def full_pipeline(model_type, predicted_column, grain_column, impute=True, verbose=True): """ Builds the data preparation pipeline. Sequentially runs transformers and filters to clean and prepare the data. Note advanced users may wish to use their own custom pipeline. """ # Note: this could be done more elegantly using FeatureUnions _if_ you are not using pandas dataframes for # inputs of the later pipelines as FeatureUnion intrinsically converts outputs to numpy arrays. pipeline = Pipeline([ ('remove_DTS_columns', hcai_filters.DataframeColumnSuffixFilter()), ('remove_grain_column', hcai_filters.DataframeColumnRemover(grain_column)), # Perform one of two basic imputation methods # TODO we need to think about making this optional to solve the problem of rare and very predictive values ('imputation', hcai_transformers.DataFrameImputer(impute=impute, verbose=verbose)), ('null_row_filter', hcai_filters.DataframeNullValueFilter(excluded_columns=None)), ('convert_target_to_binary', hcai_transformers.DataFrameConvertTargetToBinary( model_type, predicted_column)), ('prediction_to_numeric', hcai_transformers.DataFrameConvertColumnToNumeric(predicted_column)), ('create_dummy_variables', hcai_transformers.DataFrameCreateDummyVariables( excluded_columns=[predicted_column])), ]) return pipeline
def test_removes_row_all_nulls_exception(self): df = pd.DataFrame({'a': [1, None, 2, 3], 'b': ['m', 'f', None, 'f'], 'c': [3, 4, 5, None], 'd': [None, 8, 1, 3], 'label': ['Y', 'N', 'Y', 'N']}) self.assertRaises(HealthcareAIError, filters.DataframeNullValueFilter().fit_transform, df)
def test_removes_row_with_all_nulls(self): df = pd.DataFrame({ 'category': ['a', None, None], 'gender': ['F', 'M', None], 'age': [1, 5, None] }) result = filters.DataframeNullValueFilter().fit_transform(df) self.assertEqual(len(result), 1)
def test_removes_nothing_when_no_nulls_exist(self): df = pd.DataFrame({ 'category': ['a', 'b', 'c'], 'gender': ['F', 'M', 'F'], 'age': [1, 5, 4] }) result = filters.DataframeNullValueFilter().fit_transform(df) self.assertEqual(len(result), 3)