diff --git a/tests/test_dataset.py b/tests/test_dataset.py index 542cfc4..3e874ff 100644 --- a/tests/test_dataset.py +++ b/tests/test_dataset.py @@ -27,8 +27,8 @@ def test_empty_dataset() -> None: assert df.shape[0] == 0 assert np.all(df.columns == ["a", "b"]) - assert df.dtypes[0] == int - assert df.dtypes[1] == object or isinstance(df.dtypes[1], StringDtype) + assert df.dtypes.iloc[0] == int + assert df.dtypes.iloc[1] == object or isinstance(df.dtypes.iloc[1], StringDtype) def test_dataset() -> None: diff --git a/tests/test_indexed_dataset.py b/tests/test_indexed_dataset.py index 971c115..6ad62fb 100644 --- a/tests/test_indexed_dataset.py +++ b/tests/test_indexed_dataset.py @@ -34,8 +34,8 @@ def test_empty_indexed_dataset() -> None: assert df.index.get_level_values(0).dtype == int assert df.index.get_level_values(1).dtype == object or isinstance(df.index.get_level_values(1).dtype, StringDtype) - assert df.dtypes[0] == int - assert df.dtypes[1] == object or isinstance(df.dtypes[1], StringDtype) + assert df.dtypes.iloc[0] == int + assert df.dtypes.iloc[1] == object or isinstance(df.dtypes.iloc[1], StringDtype) def test_indexed_dataset() -> None: diff --git a/tests/test_type_validation.py b/tests/test_type_validation.py index 91e61ab..75d7b85 100644 --- a/tests/test_type_validation.py +++ b/tests/test_type_validation.py @@ -21,7 +21,7 @@ def is_backward_compatibility_type(dtype) -> bool: if isinstance(dtype, BackwardCompatibility): return True - if dtype not in [Any, np.integer]: + if dtype != Any: if isinstance(dtype, Callable) and isinstance(dtype(), BackwardCompatibility): # type: ignore return True @@ -58,13 +58,13 @@ def check_list_of_types(observed, expected_to_match, expected_to_fail): def test_numeric_base_python_types(): - check_list_of_types(int, [np.int64, np.int_, np.integer, int], [float, np.float_]) + check_list_of_types(int, [np.int64, np.int_, int], [float, np.float_]) check_list_of_types(float, [np.float64, np.float_, float], [int, np.int_]) check_list_of_types(bool, [np.bool_, bool], [int, np.int_]) def test_numpy_types(): - check_list_of_types(np.int64, [np.int64, np.int_, np.integer, int], [float, np.float_]) + check_list_of_types(np.int64, [np.int64, np.int_, int], [float, np.float_]) check_list_of_types(np.float64, [np.float64, np.float_, float], [int, np.int_]) check_list_of_types(np.bool_, [np.bool_, bool], [int, np.int_]) check_list_of_types(np.datetime64, [np.datetime64], [np.timedelta64, DatetimeTZDtype(tz="UTC"), np.int_]) @@ -99,7 +99,7 @@ def test_strings(): # as long as this is true df = pd.DataFrame({"a": ["a", "b", "c"]}) - assert df.dtypes[0] == object + assert df.dtypes.iloc[0] == object # we'll need to do this check_list_of_types(object, [str], [StringDtype])