import numpy as np from pandas import MultiIndex, Series, date_range import pandas._testing as tm def test_xs_datetimelike_wrapping(): # GH#31630 a case where we shouldn't wrap datetime64 in Timestamp arr = date_range("2016-01-01", periods=3)._data._data ser = Series(arr, dtype=object) for i in range(len(ser)): ser.iloc[i] = arr[i] assert ser.dtype == object assert isinstance(ser[0], np.datetime64) result = ser.xs(0) assert isinstance(result, np.datetime64) class TestXSWithMultiIndex: def test_xs_level_series(self, multiindex_dataframe_random_data): df = multiindex_dataframe_random_data ser = df["A"] expected = ser[:, "two"] result = df.xs("two", level=1)["A"] tm.assert_series_equal(result, expected) def test_series_getitem_multiindex_xs_by_label(self): # GH#5684 idx = MultiIndex.from_tuples( [("a", "one"), ("a", "two"), ("b", "one"), ("b", "two")] ) ser = Series([1, 2, 3, 4], index=idx) return_value = ser.index.set_names(["L1", "L2"], inplace=True) assert return_value is None expected = Series([1, 3], index=["a", "b"]) return_value = expected.index.set_names(["L1"], inplace=True) assert return_value is None result = ser.xs("one", level="L2") tm.assert_series_equal(result, expected) def test_series_getitem_multiindex_xs(xs): # GH#6258 dt = list(date_range("20130903", periods=3)) idx = MultiIndex.from_product([list("AB"), dt]) ser = Series([1, 3, 4, 1, 3, 4], index=idx) expected = Series([1, 1], index=list("AB")) result = ser.xs("20130903", level=1) tm.assert_series_equal(result, expected) def test_series_xs_droplevel_false(self): # GH: 19056 mi = MultiIndex.from_tuples( [("a", "x"), ("a", "y"), ("b", "x")], names=["level1", "level2"] ) ser = Series([1, 1, 1], index=mi) result = ser.xs("a", axis=0, drop_level=False) expected = Series( [1, 1], index=MultiIndex.from_tuples( [("a", "x"), ("a", "y")], names=["level1", "level2"] ), ) tm.assert_series_equal(result, expected)