import warnings
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import numpy as np
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import pytest
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from pandas.errors import PerformanceWarning
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import pandas as pd
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from pandas import (
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Index,
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MultiIndex,
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)
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import pandas._testing as tm
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def test_drop(idx):
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dropped = idx.drop([("foo", "two"), ("qux", "one")])
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index = MultiIndex.from_tuples([("foo", "two"), ("qux", "one")])
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dropped2 = idx.drop(index)
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expected = idx[[0, 2, 3, 5]]
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tm.assert_index_equal(dropped, expected)
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tm.assert_index_equal(dropped2, expected)
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dropped = idx.drop(["bar"])
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expected = idx[[0, 1, 3, 4, 5]]
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tm.assert_index_equal(dropped, expected)
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dropped = idx.drop("foo")
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expected = idx[[2, 3, 4, 5]]
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tm.assert_index_equal(dropped, expected)
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index = MultiIndex.from_tuples([("bar", "two")])
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with pytest.raises(KeyError, match=r"^15$"):
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idx.drop([("bar", "two")])
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with pytest.raises(KeyError, match=r"^15$"):
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idx.drop(index)
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with pytest.raises(KeyError, match=r"^'two'$"):
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idx.drop(["foo", "two"])
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# partially correct argument
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mixed_index = MultiIndex.from_tuples([("qux", "one"), ("bar", "two")])
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with pytest.raises(KeyError, match=r"^15$"):
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idx.drop(mixed_index)
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# error='ignore'
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dropped = idx.drop(index, errors="ignore")
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expected = idx[[0, 1, 2, 3, 4, 5]]
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tm.assert_index_equal(dropped, expected)
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dropped = idx.drop(mixed_index, errors="ignore")
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expected = idx[[0, 1, 2, 3, 5]]
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tm.assert_index_equal(dropped, expected)
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dropped = idx.drop(["foo", "two"], errors="ignore")
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expected = idx[[2, 3, 4, 5]]
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tm.assert_index_equal(dropped, expected)
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# mixed partial / full drop
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dropped = idx.drop(["foo", ("qux", "one")])
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expected = idx[[2, 3, 5]]
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tm.assert_index_equal(dropped, expected)
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# mixed partial / full drop / error='ignore'
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mixed_index = ["foo", ("qux", "one"), "two"]
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with pytest.raises(KeyError, match=r"^'two'$"):
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idx.drop(mixed_index)
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dropped = idx.drop(mixed_index, errors="ignore")
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expected = idx[[2, 3, 5]]
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tm.assert_index_equal(dropped, expected)
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def test_droplevel_with_names(idx):
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index = idx[idx.get_loc("foo")]
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dropped = index.droplevel(0)
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assert dropped.name == "second"
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index = MultiIndex(
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levels=[Index(range(4)), Index(range(4)), Index(range(4))],
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codes=[
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np.array([0, 0, 1, 2, 2, 2, 3, 3]),
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np.array([0, 1, 0, 0, 0, 1, 0, 1]),
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np.array([1, 0, 1, 1, 0, 0, 1, 0]),
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],
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names=["one", "two", "three"],
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)
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dropped = index.droplevel(0)
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assert dropped.names == ("two", "three")
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dropped = index.droplevel("two")
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expected = index.droplevel(1)
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assert dropped.equals(expected)
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def test_droplevel_list():
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index = MultiIndex(
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levels=[Index(range(4)), Index(range(4)), Index(range(4))],
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codes=[
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np.array([0, 0, 1, 2, 2, 2, 3, 3]),
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np.array([0, 1, 0, 0, 0, 1, 0, 1]),
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np.array([1, 0, 1, 1, 0, 0, 1, 0]),
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],
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names=["one", "two", "three"],
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)
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dropped = index[:2].droplevel(["three", "one"])
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expected = index[:2].droplevel(2).droplevel(0)
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assert dropped.equals(expected)
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dropped = index[:2].droplevel([])
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expected = index[:2]
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assert dropped.equals(expected)
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msg = (
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"Cannot remove 3 levels from an index with 3 levels: "
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"at least one level must be left"
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)
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with pytest.raises(ValueError, match=msg):
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index[:2].droplevel(["one", "two", "three"])
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with pytest.raises(KeyError, match="'Level four not found'"):
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index[:2].droplevel(["one", "four"])
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def test_drop_not_lexsorted():
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# GH 12078
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# define the lexsorted version of the multi-index
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tuples = [("a", ""), ("b1", "c1"), ("b2", "c2")]
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lexsorted_mi = MultiIndex.from_tuples(tuples, names=["b", "c"])
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assert lexsorted_mi._is_lexsorted()
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# and the not-lexsorted version
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df = pd.DataFrame(
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columns=["a", "b", "c", "d"], data=[[1, "b1", "c1", 3], [1, "b2", "c2", 4]]
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)
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df = df.pivot_table(index="a", columns=["b", "c"], values="d")
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df = df.reset_index()
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not_lexsorted_mi = df.columns
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assert not not_lexsorted_mi._is_lexsorted()
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# compare the results
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tm.assert_index_equal(lexsorted_mi, not_lexsorted_mi)
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with tm.assert_produces_warning(PerformanceWarning):
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tm.assert_index_equal(lexsorted_mi.drop("a"), not_lexsorted_mi.drop("a"))
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def test_drop_with_nan_in_index(nulls_fixture):
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# GH#18853
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mi = MultiIndex.from_tuples([("blah", nulls_fixture)], names=["name", "date"])
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msg = r"labels \[Timestamp\('2001-01-01 00:00:00'\)\] not found in level"
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with pytest.raises(KeyError, match=msg):
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mi.drop(pd.Timestamp("2001"), level="date")
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def test_drop_with_non_monotonic_duplicates():
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# GH#33494
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mi = MultiIndex.from_tuples([(1, 2), (2, 3), (1, 2)])
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with warnings.catch_warnings():
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warnings.simplefilter("ignore", PerformanceWarning)
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result = mi.drop((1, 2))
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expected = MultiIndex.from_tuples([(2, 3)])
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tm.assert_index_equal(result, expected)
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def test_single_level_drop_partially_missing_elements():
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# GH 37820
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mi = MultiIndex.from_tuples([(1, 2), (2, 2), (3, 2)])
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msg = r"labels \[4\] not found in level"
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with pytest.raises(KeyError, match=msg):
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mi.drop(4, level=0)
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with pytest.raises(KeyError, match=msg):
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mi.drop([1, 4], level=0)
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msg = r"labels \[nan\] not found in level"
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with pytest.raises(KeyError, match=msg):
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mi.drop([np.nan], level=0)
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with pytest.raises(KeyError, match=msg):
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mi.drop([np.nan, 1, 2, 3], level=0)
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mi = MultiIndex.from_tuples([(np.nan, 1), (1, 2)])
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msg = r"labels \['a'\] not found in level"
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with pytest.raises(KeyError, match=msg):
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mi.drop([np.nan, 1, "a"], level=0)
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def test_droplevel_multiindex_one_level():
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# GH#37208
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index = MultiIndex.from_tuples([(2,)], names=("b",))
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result = index.droplevel([])
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expected = Index([2], name="b")
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tm.assert_index_equal(result, expected)
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