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)
