import numpy as np import pytest from pandas.compat import PY311 from pandas.core.dtypes.dtypes import DatetimeTZDtype import pandas as pd from pandas import ( CategoricalIndex, MultiIndex, ) import pandas._testing as tm def assert_matching(actual, expected, check_dtype=False): # avoid specifying internal representation # as much as possible assert len(actual) == len(expected) for act, exp in zip(actual, expected): act = np.asarray(act) exp = np.asarray(exp) tm.assert_numpy_array_equal(act, exp, check_dtype=check_dtype) def test_get_level_number_integer(idx): idx.names = [1, 0] assert idx._get_level_number(1) == 0 assert idx._get_level_number(0) == 1 msg = "Too many levels: Index has only 2 levels, not 3" with pytest.raises(IndexError, match=msg): idx._get_level_number(2) with pytest.raises(KeyError, match="Level fourth not found"): idx._get_level_number("fourth") def test_get_dtypes(): # Test MultiIndex.dtypes (# Gh37062) idx_multitype = MultiIndex.from_product( [[1, 2, 3], ["a", "b", "c"], pd.date_range("20200101", periods=2, tz="UTC")], names=["int", "string", "dt"], ) expected = pd.Series( { "int": np.dtype("int64"), "string": np.dtype("O"), "dt": DatetimeTZDtype(tz="utc"), } ) tm.assert_series_equal(expected, idx_multitype.dtypes) def test_get_dtypes_no_level_name(): # Test MultiIndex.dtypes (# GH38580 ) idx_multitype = MultiIndex.from_product( [ [1, 2, 3], ["a", "b", "c"], pd.date_range("20200101", periods=2, tz="UTC"), ], ) expected = pd.Series( { "level_0": np.dtype("int64"), "level_1": np.dtype("O"), "level_2": DatetimeTZDtype(tz="utc"), } ) tm.assert_series_equal(expected, idx_multitype.dtypes) def test_get_dtypes_duplicate_level_names(): # Test MultiIndex.dtypes with non-unique level names (# GH45174) result = MultiIndex.from_product( [ [1, 2, 3], ["a", "b", "c"], pd.date_range("20200101", periods=2, tz="UTC"), ], names=["A", "A", "A"], ).dtypes expected = pd.Series( [np.dtype("int64"), np.dtype("O"), DatetimeTZDtype(tz="utc")], index=["A", "A", "A"], ) tm.assert_series_equal(result, expected) def test_get_level_number_out_of_bounds(multiindex_dataframe_random_data): frame = multiindex_dataframe_random_data with pytest.raises(IndexError, match="Too many levels"): frame.index._get_level_number(2) with pytest.raises(IndexError, match="not a valid level number"): frame.index._get_level_number(-3) def test_set_name_methods(idx, index_names): # so long as these are synonyms, we don't need to test set_names assert idx.rename == idx.set_names new_names = [name + "SUFFIX" for name in index_names] ind = idx.set_names(new_names) assert idx.names == index_names assert ind.names == new_names msg = "Length of names must match number of levels in MultiIndex" with pytest.raises(ValueError, match=msg): ind.set_names(new_names + new_names) new_names2 = [name + "SUFFIX2" for name in new_names] res = ind.set_names(new_names2, inplace=True) assert res is None assert ind.names == new_names2 # set names for specific level (# GH7792) ind = idx.set_names(new_names[0], level=0) assert idx.names == index_names assert ind.names == [new_names[0], index_names[1]] res = ind.set_names(new_names2[0], level=0, inplace=True) assert res is None assert ind.names == [new_names2[0], index_names[1]] # set names for multiple levels ind = idx.set_names(new_names, level=[0, 1]) assert idx.names == index_names assert ind.names == new_names res = ind.set_names(new_names2, level=[0, 1], inplace=True) assert res is None assert ind.names == new_names2 def test_set_levels_codes_directly(idx): # setting levels/codes directly raises AttributeError levels = idx.levels new_levels = [[lev + "a" for lev in level] for level in levels] codes = idx.codes major_codes, minor_codes = codes major_codes = [(x + 1) % 3 for x in major_codes] minor_codes = [(x + 1) % 1 for x in minor_codes] new_codes = [major_codes, minor_codes] msg = "Can't set attribute" with pytest.raises(AttributeError, match=msg): idx.levels = new_levels msg = ( "property 'codes' of 'MultiIndex' object has no setter" if PY311 else "can't set attribute" ) with pytest.raises(AttributeError, match=msg): idx.codes = new_codes def test_set_levels(idx): # side note - you probably wouldn't want to use levels and codes # directly like this - but it is possible. levels = idx.levels new_levels = [[lev + "a" for lev in level] for level in levels] # level changing [w/o mutation] ind2 = idx.set_levels(new_levels) assert_matching(ind2.levels, new_levels) assert_matching(idx.levels, levels) # level changing specific level [w/o mutation] ind2 = idx.set_levels(new_levels[0], level=0) assert_matching(ind2.levels, [new_levels[0], levels[1]]) assert_matching(idx.levels, levels) ind2 = idx.set_levels(new_levels[1], level=1) assert_matching(ind2.levels, [levels[0], new_levels[1]]) assert_matching(idx.levels, levels) # level changing multiple levels [w/o mutation] ind2 = idx.set_levels(new_levels, level=[0, 1]) assert_matching(ind2.levels, new_levels) assert_matching(idx.levels, levels) # illegal level changing should not change levels # GH 13754 original_index = idx.copy() with pytest.raises(ValueError, match="^On"): idx.set_levels(["c"], level=0) assert_matching(idx.levels, original_index.levels, check_dtype=True) with pytest.raises(ValueError, match="^On"): idx.set_codes([0, 1, 2, 3, 4, 5], level=0) assert_matching(idx.codes, original_index.codes, check_dtype=True) with pytest.raises(TypeError, match="^Levels"): idx.set_levels("c", level=0) assert_matching(idx.levels, original_index.levels, check_dtype=True) with pytest.raises(TypeError, match="^Codes"): idx.set_codes(1, level=0) assert_matching(idx.codes, original_index.codes, check_dtype=True) def test_set_codes(idx): # side note - you probably wouldn't want to use levels and codes # directly like this - but it is possible. codes = idx.codes major_codes, minor_codes = codes major_codes = [(x + 1) % 3 for x in major_codes] minor_codes = [(x + 1) % 1 for x in minor_codes] new_codes = [major_codes, minor_codes] # changing codes w/o mutation ind2 = idx.set_codes(new_codes) assert_matching(ind2.codes, new_codes) assert_matching(idx.codes, codes) # codes changing specific level w/o mutation ind2 = idx.set_codes(new_codes[0], level=0) assert_matching(ind2.codes, [new_codes[0], codes[1]]) assert_matching(idx.codes, codes) ind2 = idx.set_codes(new_codes[1], level=1) assert_matching(ind2.codes, [codes[0], new_codes[1]]) assert_matching(idx.codes, codes) # codes changing multiple levels w/o mutation ind2 = idx.set_codes(new_codes, level=[0, 1]) assert_matching(ind2.codes, new_codes) assert_matching(idx.codes, codes) # label changing for levels of different magnitude of categories ind = MultiIndex.from_tuples([(0, i) for i in range(130)]) new_codes = range(129, -1, -1) expected = MultiIndex.from_tuples([(0, i) for i in new_codes]) # [w/o mutation] result = ind.set_codes(codes=new_codes, level=1) assert result.equals(expected) def test_set_levels_codes_names_bad_input(idx): levels, codes = idx.levels, idx.codes names = idx.names with pytest.raises(ValueError, match="Length of levels"): idx.set_levels([levels[0]]) with pytest.raises(ValueError, match="Length of codes"): idx.set_codes([codes[0]]) with pytest.raises(ValueError, match="Length of names"): idx.set_names([names[0]]) # shouldn't scalar data error, instead should demand list-like with pytest.raises(TypeError, match="list of lists-like"): idx.set_levels(levels[0]) # shouldn't scalar data error, instead should demand list-like with pytest.raises(TypeError, match="list of lists-like"): idx.set_codes(codes[0]) # shouldn't scalar data error, instead should demand list-like with pytest.raises(TypeError, match="list-like"): idx.set_names(names[0]) # should have equal lengths with pytest.raises(TypeError, match="list of lists-like"): idx.set_levels(levels[0], level=[0, 1]) with pytest.raises(TypeError, match="list-like"): idx.set_levels(levels, level=0) # should have equal lengths with pytest.raises(TypeError, match="list of lists-like"): idx.set_codes(codes[0], level=[0, 1]) with pytest.raises(TypeError, match="list-like"): idx.set_codes(codes, level=0) # should have equal lengths with pytest.raises(ValueError, match="Length of names"): idx.set_names(names[0], level=[0, 1]) with pytest.raises(TypeError, match="Names must be a"): idx.set_names(names, level=0) @pytest.mark.parametrize("inplace", [True, False]) def test_set_names_with_nlevel_1(inplace): # GH 21149 # Ensure that .set_names for MultiIndex with # nlevels == 1 does not raise any errors expected = MultiIndex(levels=[[0, 1]], codes=[[0, 1]], names=["first"]) m = MultiIndex.from_product([[0, 1]]) result = m.set_names("first", level=0, inplace=inplace) if inplace: result = m tm.assert_index_equal(result, expected) @pytest.mark.parametrize("ordered", [True, False]) def test_set_levels_categorical(ordered): # GH13854 index = MultiIndex.from_arrays([list("xyzx"), [0, 1, 2, 3]]) cidx = CategoricalIndex(list("bac"), ordered=ordered) result = index.set_levels(cidx, level=0) expected = MultiIndex(levels=[cidx, [0, 1, 2, 3]], codes=index.codes) tm.assert_index_equal(result, expected) result_lvl = result.get_level_values(0) expected_lvl = CategoricalIndex( list("bacb"), categories=cidx.categories, ordered=cidx.ordered ) tm.assert_index_equal(result_lvl, expected_lvl) def test_set_value_keeps_names(): # motivating example from #3742 lev1 = ["hans", "hans", "hans", "grethe", "grethe", "grethe"] lev2 = ["1", "2", "3"] * 2 idx = MultiIndex.from_arrays([lev1, lev2], names=["Name", "Number"]) df = pd.DataFrame( np.random.randn(6, 4), columns=["one", "two", "three", "four"], index=idx ) df = df.sort_index() assert df._is_copy is None assert df.index.names == ("Name", "Number") df.at[("grethe", "4"), "one"] = 99.34 assert df._is_copy is None assert df.index.names == ("Name", "Number") def test_set_levels_with_iterable(): # GH23273 sizes = [1, 2, 3] colors = ["black"] * 3 index = MultiIndex.from_arrays([sizes, colors], names=["size", "color"]) result = index.set_levels(map(int, ["3", "2", "1"]), level="size") expected_sizes = [3, 2, 1] expected = MultiIndex.from_arrays([expected_sizes, colors], names=["size", "color"]) tm.assert_index_equal(result, expected) def test_set_empty_level(): # GH#48636 midx = MultiIndex.from_arrays([[]], names=["A"]) result = midx.set_levels(pd.DatetimeIndex([]), level=0) expected = MultiIndex.from_arrays([pd.DatetimeIndex([])], names=["A"]) tm.assert_index_equal(result, expected) def test_set_levels_pos_args_removal(): # https://github.com/pandas-dev/pandas/issues/41485 idx = MultiIndex.from_tuples( [ (1, "one"), (3, "one"), ], names=["foo", "bar"], ) with pytest.raises(TypeError, match="positional arguments"): idx.set_levels(["a", "b", "c"], 0) with pytest.raises(TypeError, match="positional arguments"): idx.set_codes([[0, 1], [1, 0]], 0)