import numpy as np
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import pytest
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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_reindex(idx):
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result, indexer = idx.reindex(list(idx[:4]))
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assert isinstance(result, MultiIndex)
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assert result.names == ["first", "second"]
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assert [level.name for level in result.levels] == ["first", "second"]
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result, indexer = idx.reindex(list(idx))
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assert isinstance(result, MultiIndex)
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assert indexer is None
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assert result.names == ["first", "second"]
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assert [level.name for level in result.levels] == ["first", "second"]
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def test_reindex_level(idx):
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index = Index(["one"])
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target, indexer = idx.reindex(index, level="second")
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target2, indexer2 = index.reindex(idx, level="second")
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exp_index = idx.join(index, level="second", how="right")
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exp_index2 = idx.join(index, level="second", how="left")
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assert target.equals(exp_index)
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exp_indexer = np.array([0, 2, 4])
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tm.assert_numpy_array_equal(indexer, exp_indexer, check_dtype=False)
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assert target2.equals(exp_index2)
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exp_indexer2 = np.array([0, -1, 0, -1, 0, -1])
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tm.assert_numpy_array_equal(indexer2, exp_indexer2, check_dtype=False)
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with pytest.raises(TypeError, match="Fill method not supported"):
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idx.reindex(idx, method="pad", level="second")
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def test_reindex_preserves_names_when_target_is_list_or_ndarray(idx):
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# GH6552
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idx = idx.copy()
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target = idx.copy()
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idx.names = target.names = [None, None]
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other_dtype = MultiIndex.from_product([[1, 2], [3, 4]])
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# list & ndarray cases
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assert idx.reindex([])[0].names == [None, None]
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assert idx.reindex(np.array([]))[0].names == [None, None]
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assert idx.reindex(target.tolist())[0].names == [None, None]
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assert idx.reindex(target.values)[0].names == [None, None]
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assert idx.reindex(other_dtype.tolist())[0].names == [None, None]
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assert idx.reindex(other_dtype.values)[0].names == [None, None]
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idx.names = ["foo", "bar"]
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assert idx.reindex([])[0].names == ["foo", "bar"]
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assert idx.reindex(np.array([]))[0].names == ["foo", "bar"]
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assert idx.reindex(target.tolist())[0].names == ["foo", "bar"]
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assert idx.reindex(target.values)[0].names == ["foo", "bar"]
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assert idx.reindex(other_dtype.tolist())[0].names == ["foo", "bar"]
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assert idx.reindex(other_dtype.values)[0].names == ["foo", "bar"]
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def test_reindex_lvl_preserves_names_when_target_is_list_or_array():
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# GH7774
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idx = MultiIndex.from_product([[0, 1], ["a", "b"]], names=["foo", "bar"])
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assert idx.reindex([], level=0)[0].names == ["foo", "bar"]
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assert idx.reindex([], level=1)[0].names == ["foo", "bar"]
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def test_reindex_lvl_preserves_type_if_target_is_empty_list_or_array():
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# GH7774
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idx = MultiIndex.from_product([[0, 1], ["a", "b"]])
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assert idx.reindex([], level=0)[0].levels[0].dtype.type == np.int64
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assert idx.reindex([], level=1)[0].levels[1].dtype.type == np.object_
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# case with EA levels
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cat = pd.Categorical(["foo", "bar"])
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dti = pd.date_range("2016-01-01", periods=2, tz="US/Pacific")
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mi = MultiIndex.from_product([cat, dti])
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assert mi.reindex([], level=0)[0].levels[0].dtype == cat.dtype
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assert mi.reindex([], level=1)[0].levels[1].dtype == dti.dtype
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def test_reindex_base(idx):
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expected = np.arange(idx.size, dtype=np.intp)
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actual = idx.get_indexer(idx)
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tm.assert_numpy_array_equal(expected, actual)
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with pytest.raises(ValueError, match="Invalid fill method"):
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idx.get_indexer(idx, method="invalid")
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def test_reindex_non_unique():
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idx = MultiIndex.from_tuples([(0, 0), (1, 1), (1, 1), (2, 2)])
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a = pd.Series(np.arange(4), index=idx)
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new_idx = MultiIndex.from_tuples([(0, 0), (1, 1), (2, 2)])
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msg = "cannot handle a non-unique multi-index!"
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with pytest.raises(ValueError, match=msg):
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a.reindex(new_idx)
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@pytest.mark.parametrize("values", [[["a"], ["x"]], [[], []]])
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def test_reindex_empty_with_level(values):
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# GH41170
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idx = MultiIndex.from_arrays(values)
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result, result_indexer = idx.reindex(np.array(["b"]), level=0)
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expected = MultiIndex(levels=[["b"], values[1]], codes=[[], []])
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expected_indexer = np.array([], dtype=result_indexer.dtype)
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tm.assert_index_equal(result, expected)
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tm.assert_numpy_array_equal(result_indexer, expected_indexer)
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def test_reindex_not_all_tuples():
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keys = [("i", "i"), ("i", "j"), ("j", "i"), "j"]
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mi = MultiIndex.from_tuples(keys[:-1])
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idx = Index(keys)
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res, indexer = mi.reindex(idx)
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tm.assert_index_equal(res, idx)
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expected = np.array([0, 1, 2, -1], dtype=np.intp)
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tm.assert_numpy_array_equal(indexer, expected)
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def test_reindex_limit_arg_with_multiindex():
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# GH21247
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idx = MultiIndex.from_tuples([(3, "A"), (4, "A"), (4, "B")])
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df = pd.Series([0.02, 0.01, 0.012], index=idx)
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new_idx = MultiIndex.from_tuples(
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[
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(3, "A"),
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(3, "B"),
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(4, "A"),
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(4, "B"),
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(4, "C"),
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(5, "B"),
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(5, "C"),
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(6, "B"),
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(6, "C"),
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]
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)
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with pytest.raises(
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ValueError,
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match="limit argument only valid if doing pad, backfill or nearest reindexing",
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):
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df.reindex(new_idx, fill_value=0, limit=1)
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def test_reindex_with_none_in_nested_multiindex():
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# GH42883
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index = MultiIndex.from_tuples([(("a", None), 1), (("b", None), 2)])
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index2 = MultiIndex.from_tuples([(("b", None), 2), (("a", None), 1)])
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df1_dtype = pd.DataFrame([1, 2], index=index)
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df2_dtype = pd.DataFrame([2, 1], index=index2)
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result = df1_dtype.reindex_like(df2_dtype)
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expected = df2_dtype
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tm.assert_frame_equal(result, expected)
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