def test_df_selector_raise_missing_column(self, categorical: pd.DataFrame): select = Select(["category_a", "category_b", "category_c"]) with pytest.raises( TransformerError, match="The DataFrame does not include the columns:"): select.fit_transform(categorical)
def test_df_selector_raise_missing_column(categorical): select = Select(['category_a', 'category_b', 'category_c']) with pytest.raises( TransformerError, message="Expecting TransformerError but no error occurred", match="The DataFrame does not include the columns:"): select.fit_transform(categorical)
def test_df_selector_with_multiple_columns(categorical): select = Select(['category_a', 'category_b']) result = select.fit_transform(categorical) assert isinstance(result, pd.DataFrame) assert len(categorical) == len(result) assert {'category_a', 'category_b'} == set(result.columns)
def test_df_selector_returns_correct_dataframe(categorical, container): select = Select(container) result = select.fit_transform(categorical) assert isinstance(result, pd.DataFrame) assert len(categorical) == len(result) assert {'category_a'} == set(result.columns)
def test_df_selector_with_multiple_columns(self, categorical: pd.DataFrame): select = Select(["category_a", "category_b"]) result = select.fit_transform(categorical) assert isinstance(result, pd.DataFrame) assert len(categorical) == len(result) assert {"category_a", "category_b"} == set(result.columns)