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| import numpy as np
| import pytest
|
| import pandas as pd
| from pandas import (
| Index,
| MultiIndex,
| date_range,
| period_range,
| )
| import pandas._testing as tm
|
|
| def test_infer_objects(idx):
| with pytest.raises(NotImplementedError, match="to_frame"):
| idx.infer_objects()
|
|
| def test_shift(idx):
| # GH8083 test the base class for shift
| msg = (
| "This method is only implemented for DatetimeIndex, PeriodIndex and "
| "TimedeltaIndex; Got type MultiIndex"
| )
| with pytest.raises(NotImplementedError, match=msg):
| idx.shift(1)
| with pytest.raises(NotImplementedError, match=msg):
| idx.shift(1, 2)
|
|
| def test_groupby(idx):
| groups = idx.groupby(np.array([1, 1, 1, 2, 2, 2]))
| labels = idx.tolist()
| exp = {1: labels[:3], 2: labels[3:]}
| tm.assert_dict_equal(groups, exp)
|
| # GH5620
| groups = idx.groupby(idx)
| exp = {key: [key] for key in idx}
| tm.assert_dict_equal(groups, exp)
|
|
| def test_truncate_multiindex():
| # GH 34564 for MultiIndex level names check
| major_axis = Index(list(range(4)))
| minor_axis = Index(list(range(2)))
|
| major_codes = np.array([0, 0, 1, 2, 3, 3])
| minor_codes = np.array([0, 1, 0, 1, 0, 1])
|
| index = MultiIndex(
| levels=[major_axis, minor_axis],
| codes=[major_codes, minor_codes],
| names=["L1", "L2"],
| )
|
| result = index.truncate(before=1)
| assert "foo" not in result.levels[0]
| assert 1 in result.levels[0]
| assert index.names == result.names
|
| result = index.truncate(after=1)
| assert 2 not in result.levels[0]
| assert 1 in result.levels[0]
| assert index.names == result.names
|
| result = index.truncate(before=1, after=2)
| assert len(result.levels[0]) == 2
| assert index.names == result.names
|
| msg = "after < before"
| with pytest.raises(ValueError, match=msg):
| index.truncate(3, 1)
|
|
| # TODO: reshape
|
|
| def test_reorder_levels(idx):
| # this blows up
| with pytest.raises(IndexError, match="^Too many levels"):
| idx.reorder_levels([2, 1, 0])
|
|
| def test_numpy_repeat():
| reps = 2
| numbers = [1, 2, 3]
| names = np.array(["foo", "bar"])
|
| m = MultiIndex.from_product([numbers, names], names=names)
| expected = MultiIndex.from_product([numbers, names.repeat(reps)], names=names)
| tm.assert_index_equal(np.repeat(m, reps), expected)
|
| msg = "the 'axis' parameter is not supported"
| with pytest.raises(ValueError, match=msg):
| np.repeat(m, reps, axis=1)
|
|
| def test_append_mixed_dtypes():
| # GH 13660
| dti = date_range("2011-01-01", freq="M", periods=3)
| dti_tz = date_range("2011-01-01", freq="M", periods=3, tz="US/Eastern")
| pi = period_range("2011-01", freq="M", periods=3)
|
| mi = MultiIndex.from_arrays(
| [[1, 2, 3], [1.1, np.nan, 3.3], ["a", "b", "c"], dti, dti_tz, pi]
| )
| assert mi.nlevels == 6
|
| res = mi.append(mi)
| exp = MultiIndex.from_arrays(
| [
| [1, 2, 3, 1, 2, 3],
| [1.1, np.nan, 3.3, 1.1, np.nan, 3.3],
| ["a", "b", "c", "a", "b", "c"],
| dti.append(dti),
| dti_tz.append(dti_tz),
| pi.append(pi),
| ]
| )
| tm.assert_index_equal(res, exp)
|
| other = MultiIndex.from_arrays(
| [
| ["x", "y", "z"],
| ["x", "y", "z"],
| ["x", "y", "z"],
| ["x", "y", "z"],
| ["x", "y", "z"],
| ["x", "y", "z"],
| ]
| )
|
| res = mi.append(other)
| exp = MultiIndex.from_arrays(
| [
| [1, 2, 3, "x", "y", "z"],
| [1.1, np.nan, 3.3, "x", "y", "z"],
| ["a", "b", "c", "x", "y", "z"],
| dti.append(Index(["x", "y", "z"])),
| dti_tz.append(Index(["x", "y", "z"])),
| pi.append(Index(["x", "y", "z"])),
| ]
| )
| tm.assert_index_equal(res, exp)
|
|
| def test_iter(idx):
| result = list(idx)
| expected = [
| ("foo", "one"),
| ("foo", "two"),
| ("bar", "one"),
| ("baz", "two"),
| ("qux", "one"),
| ("qux", "two"),
| ]
| assert result == expected
|
|
| def test_sub(idx):
| first = idx
|
| # - now raises (previously was set op difference)
| msg = "cannot perform __sub__ with this index type: MultiIndex"
| with pytest.raises(TypeError, match=msg):
| first - idx[-3:]
| with pytest.raises(TypeError, match=msg):
| idx[-3:] - first
| with pytest.raises(TypeError, match=msg):
| idx[-3:] - first.tolist()
| msg = "cannot perform __rsub__ with this index type: MultiIndex"
| with pytest.raises(TypeError, match=msg):
| first.tolist() - idx[-3:]
|
|
| def test_map(idx):
| # callable
| index = idx
|
| result = index.map(lambda x: x)
| tm.assert_index_equal(result, index)
|
|
| @pytest.mark.parametrize(
| "mapper",
| [
| lambda values, idx: {i: e for e, i in zip(values, idx)},
| lambda values, idx: pd.Series(values, idx),
| ],
| )
| def test_map_dictlike(idx, mapper):
| identity = mapper(idx.values, idx)
|
| # we don't infer to uint64 dtype for a dict
| if idx.dtype == np.uint64 and isinstance(identity, dict):
| expected = idx.astype("int64")
| else:
| expected = idx
|
| result = idx.map(identity)
| tm.assert_index_equal(result, expected)
|
| # empty mappable
| expected = Index([np.nan] * len(idx))
| result = idx.map(mapper(expected, idx))
| tm.assert_index_equal(result, expected)
|
|
| @pytest.mark.parametrize(
| "func",
| [
| np.exp,
| np.exp2,
| np.expm1,
| np.log,
| np.log2,
| np.log10,
| np.log1p,
| np.sqrt,
| np.sin,
| np.cos,
| np.tan,
| np.arcsin,
| np.arccos,
| np.arctan,
| np.sinh,
| np.cosh,
| np.tanh,
| np.arcsinh,
| np.arccosh,
| np.arctanh,
| np.deg2rad,
| np.rad2deg,
| ],
| ids=lambda func: func.__name__,
| )
| def test_numpy_ufuncs(idx, func):
| # test ufuncs of numpy. see:
| # https://numpy.org/doc/stable/reference/ufuncs.html
|
| expected_exception = TypeError
| msg = (
| "loop of ufunc does not support argument 0 of type tuple which "
| f"has no callable {func.__name__} method"
| )
| with pytest.raises(expected_exception, match=msg):
| func(idx)
|
|
| @pytest.mark.parametrize(
| "func",
| [np.isfinite, np.isinf, np.isnan, np.signbit],
| ids=lambda func: func.__name__,
| )
| def test_numpy_type_funcs(idx, func):
| msg = (
| f"ufunc '{func.__name__}' not supported for the input types, and the inputs "
| "could not be safely coerced to any supported types according to "
| "the casting rule ''safe''"
| )
| with pytest.raises(TypeError, match=msg):
| func(idx)
|
|
