import numpy as np import pytest from pandas import MultiIndex import pandas._testing as tm def test_numeric_compat(idx): with pytest.raises(TypeError, match="cannot perform __mul__"): idx * 1 with pytest.raises(TypeError, match="cannot perform __rmul__"): 1 * idx div_err = "cannot perform __truediv__" with pytest.raises(TypeError, match=div_err): idx / 1 div_err = div_err.replace(" __", " __r") with pytest.raises(TypeError, match=div_err): 1 / idx with pytest.raises(TypeError, match="cannot perform __floordiv__"): idx // 1 with pytest.raises(TypeError, match="cannot perform __rfloordiv__"): 1 // idx @pytest.mark.parametrize("method", ["all", "any"]) def test_logical_compat(idx, method): msg = f"cannot perform {method}" with pytest.raises(TypeError, match=msg): getattr(idx, method)() def test_boolean_context_compat(idx): msg = ( "The truth value of a MultiIndex is ambiguous. " r"Use a.empty, a.bool\(\), a.item\(\), a.any\(\) or a.all\(\)." ) with pytest.raises(ValueError, match=msg): bool(idx) def test_boolean_context_compat2(): # boolean context compat # GH7897 i1 = MultiIndex.from_tuples([("A", 1), ("A", 2)]) i2 = MultiIndex.from_tuples([("A", 1), ("A", 3)]) common = i1.intersection(i2) msg = ( r"The truth value of a MultiIndex is ambiguous\. " r"Use a\.empty, a\.bool\(\), a\.item\(\), a\.any\(\) or a\.all\(\)\." ) with pytest.raises(ValueError, match=msg): bool(common) def test_inplace_mutation_resets_values(): levels = [["a", "b", "c"], [4]] levels2 = [[1, 2, 3], ["a"]] codes = [[0, 1, 0, 2, 2, 0], [0, 0, 0, 0, 0, 0]] mi1 = MultiIndex(levels=levels, codes=codes) mi2 = MultiIndex(levels=levels2, codes=codes) # instantiating MultiIndex should not access/cache _.values assert "_values" not in mi1._cache assert "_values" not in mi2._cache vals = mi1.values.copy() vals2 = mi2.values.copy() # accessing .values should cache ._values assert mi1._values is mi1._cache["_values"] assert mi1.values is mi1._cache["_values"] assert isinstance(mi1._cache["_values"], np.ndarray) # Make sure level setting works new_vals = mi1.set_levels(levels2).values tm.assert_almost_equal(vals2, new_vals) # Non-inplace doesn't drop _values from _cache [implementation detail] tm.assert_almost_equal(mi1._cache["_values"], vals) # ...and values is still same too tm.assert_almost_equal(mi1.values, vals) # Inplace should drop _values from _cache with tm.assert_produces_warning(FutureWarning): mi1.set_levels(levels2, inplace=True) assert "_values" not in mi1._cache tm.assert_almost_equal(mi1.values, vals2) # Make sure label setting works too codes2 = [[0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0]] exp_values = np.empty((6,), dtype=object) exp_values[:] = [(1, "a")] * 6 # Must be 1d array of tuples assert exp_values.shape == (6,) new_mi = mi2.set_codes(codes2) assert "_values" not in new_mi._cache new_values = new_mi.values assert "_values" in new_mi._cache # Not inplace shouldn't change tm.assert_almost_equal(mi2._cache["_values"], vals2) # Should have correct values tm.assert_almost_equal(exp_values, new_values) # ...and again setting inplace should drop _values from _cache, etc with tm.assert_produces_warning(FutureWarning): mi2.set_codes(codes2, inplace=True) assert "_values" not in mi2._cache tm.assert_almost_equal(mi2.values, new_values) assert "_values" in mi2._cache def test_ndarray_compat_properties(idx, compat_props): assert idx.T.equals(idx) assert idx.transpose().equals(idx) values = idx.values for prop in compat_props: assert getattr(idx, prop) == getattr(values, prop) # test for validity idx.nbytes idx.values.nbytes def test_pickle_compat_construction(): # this is testing for pickle compat # need an object to create with with pytest.raises(TypeError, match="Must pass both levels and codes"): MultiIndex()