import numpy as np
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import pytest
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from pandas.errors import InvalidIndexError
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import pandas as pd
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from pandas import (
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CategoricalIndex,
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Index,
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IntervalIndex,
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Timestamp,
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)
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import pandas._testing as tm
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class TestTake:
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def test_take_fill_value(self):
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# GH 12631
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# numeric category
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idx = CategoricalIndex([1, 2, 3], name="xxx")
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result = idx.take(np.array([1, 0, -1]))
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expected = CategoricalIndex([2, 1, 3], name="xxx")
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tm.assert_index_equal(result, expected)
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tm.assert_categorical_equal(result.values, expected.values)
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# fill_value
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result = idx.take(np.array([1, 0, -1]), fill_value=True)
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expected = CategoricalIndex([2, 1, np.nan], categories=[1, 2, 3], name="xxx")
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tm.assert_index_equal(result, expected)
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tm.assert_categorical_equal(result.values, expected.values)
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# allow_fill=False
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result = idx.take(np.array([1, 0, -1]), allow_fill=False, fill_value=True)
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expected = CategoricalIndex([2, 1, 3], name="xxx")
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tm.assert_index_equal(result, expected)
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tm.assert_categorical_equal(result.values, expected.values)
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# object category
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idx = CategoricalIndex(
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list("CBA"), categories=list("ABC"), ordered=True, name="xxx"
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)
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result = idx.take(np.array([1, 0, -1]))
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expected = CategoricalIndex(
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list("BCA"), categories=list("ABC"), ordered=True, name="xxx"
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)
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tm.assert_index_equal(result, expected)
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tm.assert_categorical_equal(result.values, expected.values)
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# fill_value
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result = idx.take(np.array([1, 0, -1]), fill_value=True)
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expected = CategoricalIndex(
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["B", "C", np.nan], categories=list("ABC"), ordered=True, name="xxx"
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)
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tm.assert_index_equal(result, expected)
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tm.assert_categorical_equal(result.values, expected.values)
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# allow_fill=False
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result = idx.take(np.array([1, 0, -1]), allow_fill=False, fill_value=True)
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expected = CategoricalIndex(
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list("BCA"), categories=list("ABC"), ordered=True, name="xxx"
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)
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tm.assert_index_equal(result, expected)
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tm.assert_categorical_equal(result.values, expected.values)
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msg = (
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"When allow_fill=True and fill_value is not None, "
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"all indices must be >= -1"
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)
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with pytest.raises(ValueError, match=msg):
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idx.take(np.array([1, 0, -2]), fill_value=True)
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with pytest.raises(ValueError, match=msg):
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idx.take(np.array([1, 0, -5]), fill_value=True)
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msg = "index -5 is out of bounds for (axis 0 with )?size 3"
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with pytest.raises(IndexError, match=msg):
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idx.take(np.array([1, -5]))
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def test_take_fill_value_datetime(self):
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# datetime category
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idx = pd.DatetimeIndex(["2011-01-01", "2011-02-01", "2011-03-01"], name="xxx")
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idx = CategoricalIndex(idx)
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result = idx.take(np.array([1, 0, -1]))
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expected = pd.DatetimeIndex(
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["2011-02-01", "2011-01-01", "2011-03-01"], name="xxx"
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)
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expected = CategoricalIndex(expected)
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tm.assert_index_equal(result, expected)
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# fill_value
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result = idx.take(np.array([1, 0, -1]), fill_value=True)
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expected = pd.DatetimeIndex(["2011-02-01", "2011-01-01", "NaT"], name="xxx")
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exp_cats = pd.DatetimeIndex(["2011-01-01", "2011-02-01", "2011-03-01"])
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expected = CategoricalIndex(expected, categories=exp_cats)
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tm.assert_index_equal(result, expected)
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# allow_fill=False
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result = idx.take(np.array([1, 0, -1]), allow_fill=False, fill_value=True)
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expected = pd.DatetimeIndex(
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["2011-02-01", "2011-01-01", "2011-03-01"], name="xxx"
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)
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expected = CategoricalIndex(expected)
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tm.assert_index_equal(result, expected)
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msg = (
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"When allow_fill=True and fill_value is not None, "
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"all indices must be >= -1"
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)
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with pytest.raises(ValueError, match=msg):
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idx.take(np.array([1, 0, -2]), fill_value=True)
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with pytest.raises(ValueError, match=msg):
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idx.take(np.array([1, 0, -5]), fill_value=True)
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msg = "index -5 is out of bounds for (axis 0 with )?size 3"
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with pytest.raises(IndexError, match=msg):
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idx.take(np.array([1, -5]))
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def test_take_invalid_kwargs(self):
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idx = CategoricalIndex([1, 2, 3], name="foo")
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indices = [1, 0, -1]
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msg = r"take\(\) got an unexpected keyword argument 'foo'"
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with pytest.raises(TypeError, match=msg):
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idx.take(indices, foo=2)
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msg = "the 'out' parameter is not supported"
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with pytest.raises(ValueError, match=msg):
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idx.take(indices, out=indices)
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msg = "the 'mode' parameter is not supported"
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with pytest.raises(ValueError, match=msg):
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idx.take(indices, mode="clip")
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class TestGetLoc:
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def test_get_loc(self):
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# GH 12531
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cidx1 = CategoricalIndex(list("abcde"), categories=list("edabc"))
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idx1 = Index(list("abcde"))
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assert cidx1.get_loc("a") == idx1.get_loc("a")
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assert cidx1.get_loc("e") == idx1.get_loc("e")
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for i in [cidx1, idx1]:
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with pytest.raises(KeyError, match="'NOT-EXIST'"):
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i.get_loc("NOT-EXIST")
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# non-unique
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cidx2 = CategoricalIndex(list("aacded"), categories=list("edabc"))
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idx2 = Index(list("aacded"))
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# results in bool array
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res = cidx2.get_loc("d")
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tm.assert_numpy_array_equal(res, idx2.get_loc("d"))
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tm.assert_numpy_array_equal(
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res, np.array([False, False, False, True, False, True])
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)
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# unique element results in scalar
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res = cidx2.get_loc("e")
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assert res == idx2.get_loc("e")
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assert res == 4
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for i in [cidx2, idx2]:
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with pytest.raises(KeyError, match="'NOT-EXIST'"):
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i.get_loc("NOT-EXIST")
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# non-unique, sliceable
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cidx3 = CategoricalIndex(list("aabbb"), categories=list("abc"))
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idx3 = Index(list("aabbb"))
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# results in slice
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res = cidx3.get_loc("a")
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assert res == idx3.get_loc("a")
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assert res == slice(0, 2, None)
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res = cidx3.get_loc("b")
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assert res == idx3.get_loc("b")
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assert res == slice(2, 5, None)
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for i in [cidx3, idx3]:
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with pytest.raises(KeyError, match="'c'"):
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i.get_loc("c")
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def test_get_loc_unique(self):
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cidx = CategoricalIndex(list("abc"))
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result = cidx.get_loc("b")
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assert result == 1
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def test_get_loc_monotonic_nonunique(self):
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cidx = CategoricalIndex(list("abbc"))
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result = cidx.get_loc("b")
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expected = slice(1, 3, None)
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assert result == expected
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def test_get_loc_nonmonotonic_nonunique(self):
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cidx = CategoricalIndex(list("abcb"))
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result = cidx.get_loc("b")
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expected = np.array([False, True, False, True], dtype=bool)
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tm.assert_numpy_array_equal(result, expected)
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def test_get_loc_nan(self):
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# GH#41933
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ci = CategoricalIndex(["A", "B", np.nan])
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res = ci.get_loc(np.nan)
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assert res == 2
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class TestGetIndexer:
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def test_get_indexer_base(self):
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# Determined by cat ordering.
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idx = CategoricalIndex(list("cab"), categories=list("cab"))
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expected = np.arange(len(idx), 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_get_indexer_requires_unique(self):
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np.random.seed(123456789)
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ci = CategoricalIndex(list("aabbca"), categories=list("cab"), ordered=False)
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oidx = Index(np.array(ci))
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msg = "Reindexing only valid with uniquely valued Index objects"
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for n in [1, 2, 5, len(ci)]:
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finder = oidx[np.random.randint(0, len(ci), size=n)]
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with pytest.raises(InvalidIndexError, match=msg):
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ci.get_indexer(finder)
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# see gh-17323
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#
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# Even when indexer is equal to the
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# members in the index, we should
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# respect duplicates instead of taking
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# the fast-track path.
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for finder in [list("aabbca"), list("aababca")]:
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with pytest.raises(InvalidIndexError, match=msg):
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ci.get_indexer(finder)
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def test_get_indexer_non_unique(self):
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idx1 = CategoricalIndex(list("aabcde"), categories=list("edabc"))
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idx2 = CategoricalIndex(list("abf"))
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for indexer in [idx2, list("abf"), Index(list("abf"))]:
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msg = "Reindexing only valid with uniquely valued Index objects"
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with pytest.raises(InvalidIndexError, match=msg):
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idx1.get_indexer(indexer)
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r1, _ = idx1.get_indexer_non_unique(indexer)
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expected = np.array([0, 1, 2, -1], dtype=np.intp)
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tm.assert_almost_equal(r1, expected)
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def test_get_indexer_method(self):
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idx1 = CategoricalIndex(list("aabcde"), categories=list("edabc"))
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idx2 = CategoricalIndex(list("abf"))
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msg = "method pad not yet implemented for CategoricalIndex"
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with pytest.raises(NotImplementedError, match=msg):
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idx2.get_indexer(idx1, method="pad")
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msg = "method backfill not yet implemented for CategoricalIndex"
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with pytest.raises(NotImplementedError, match=msg):
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idx2.get_indexer(idx1, method="backfill")
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msg = "method nearest not yet implemented for CategoricalIndex"
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with pytest.raises(NotImplementedError, match=msg):
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idx2.get_indexer(idx1, method="nearest")
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def test_get_indexer_array(self):
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arr = np.array(
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[Timestamp("1999-12-31 00:00:00"), Timestamp("2000-12-31 00:00:00")],
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dtype=object,
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)
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cats = [Timestamp("1999-12-31 00:00:00"), Timestamp("2000-12-31 00:00:00")]
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ci = CategoricalIndex(cats, categories=cats, ordered=False, dtype="category")
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result = ci.get_indexer(arr)
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expected = np.array([0, 1], dtype="intp")
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tm.assert_numpy_array_equal(result, expected)
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def test_get_indexer_same_categories_same_order(self):
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ci = CategoricalIndex(["a", "b"], categories=["a", "b"])
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result = ci.get_indexer(CategoricalIndex(["b", "b"], categories=["a", "b"]))
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expected = np.array([1, 1], dtype="intp")
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tm.assert_numpy_array_equal(result, expected)
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def test_get_indexer_same_categories_different_order(self):
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# https://github.com/pandas-dev/pandas/issues/19551
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ci = CategoricalIndex(["a", "b"], categories=["a", "b"])
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result = ci.get_indexer(CategoricalIndex(["b", "b"], categories=["b", "a"]))
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expected = np.array([1, 1], dtype="intp")
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tm.assert_numpy_array_equal(result, expected)
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def test_get_indexer_nans_in_index_and_target(self):
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# GH 45361
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ci = CategoricalIndex([1, 2, np.nan, 3])
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other1 = [2, 3, 4, np.nan]
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res1 = ci.get_indexer(other1)
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expected1 = np.array([1, 3, -1, 2], dtype=np.intp)
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tm.assert_numpy_array_equal(res1, expected1)
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other2 = [1, 4, 2, 3]
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res2 = ci.get_indexer(other2)
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expected2 = np.array([0, -1, 1, 3], dtype=np.intp)
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tm.assert_numpy_array_equal(res2, expected2)
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class TestWhere:
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def test_where(self, listlike_box):
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klass = listlike_box
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i = CategoricalIndex(list("aabbca"), categories=list("cab"), ordered=False)
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cond = [True] * len(i)
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expected = i
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result = i.where(klass(cond))
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tm.assert_index_equal(result, expected)
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cond = [False] + [True] * (len(i) - 1)
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expected = CategoricalIndex([np.nan] + i[1:].tolist(), categories=i.categories)
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result = i.where(klass(cond))
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tm.assert_index_equal(result, expected)
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def test_where_non_categories(self):
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ci = CategoricalIndex(["a", "b", "c", "d"])
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mask = np.array([True, False, True, False])
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result = ci.where(mask, 2)
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expected = Index(["a", 2, "c", 2], dtype=object)
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tm.assert_index_equal(result, expected)
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msg = "Cannot setitem on a Categorical with a new category"
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with pytest.raises(TypeError, match=msg):
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# Test the Categorical method directly
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ci._data._where(mask, 2)
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class TestContains:
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def test_contains(self):
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ci = CategoricalIndex(list("aabbca"), categories=list("cabdef"), ordered=False)
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assert "a" in ci
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assert "z" not in ci
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assert "e" not in ci
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assert np.nan not in ci
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# assert codes NOT in index
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assert 0 not in ci
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assert 1 not in ci
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def test_contains_nan(self):
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ci = CategoricalIndex(list("aabbca") + [np.nan], categories=list("cabdef"))
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assert np.nan in ci
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@pytest.mark.parametrize("unwrap", [True, False])
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def test_contains_na_dtype(self, unwrap):
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dti = pd.date_range("2016-01-01", periods=100).insert(0, pd.NaT)
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pi = dti.to_period("D")
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tdi = dti - dti[-1]
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ci = CategoricalIndex(dti)
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obj = ci
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if unwrap:
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obj = ci._data
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assert np.nan in obj
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assert None in obj
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assert pd.NaT in obj
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assert np.datetime64("NaT") in obj
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assert np.timedelta64("NaT") not in obj
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obj2 = CategoricalIndex(tdi)
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if unwrap:
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obj2 = obj2._data
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assert np.nan in obj2
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assert None in obj2
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assert pd.NaT in obj2
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assert np.datetime64("NaT") not in obj2
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assert np.timedelta64("NaT") in obj2
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obj3 = CategoricalIndex(pi)
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if unwrap:
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obj3 = obj3._data
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assert np.nan in obj3
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assert None in obj3
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assert pd.NaT in obj3
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assert np.datetime64("NaT") not in obj3
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assert np.timedelta64("NaT") not in obj3
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@pytest.mark.parametrize(
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"item, expected",
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[
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(pd.Interval(0, 1), True),
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(1.5, True),
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(pd.Interval(0.5, 1.5), False),
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("a", False),
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(Timestamp(1), False),
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(pd.Timedelta(1), False),
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],
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ids=str,
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)
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def test_contains_interval(self, item, expected):
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# GH 23705
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ci = CategoricalIndex(IntervalIndex.from_breaks(range(3)))
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result = item in ci
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assert result is expected
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def test_contains_list(self):
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# GH#21729
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idx = CategoricalIndex([1, 2, 3])
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assert "a" not in idx
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with pytest.raises(TypeError, match="unhashable type"):
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["a"] in idx
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with pytest.raises(TypeError, match="unhashable type"):
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["a", "b"] in idx
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