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623 lines
20 KiB
623 lines
20 KiB
import numpy as np
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import pytest
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from pandas.core.dtypes.common import ensure_platform_int
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import pandas as pd
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from pandas import (
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Index,
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RangeIndex,
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)
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import pandas._testing as tm
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class TestRangeIndex:
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@pytest.fixture
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def simple_index(self):
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return RangeIndex(start=0, stop=20, step=2)
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def test_constructor_unwraps_index(self):
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result = RangeIndex(1, 3)
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expected = np.array([1, 2], dtype=np.int64)
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tm.assert_numpy_array_equal(result._data, expected)
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def test_can_hold_identifiers(self, simple_index):
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idx = simple_index
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key = idx[0]
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assert idx._can_hold_identifiers_and_holds_name(key) is False
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def test_too_many_names(self, simple_index):
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index = simple_index
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with pytest.raises(ValueError, match="^Length"):
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index.names = ["roger", "harold"]
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@pytest.mark.parametrize(
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"index, start, stop, step",
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[
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(RangeIndex(5), 0, 5, 1),
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(RangeIndex(0, 5), 0, 5, 1),
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(RangeIndex(5, step=2), 0, 5, 2),
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(RangeIndex(1, 5, 2), 1, 5, 2),
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],
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)
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def test_start_stop_step_attrs(self, index, start, stop, step):
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# GH 25710
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assert index.start == start
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assert index.stop == stop
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assert index.step == step
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def test_copy(self):
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i = RangeIndex(5, name="Foo")
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i_copy = i.copy()
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assert i_copy is not i
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assert i_copy.identical(i)
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assert i_copy._range == range(0, 5, 1)
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assert i_copy.name == "Foo"
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def test_repr(self):
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i = RangeIndex(5, name="Foo")
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result = repr(i)
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expected = "RangeIndex(start=0, stop=5, step=1, name='Foo')"
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assert result == expected
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result = eval(result)
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tm.assert_index_equal(result, i, exact=True)
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i = RangeIndex(5, 0, -1)
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result = repr(i)
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expected = "RangeIndex(start=5, stop=0, step=-1)"
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assert result == expected
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result = eval(result)
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tm.assert_index_equal(result, i, exact=True)
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def test_insert(self):
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idx = RangeIndex(5, name="Foo")
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result = idx[1:4]
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# test 0th element
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tm.assert_index_equal(idx[0:4], result.insert(0, idx[0]), exact="equiv")
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# GH 18295 (test missing)
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expected = Index([0, np.nan, 1, 2, 3, 4], dtype=np.float64)
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for na in [np.nan, None, pd.NA]:
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result = RangeIndex(5).insert(1, na)
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tm.assert_index_equal(result, expected)
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result = RangeIndex(5).insert(1, pd.NaT)
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expected = Index([0, pd.NaT, 1, 2, 3, 4], dtype=object)
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tm.assert_index_equal(result, expected)
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def test_insert_edges_preserves_rangeindex(self):
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idx = Index(range(4, 9, 2))
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result = idx.insert(0, 2)
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expected = Index(range(2, 9, 2))
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tm.assert_index_equal(result, expected, exact=True)
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result = idx.insert(3, 10)
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expected = Index(range(4, 11, 2))
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tm.assert_index_equal(result, expected, exact=True)
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def test_insert_middle_preserves_rangeindex(self):
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# insert in the middle
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idx = Index(range(0, 3, 2))
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result = idx.insert(1, 1)
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expected = Index(range(3))
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tm.assert_index_equal(result, expected, exact=True)
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idx = idx * 2
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result = idx.insert(1, 2)
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expected = expected * 2
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tm.assert_index_equal(result, expected, exact=True)
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def test_delete(self):
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idx = RangeIndex(5, name="Foo")
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expected = idx[1:]
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result = idx.delete(0)
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tm.assert_index_equal(result, expected, exact=True)
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assert result.name == expected.name
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expected = idx[:-1]
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result = idx.delete(-1)
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tm.assert_index_equal(result, expected, exact=True)
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assert result.name == expected.name
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msg = "index 5 is out of bounds for axis 0 with size 5"
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with pytest.raises((IndexError, ValueError), match=msg):
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# either depending on numpy version
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result = idx.delete(len(idx))
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def test_delete_preserves_rangeindex(self):
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idx = Index(range(2), name="foo")
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result = idx.delete([1])
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expected = Index(range(1), name="foo")
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tm.assert_index_equal(result, expected, exact=True)
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result = idx.delete(1)
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tm.assert_index_equal(result, expected, exact=True)
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def test_delete_preserves_rangeindex_middle(self):
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idx = Index(range(3), name="foo")
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result = idx.delete(1)
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expected = idx[::2]
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tm.assert_index_equal(result, expected, exact=True)
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result = idx.delete(-2)
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tm.assert_index_equal(result, expected, exact=True)
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def test_delete_preserves_rangeindex_list_at_end(self):
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idx = RangeIndex(0, 6, 1)
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loc = [2, 3, 4, 5]
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result = idx.delete(loc)
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expected = idx[:2]
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tm.assert_index_equal(result, expected, exact=True)
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result = idx.delete(loc[::-1])
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tm.assert_index_equal(result, expected, exact=True)
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def test_delete_preserves_rangeindex_list_middle(self):
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idx = RangeIndex(0, 6, 1)
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loc = [1, 2, 3, 4]
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result = idx.delete(loc)
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expected = RangeIndex(0, 6, 5)
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tm.assert_index_equal(result, expected, exact=True)
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result = idx.delete(loc[::-1])
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tm.assert_index_equal(result, expected, exact=True)
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def test_delete_all_preserves_rangeindex(self):
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idx = RangeIndex(0, 6, 1)
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loc = [0, 1, 2, 3, 4, 5]
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result = idx.delete(loc)
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expected = idx[:0]
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tm.assert_index_equal(result, expected, exact=True)
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result = idx.delete(loc[::-1])
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tm.assert_index_equal(result, expected, exact=True)
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def test_delete_not_preserving_rangeindex(self):
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idx = RangeIndex(0, 6, 1)
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loc = [0, 3, 5]
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result = idx.delete(loc)
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expected = Index([1, 2, 4])
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tm.assert_index_equal(result, expected, exact=True)
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result = idx.delete(loc[::-1])
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tm.assert_index_equal(result, expected, exact=True)
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def test_view(self):
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i = RangeIndex(0, name="Foo")
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i_view = i.view()
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assert i_view.name == "Foo"
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i_view = i.view("i8")
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tm.assert_numpy_array_equal(i.values, i_view)
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msg = "Passing a type in RangeIndex.view is deprecated"
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with tm.assert_produces_warning(FutureWarning, match=msg):
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i_view = i.view(RangeIndex)
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tm.assert_index_equal(i, i_view)
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def test_dtype(self, simple_index):
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index = simple_index
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assert index.dtype == np.int64
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def test_cache(self):
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# GH 26565, GH26617, GH35432, GH53387
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# This test checks whether _cache has been set.
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# Calling RangeIndex._cache["_data"] creates an int64 array of the same length
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# as the RangeIndex and stores it in _cache.
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idx = RangeIndex(0, 100, 10)
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assert idx._cache == {}
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repr(idx)
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assert idx._cache == {}
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str(idx)
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assert idx._cache == {}
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idx.get_loc(20)
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assert idx._cache == {}
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90 in idx # True
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assert idx._cache == {}
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91 in idx # False
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assert idx._cache == {}
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idx.all()
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assert idx._cache == {}
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idx.any()
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assert idx._cache == {}
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for _ in idx:
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pass
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assert idx._cache == {}
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msg = "RangeIndex.format is deprecated"
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with tm.assert_produces_warning(FutureWarning, match=msg):
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idx.format()
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assert idx._cache == {}
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df = pd.DataFrame({"a": range(10)}, index=idx)
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# df.__repr__ should not populate index cache
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str(df)
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assert idx._cache == {}
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df.loc[50]
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assert idx._cache == {}
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with pytest.raises(KeyError, match="51"):
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df.loc[51]
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assert idx._cache == {}
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df.loc[10:50]
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assert idx._cache == {}
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df.iloc[5:10]
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assert idx._cache == {}
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# after calling take, _cache may contain other keys, but not "_data"
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idx.take([3, 0, 1])
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assert "_data" not in idx._cache
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df.loc[[50]]
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assert "_data" not in idx._cache
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df.iloc[[5, 6, 7, 8, 9]]
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assert "_data" not in idx._cache
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# idx._cache should contain a _data entry after call to idx._data
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idx._data
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assert isinstance(idx._data, np.ndarray)
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assert idx._data is idx._data # check cached value is reused
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assert "_data" in idx._cache
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expected = np.arange(0, 100, 10, dtype="int64")
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tm.assert_numpy_array_equal(idx._cache["_data"], expected)
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def test_is_monotonic(self):
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index = RangeIndex(0, 20, 2)
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assert index.is_monotonic_increasing is True
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assert index.is_monotonic_increasing is True
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assert index.is_monotonic_decreasing is False
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assert index._is_strictly_monotonic_increasing is True
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assert index._is_strictly_monotonic_decreasing is False
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index = RangeIndex(4, 0, -1)
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assert index.is_monotonic_increasing is False
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assert index._is_strictly_monotonic_increasing is False
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assert index.is_monotonic_decreasing is True
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assert index._is_strictly_monotonic_decreasing is True
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index = RangeIndex(1, 2)
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assert index.is_monotonic_increasing is True
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assert index.is_monotonic_increasing is True
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assert index.is_monotonic_decreasing is True
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assert index._is_strictly_monotonic_increasing is True
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assert index._is_strictly_monotonic_decreasing is True
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index = RangeIndex(2, 1)
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assert index.is_monotonic_increasing is True
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assert index.is_monotonic_increasing is True
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assert index.is_monotonic_decreasing is True
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assert index._is_strictly_monotonic_increasing is True
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assert index._is_strictly_monotonic_decreasing is True
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index = RangeIndex(1, 1)
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assert index.is_monotonic_increasing is True
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assert index.is_monotonic_increasing is True
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assert index.is_monotonic_decreasing is True
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assert index._is_strictly_monotonic_increasing is True
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assert index._is_strictly_monotonic_decreasing is True
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@pytest.mark.parametrize(
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"left,right",
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[
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(RangeIndex(0, 9, 2), RangeIndex(0, 10, 2)),
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(RangeIndex(0), RangeIndex(1, -1, 3)),
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(RangeIndex(1, 2, 3), RangeIndex(1, 3, 4)),
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(RangeIndex(0, -9, -2), RangeIndex(0, -10, -2)),
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],
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)
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def test_equals_range(self, left, right):
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assert left.equals(right)
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assert right.equals(left)
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def test_logical_compat(self, simple_index):
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idx = simple_index
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assert idx.all() == idx.values.all()
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assert idx.any() == idx.values.any()
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def test_identical(self, simple_index):
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index = simple_index
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i = Index(index.copy())
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assert i.identical(index)
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# we don't allow object dtype for RangeIndex
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if isinstance(index, RangeIndex):
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return
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same_values_different_type = Index(i, dtype=object)
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assert not i.identical(same_values_different_type)
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i = index.copy(dtype=object)
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i = i.rename("foo")
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same_values = Index(i, dtype=object)
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assert same_values.identical(index.copy(dtype=object))
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assert not i.identical(index)
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assert Index(same_values, name="foo", dtype=object).identical(i)
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assert not index.copy(dtype=object).identical(index.copy(dtype="int64"))
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def test_nbytes(self):
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# memory savings vs int index
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idx = RangeIndex(0, 1000)
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assert idx.nbytes < Index(idx._values).nbytes / 10
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# constant memory usage
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i2 = RangeIndex(0, 10)
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assert idx.nbytes == i2.nbytes
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@pytest.mark.parametrize(
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"start,stop,step",
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[
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# can't
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("foo", "bar", "baz"),
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# shouldn't
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("0", "1", "2"),
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],
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)
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def test_cant_or_shouldnt_cast(self, start, stop, step):
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msg = f"Wrong type {type(start)} for value {start}"
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with pytest.raises(TypeError, match=msg):
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RangeIndex(start, stop, step)
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def test_view_index(self, simple_index):
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index = simple_index
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msg = "Passing a type in RangeIndex.view is deprecated"
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with tm.assert_produces_warning(FutureWarning, match=msg):
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index.view(Index)
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def test_prevent_casting(self, simple_index):
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index = simple_index
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result = index.astype("O")
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assert result.dtype == np.object_
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def test_repr_roundtrip(self, simple_index):
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index = simple_index
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tm.assert_index_equal(eval(repr(index)), index)
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def test_slice_keep_name(self):
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idx = RangeIndex(1, 2, name="asdf")
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assert idx.name == idx[1:].name
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@pytest.mark.parametrize(
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"index",
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[
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RangeIndex(start=0, stop=20, step=2, name="foo"),
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RangeIndex(start=18, stop=-1, step=-2, name="bar"),
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],
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ids=["index_inc", "index_dec"],
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)
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def test_has_duplicates(self, index):
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assert index.is_unique
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assert not index.has_duplicates
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def test_extended_gcd(self, simple_index):
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index = simple_index
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result = index._extended_gcd(6, 10)
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assert result[0] == result[1] * 6 + result[2] * 10
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assert 2 == result[0]
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result = index._extended_gcd(10, 6)
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assert 2 == result[1] * 10 + result[2] * 6
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assert 2 == result[0]
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def test_min_fitting_element(self):
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result = RangeIndex(0, 20, 2)._min_fitting_element(1)
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assert 2 == result
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result = RangeIndex(1, 6)._min_fitting_element(1)
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assert 1 == result
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result = RangeIndex(18, -2, -2)._min_fitting_element(1)
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assert 2 == result
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result = RangeIndex(5, 0, -1)._min_fitting_element(1)
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assert 1 == result
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big_num = 500000000000000000000000
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result = RangeIndex(5, big_num * 2, 1)._min_fitting_element(big_num)
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assert big_num == result
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def test_slice_specialised(self, simple_index):
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index = simple_index
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index.name = "foo"
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# scalar indexing
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res = index[1]
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expected = 2
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assert res == expected
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res = index[-1]
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expected = 18
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assert res == expected
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# slicing
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# slice value completion
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index_slice = index[:]
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expected = index
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tm.assert_index_equal(index_slice, expected)
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# positive slice values
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index_slice = index[7:10:2]
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expected = Index([14, 18], name="foo")
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tm.assert_index_equal(index_slice, expected, exact="equiv")
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# negative slice values
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index_slice = index[-1:-5:-2]
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expected = Index([18, 14], name="foo")
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tm.assert_index_equal(index_slice, expected, exact="equiv")
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# stop overshoot
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index_slice = index[2:100:4]
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expected = Index([4, 12], name="foo")
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tm.assert_index_equal(index_slice, expected, exact="equiv")
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# reverse
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index_slice = index[::-1]
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expected = Index(index.values[::-1], name="foo")
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tm.assert_index_equal(index_slice, expected, exact="equiv")
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index_slice = index[-8::-1]
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expected = Index([4, 2, 0], name="foo")
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tm.assert_index_equal(index_slice, expected, exact="equiv")
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index_slice = index[-40::-1]
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expected = Index(np.array([], dtype=np.int64), name="foo")
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tm.assert_index_equal(index_slice, expected, exact="equiv")
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index_slice = index[40::-1]
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expected = Index(index.values[40::-1], name="foo")
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tm.assert_index_equal(index_slice, expected, exact="equiv")
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index_slice = index[10::-1]
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expected = Index(index.values[::-1], name="foo")
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tm.assert_index_equal(index_slice, expected, exact="equiv")
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@pytest.mark.parametrize("step", set(range(-5, 6)) - {0})
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def test_len_specialised(self, step):
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# make sure that our len is the same as np.arange calc
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start, stop = (0, 5) if step > 0 else (5, 0)
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arr = np.arange(start, stop, step)
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index = RangeIndex(start, stop, step)
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assert len(index) == len(arr)
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index = RangeIndex(stop, start, step)
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|
assert len(index) == 0
|
|
|
|
@pytest.mark.parametrize(
|
|
"indices, expected",
|
|
[
|
|
([RangeIndex(1, 12, 5)], RangeIndex(1, 12, 5)),
|
|
([RangeIndex(0, 6, 4)], RangeIndex(0, 6, 4)),
|
|
([RangeIndex(1, 3), RangeIndex(3, 7)], RangeIndex(1, 7)),
|
|
([RangeIndex(1, 5, 2), RangeIndex(5, 6)], RangeIndex(1, 6, 2)),
|
|
([RangeIndex(1, 3, 2), RangeIndex(4, 7, 3)], RangeIndex(1, 7, 3)),
|
|
([RangeIndex(-4, 3, 2), RangeIndex(4, 7, 2)], RangeIndex(-4, 7, 2)),
|
|
([RangeIndex(-4, -8), RangeIndex(-8, -12)], RangeIndex(0, 0)),
|
|
([RangeIndex(-4, -8), RangeIndex(3, -4)], RangeIndex(0, 0)),
|
|
([RangeIndex(-4, -8), RangeIndex(3, 5)], RangeIndex(3, 5)),
|
|
([RangeIndex(-4, -2), RangeIndex(3, 5)], Index([-4, -3, 3, 4])),
|
|
([RangeIndex(-2), RangeIndex(3, 5)], RangeIndex(3, 5)),
|
|
([RangeIndex(2), RangeIndex(2)], Index([0, 1, 0, 1])),
|
|
([RangeIndex(2), RangeIndex(2, 5), RangeIndex(5, 8, 4)], RangeIndex(0, 6)),
|
|
(
|
|
[RangeIndex(2), RangeIndex(3, 5), RangeIndex(5, 8, 4)],
|
|
Index([0, 1, 3, 4, 5]),
|
|
),
|
|
(
|
|
[RangeIndex(-2, 2), RangeIndex(2, 5), RangeIndex(5, 8, 4)],
|
|
RangeIndex(-2, 6),
|
|
),
|
|
([RangeIndex(3), Index([-1, 3, 15])], Index([0, 1, 2, -1, 3, 15])),
|
|
([RangeIndex(3), Index([-1, 3.1, 15.0])], Index([0, 1, 2, -1, 3.1, 15.0])),
|
|
([RangeIndex(3), Index(["a", None, 14])], Index([0, 1, 2, "a", None, 14])),
|
|
([RangeIndex(3, 1), Index(["a", None, 14])], Index(["a", None, 14])),
|
|
],
|
|
)
|
|
def test_append(self, indices, expected):
|
|
# GH16212
|
|
result = indices[0].append(indices[1:])
|
|
tm.assert_index_equal(result, expected, exact=True)
|
|
|
|
if len(indices) == 2:
|
|
# Append single item rather than list
|
|
result2 = indices[0].append(indices[1])
|
|
tm.assert_index_equal(result2, expected, exact=True)
|
|
|
|
def test_engineless_lookup(self):
|
|
# GH 16685
|
|
# Standard lookup on RangeIndex should not require the engine to be
|
|
# created
|
|
idx = RangeIndex(2, 10, 3)
|
|
|
|
assert idx.get_loc(5) == 1
|
|
tm.assert_numpy_array_equal(
|
|
idx.get_indexer([2, 8]), ensure_platform_int(np.array([0, 2]))
|
|
)
|
|
with pytest.raises(KeyError, match="3"):
|
|
idx.get_loc(3)
|
|
|
|
assert "_engine" not in idx._cache
|
|
|
|
# Different types of scalars can be excluded immediately, no need to
|
|
# use the _engine
|
|
with pytest.raises(KeyError, match="'a'"):
|
|
idx.get_loc("a")
|
|
|
|
assert "_engine" not in idx._cache
|
|
|
|
def test_format_empty(self):
|
|
# GH35712
|
|
empty_idx = RangeIndex(0)
|
|
msg = r"RangeIndex\.format is deprecated"
|
|
with tm.assert_produces_warning(FutureWarning, match=msg):
|
|
assert empty_idx.format() == []
|
|
with tm.assert_produces_warning(FutureWarning, match=msg):
|
|
assert empty_idx.format(name=True) == [""]
|
|
|
|
@pytest.mark.parametrize(
|
|
"ri",
|
|
[
|
|
RangeIndex(0, -1, -1),
|
|
RangeIndex(0, 1, 1),
|
|
RangeIndex(1, 3, 2),
|
|
RangeIndex(0, -1, -2),
|
|
RangeIndex(-3, -5, -2),
|
|
],
|
|
)
|
|
def test_append_len_one(self, ri):
|
|
# GH39401
|
|
result = ri.append([])
|
|
tm.assert_index_equal(result, ri, exact=True)
|
|
|
|
@pytest.mark.parametrize("base", [RangeIndex(0, 2), Index([0, 1])])
|
|
def test_isin_range(self, base):
|
|
# GH#41151
|
|
values = RangeIndex(0, 1)
|
|
result = base.isin(values)
|
|
expected = np.array([True, False])
|
|
tm.assert_numpy_array_equal(result, expected)
|
|
|
|
def test_sort_values_key(self):
|
|
# GH#43666, GH#52764
|
|
sort_order = {8: 2, 6: 0, 4: 8, 2: 10, 0: 12}
|
|
values = RangeIndex(0, 10, 2)
|
|
result = values.sort_values(key=lambda x: x.map(sort_order))
|
|
expected = Index([6, 8, 4, 2, 0], dtype="int64")
|
|
tm.assert_index_equal(result, expected, check_exact=True)
|
|
|
|
# check this matches the Series.sort_values behavior
|
|
ser = values.to_series()
|
|
result2 = ser.sort_values(key=lambda x: x.map(sort_order))
|
|
tm.assert_series_equal(result2, expected.to_series(), check_exact=True)
|
|
|
|
def test_range_index_rsub_by_const(self):
|
|
# GH#53255
|
|
result = 3 - RangeIndex(0, 4, 1)
|
|
expected = RangeIndex(3, -1, -1)
|
|
tm.assert_index_equal(result, expected)
|