified_df = input_df.copy()
        modified_df["non_zero"] = feature_cols_only.\
            apply(lambda row: np.count_nonzero(row), axis=1).astype(np.float64)
        modified_df["zero_col"] = feature_cols_only.\
            apply(lambda row: (num_features - np.count_nonzero(row)), axis=1).astype(np.float64)

        return modified_df.copy()

After Change

        X_transformed: array-like, shape (n_samples, n_features)
            The transformed feature set
        
        X = check_array(X)
        n_samples, n_features = X.shape

        X_transformed = np.copy(X)

Instances