# TODO: moved from tests.indexes.timedeltas.test_arithmetic; needs
# parametrization+de-duplication
+ @pytest.mark.intel
def test_timedelta_ops_with_missing_values(self):
# setup
s1 = pd.to_timedelta(Series(["00:00:01"]))
expected = pd.Series(result, index=["A", "B"])
tm.assert_series_equal(result, expected)
+ @pytest.mark.intel
def test_sum_nanops_timedelta(self):
# prod isn't defined on timedeltas
idx = ["a", "b", "c"]
)
check(df, df2)
+ @pytest.mark.intel
def test_timestamp_compare(self):
# make sure we can compare Timestamps on the right AND left hand side
# GH#4982
result = a.where(do_not_replace, b)
assert_frame_equal(result, expected)
+ @pytest.mark.intel
def test_where_datetime(self):
# GH 3311
list(grouped)
+@pytest.mark.intel
def test_agg_dict_parameter_cast_result_dtypes():
# GH 12821
series[2] = val
assert isna(series[2])
+ @pytest.mark.intel
def test_NaT_cast(self):
# GH10747
result = Series([np.nan]).astype("M8[ns]")
expected = Series([2, 1, 1], index=[5.0, 10.3, np.nan])
tm.assert_series_equal(result, expected)
+ @pytest.mark.intel
def test_value_counts_normalized(self):
# GH12558
s = Series([1, 2, np.nan, np.nan, np.nan])