1244 lines
44 KiB
Python
1244 lines
44 KiB
Python
from datetime import datetime, timedelta
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import re
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import numpy as np
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import pytest
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from pandas._libs.tslibs import Timestamp
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import pandas as pd
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from pandas import Float64Index, Index, Int64Index, Series, UInt64Index
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import pandas._testing as tm
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from pandas.api.types import pandas_dtype
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from pandas.tests.indexes.common import Base
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class Numeric(Base):
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def test_can_hold_identifiers(self):
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idx = self.create_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_numeric_compat(self):
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pass # override Base method
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def test_explicit_conversions(self):
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# GH 8608
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# add/sub are overridden explicitly for Float/Int Index
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idx = self._holder(np.arange(5, dtype="int64"))
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# float conversions
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arr = np.arange(5, dtype="int64") * 3.2
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expected = Float64Index(arr)
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fidx = idx * 3.2
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tm.assert_index_equal(fidx, expected)
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fidx = 3.2 * idx
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tm.assert_index_equal(fidx, expected)
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# interops with numpy arrays
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expected = Float64Index(arr)
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a = np.zeros(5, dtype="float64")
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result = fidx - a
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tm.assert_index_equal(result, expected)
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expected = Float64Index(-arr)
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a = np.zeros(5, dtype="float64")
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result = a - fidx
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tm.assert_index_equal(result, expected)
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def test_index_groupby(self):
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int_idx = Index(range(6))
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float_idx = Index(np.arange(0, 0.6, 0.1))
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obj_idx = Index("A B C D E F".split())
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dt_idx = pd.date_range("2013-01-01", freq="M", periods=6)
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for idx in [int_idx, float_idx, obj_idx, dt_idx]:
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to_groupby = np.array([1, 2, np.nan, np.nan, 2, 1])
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tm.assert_dict_equal(
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idx.groupby(to_groupby), {1.0: idx[[0, 5]], 2.0: idx[[1, 4]]}
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)
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to_groupby = Index(
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[
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datetime(2011, 11, 1),
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datetime(2011, 12, 1),
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pd.NaT,
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pd.NaT,
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datetime(2011, 12, 1),
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datetime(2011, 11, 1),
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],
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tz="UTC",
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).values
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ex_keys = [Timestamp("2011-11-01"), Timestamp("2011-12-01")]
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expected = {ex_keys[0]: idx[[0, 5]], ex_keys[1]: idx[[1, 4]]}
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tm.assert_dict_equal(idx.groupby(to_groupby), expected)
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@pytest.mark.parametrize("klass", [list, tuple, np.array, Series])
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def test_where(self, klass):
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i = self.create_index()
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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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cond = [False] + [True] * (len(i) - 1)
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expected = Float64Index([i._na_value] + i[1:].tolist())
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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_insert(self, nulls_fixture):
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# GH 18295 (test missing)
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index = self.create_index()
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expected = Float64Index([index[0], np.nan] + list(index[1:]))
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result = index.insert(1, nulls_fixture)
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tm.assert_index_equal(result, expected)
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class TestFloat64Index(Numeric):
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_holder = Float64Index
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@pytest.fixture(
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params=[
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[1.5, 2, 3, 4, 5],
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[0.0, 2.5, 5.0, 7.5, 10.0],
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[5, 4, 3, 2, 1.5],
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[10.0, 7.5, 5.0, 2.5, 0.0],
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],
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ids=["mixed", "float", "mixed_dec", "float_dec"],
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)
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def indices(self, request):
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return Float64Index(request.param)
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@pytest.fixture
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def mixed_index(self):
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return Float64Index([1.5, 2, 3, 4, 5])
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@pytest.fixture
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def float_index(self):
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return Float64Index([0.0, 2.5, 5.0, 7.5, 10.0])
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def create_index(self):
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return Float64Index(np.arange(5, dtype="float64"))
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def test_repr_roundtrip(self, indices):
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tm.assert_index_equal(eval(repr(indices)), indices)
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def check_is_index(self, i):
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assert isinstance(i, Index)
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assert not isinstance(i, Float64Index)
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def check_coerce(self, a, b, is_float_index=True):
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assert a.equals(b)
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tm.assert_index_equal(a, b, exact=False)
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if is_float_index:
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assert isinstance(b, Float64Index)
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else:
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self.check_is_index(b)
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def test_constructor(self):
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# explicit construction
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index = Float64Index([1, 2, 3, 4, 5])
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assert isinstance(index, Float64Index)
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expected = np.array([1, 2, 3, 4, 5], dtype="float64")
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tm.assert_numpy_array_equal(index.values, expected)
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index = Float64Index(np.array([1, 2, 3, 4, 5]))
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assert isinstance(index, Float64Index)
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index = Float64Index([1.0, 2, 3, 4, 5])
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assert isinstance(index, Float64Index)
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index = Float64Index(np.array([1.0, 2, 3, 4, 5]))
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assert isinstance(index, Float64Index)
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assert index.dtype == float
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index = Float64Index(np.array([1.0, 2, 3, 4, 5]), dtype=np.float32)
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assert isinstance(index, Float64Index)
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assert index.dtype == np.float64
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index = Float64Index(np.array([1, 2, 3, 4, 5]), dtype=np.float32)
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assert isinstance(index, Float64Index)
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assert index.dtype == np.float64
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# nan handling
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result = Float64Index([np.nan, np.nan])
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assert pd.isna(result.values).all()
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result = Float64Index(np.array([np.nan]))
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assert pd.isna(result.values).all()
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result = Index(np.array([np.nan]))
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assert pd.isna(result.values).all()
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@pytest.mark.parametrize(
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"index, dtype",
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[
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(pd.Int64Index, "float64"),
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(pd.UInt64Index, "categorical"),
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(pd.Float64Index, "datetime64"),
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(pd.RangeIndex, "float64"),
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],
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)
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def test_invalid_dtype(self, index, dtype):
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# GH 29539
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with pytest.raises(
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ValueError,
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match=rf"Incorrect `dtype` passed: expected \w+(?: \w+)?, received {dtype}",
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):
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index([1, 2, 3], dtype=dtype)
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def test_constructor_invalid(self):
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# invalid
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msg = (
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r"Float64Index\(\.\.\.\) must be called with a collection of"
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r" some kind, 0\.0 was passed"
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)
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with pytest.raises(TypeError, match=msg):
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Float64Index(0.0)
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msg = (
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"String dtype not supported, "
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"you may need to explicitly cast to a numeric type"
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)
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with pytest.raises(TypeError, match=msg):
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Float64Index(["a", "b", 0.0])
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msg = r"float\(\) argument must be a string or a number, not 'Timestamp'"
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with pytest.raises(TypeError, match=msg):
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Float64Index([Timestamp("20130101")])
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def test_constructor_coerce(self, mixed_index, float_index):
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self.check_coerce(mixed_index, Index([1.5, 2, 3, 4, 5]))
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self.check_coerce(float_index, Index(np.arange(5) * 2.5))
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self.check_coerce(
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float_index, Index(np.array(np.arange(5) * 2.5, dtype=object))
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)
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def test_constructor_explicit(self, mixed_index, float_index):
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# these don't auto convert
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self.check_coerce(
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float_index, Index((np.arange(5) * 2.5), dtype=object), is_float_index=False
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)
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self.check_coerce(
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mixed_index, Index([1.5, 2, 3, 4, 5], dtype=object), is_float_index=False
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)
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def test_astype(self, mixed_index, float_index):
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result = float_index.astype(object)
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assert result.equals(float_index)
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assert float_index.equals(result)
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self.check_is_index(result)
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i = mixed_index.copy()
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i.name = "foo"
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result = i.astype(object)
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assert result.equals(i)
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assert i.equals(result)
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self.check_is_index(result)
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# GH 12881
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# a float astype int
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for dtype in ["int16", "int32", "int64"]:
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i = Float64Index([0, 1, 2])
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result = i.astype(dtype)
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expected = Int64Index([0, 1, 2])
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tm.assert_index_equal(result, expected)
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i = Float64Index([0, 1.1, 2])
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result = i.astype(dtype)
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expected = Int64Index([0, 1, 2])
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tm.assert_index_equal(result, expected)
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for dtype in ["float32", "float64"]:
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i = Float64Index([0, 1, 2])
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result = i.astype(dtype)
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expected = i
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tm.assert_index_equal(result, expected)
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i = Float64Index([0, 1.1, 2])
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result = i.astype(dtype)
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expected = Index(i.values.astype(dtype))
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tm.assert_index_equal(result, expected)
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# invalid
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for dtype in ["M8[ns]", "m8[ns]"]:
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msg = (
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f"Cannot convert Float64Index to dtype {pandas_dtype(dtype)}; "
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f"integer values are required for conversion"
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)
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with pytest.raises(TypeError, match=re.escape(msg)):
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i.astype(dtype)
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# GH 13149
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for dtype in ["int16", "int32", "int64"]:
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i = Float64Index([0, 1.1, np.NAN])
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msg = r"Cannot convert non-finite values \(NA or inf\) to integer"
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with pytest.raises(ValueError, match=msg):
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i.astype(dtype)
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def test_cannot_cast_inf_to_int(self):
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idx = pd.Float64Index([1, 2, np.inf])
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msg = r"Cannot convert non-finite values \(NA or inf\) to integer"
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with pytest.raises(ValueError, match=msg):
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idx.astype(int)
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def test_type_coercion_fail(self, any_int_dtype):
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# see gh-15832
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msg = "Trying to coerce float values to integers"
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with pytest.raises(ValueError, match=msg):
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Index([1, 2, 3.5], dtype=any_int_dtype)
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def test_type_coercion_valid(self, float_dtype):
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# There is no Float32Index, so we always
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# generate Float64Index.
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i = Index([1, 2, 3.5], dtype=float_dtype)
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tm.assert_index_equal(i, Index([1, 2, 3.5]))
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def test_equals_numeric(self):
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i = Float64Index([1.0, 2.0])
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assert i.equals(i)
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assert i.identical(i)
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i2 = Float64Index([1.0, 2.0])
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assert i.equals(i2)
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i = Float64Index([1.0, np.nan])
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assert i.equals(i)
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assert i.identical(i)
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i2 = Float64Index([1.0, np.nan])
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assert i.equals(i2)
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def test_get_indexer(self):
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idx = Float64Index([0.0, 1.0, 2.0])
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tm.assert_numpy_array_equal(
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idx.get_indexer(idx), np.array([0, 1, 2], dtype=np.intp)
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)
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target = [-0.1, 0.5, 1.1]
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tm.assert_numpy_array_equal(
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idx.get_indexer(target, "pad"), np.array([-1, 0, 1], dtype=np.intp)
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)
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tm.assert_numpy_array_equal(
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idx.get_indexer(target, "backfill"), np.array([0, 1, 2], dtype=np.intp)
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)
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tm.assert_numpy_array_equal(
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idx.get_indexer(target, "nearest"), np.array([0, 1, 1], dtype=np.intp)
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)
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def test_get_loc(self):
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idx = Float64Index([0.0, 1.0, 2.0])
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for method in [None, "pad", "backfill", "nearest"]:
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assert idx.get_loc(1, method) == 1
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if method is not None:
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assert idx.get_loc(1, method, tolerance=0) == 1
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for method, loc in [("pad", 1), ("backfill", 2), ("nearest", 1)]:
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assert idx.get_loc(1.1, method) == loc
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assert idx.get_loc(1.1, method, tolerance=0.9) == loc
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with pytest.raises(KeyError, match="^'foo'$"):
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idx.get_loc("foo")
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with pytest.raises(KeyError, match=r"^1\.5$"):
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idx.get_loc(1.5)
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with pytest.raises(KeyError, match=r"^1\.5$"):
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idx.get_loc(1.5, method="pad", tolerance=0.1)
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with pytest.raises(KeyError, match="^True$"):
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idx.get_loc(True)
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with pytest.raises(KeyError, match="^False$"):
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idx.get_loc(False)
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with pytest.raises(ValueError, match="must be numeric"):
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idx.get_loc(1.4, method="nearest", tolerance="foo")
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with pytest.raises(ValueError, match="must contain numeric elements"):
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idx.get_loc(1.4, method="nearest", tolerance=np.array(["foo"]))
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with pytest.raises(
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ValueError, match="tolerance size must match target index size"
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):
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idx.get_loc(1.4, method="nearest", tolerance=np.array([1, 2]))
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def test_get_loc_na(self):
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idx = Float64Index([np.nan, 1, 2])
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assert idx.get_loc(1) == 1
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assert idx.get_loc(np.nan) == 0
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idx = Float64Index([np.nan, 1, np.nan])
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assert idx.get_loc(1) == 1
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# representable by slice [0:2:2]
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# pytest.raises(KeyError, idx.slice_locs, np.nan)
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sliced = idx.slice_locs(np.nan)
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assert isinstance(sliced, tuple)
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assert sliced == (0, 3)
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# not representable by slice
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idx = Float64Index([np.nan, 1, np.nan, np.nan])
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assert idx.get_loc(1) == 1
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msg = "'Cannot get left slice bound for non-unique label: nan"
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with pytest.raises(KeyError, match=msg):
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idx.slice_locs(np.nan)
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def test_get_loc_missing_nan(self):
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# GH 8569
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idx = Float64Index([1, 2])
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assert idx.get_loc(1) == 0
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with pytest.raises(KeyError, match=r"^3\.0$"):
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idx.get_loc(3)
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with pytest.raises(KeyError, match="^nan$"):
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idx.get_loc(np.nan)
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with pytest.raises(KeyError, match=r"^\[nan\]$"):
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idx.get_loc([np.nan])
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def test_contains_nans(self):
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i = Float64Index([1.0, 2.0, np.nan])
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assert np.nan in i
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def test_contains_not_nans(self):
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i = Float64Index([1.0, 2.0, np.nan])
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assert 1.0 in i
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def test_doesnt_contain_all_the_things(self):
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i = Float64Index([np.nan])
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assert not i.isin([0]).item()
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assert not i.isin([1]).item()
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assert i.isin([np.nan]).item()
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def test_nan_multiple_containment(self):
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i = Float64Index([1.0, np.nan])
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tm.assert_numpy_array_equal(i.isin([1.0]), np.array([True, False]))
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tm.assert_numpy_array_equal(i.isin([2.0, np.pi]), np.array([False, False]))
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tm.assert_numpy_array_equal(i.isin([np.nan]), np.array([False, True]))
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tm.assert_numpy_array_equal(i.isin([1.0, np.nan]), np.array([True, True]))
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i = Float64Index([1.0, 2.0])
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tm.assert_numpy_array_equal(i.isin([np.nan]), np.array([False, False]))
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def test_astype_from_object(self):
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index = Index([1.0, np.nan, 0.2], dtype="object")
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result = index.astype(float)
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expected = Float64Index([1.0, np.nan, 0.2])
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assert result.dtype == expected.dtype
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tm.assert_index_equal(result, expected)
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def test_fillna_float64(self):
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# GH 11343
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idx = Index([1.0, np.nan, 3.0], dtype=float, name="x")
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# can't downcast
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exp = Index([1.0, 0.1, 3.0], name="x")
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tm.assert_index_equal(idx.fillna(0.1), exp)
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# downcast
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exp = Float64Index([1.0, 2.0, 3.0], name="x")
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tm.assert_index_equal(idx.fillna(2), exp)
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# object
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exp = Index([1.0, "obj", 3.0], name="x")
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tm.assert_index_equal(idx.fillna("obj"), exp)
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def test_take_fill_value(self):
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# GH 12631
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idx = pd.Float64Index([1.0, 2.0, 3.0], name="xxx")
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result = idx.take(np.array([1, 0, -1]))
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expected = pd.Float64Index([2.0, 1.0, 3.0], name="xxx")
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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.Float64Index([2.0, 1.0, np.nan], name="xxx")
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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.Float64Index([2.0, 1.0, 3.0], name="xxx")
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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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)
|
|
with pytest.raises(ValueError, match=msg):
|
|
idx.take(np.array([1, 0, -2]), fill_value=True)
|
|
with pytest.raises(ValueError, match=msg):
|
|
idx.take(np.array([1, 0, -5]), fill_value=True)
|
|
|
|
with pytest.raises(IndexError):
|
|
idx.take(np.array([1, -5]))
|
|
|
|
|
|
class NumericInt(Numeric):
|
|
def test_view(self):
|
|
i = self._holder([], name="Foo")
|
|
i_view = i.view()
|
|
assert i_view.name == "Foo"
|
|
|
|
i_view = i.view(self._dtype)
|
|
tm.assert_index_equal(i, self._holder(i_view, name="Foo"))
|
|
|
|
i_view = i.view(self._holder)
|
|
tm.assert_index_equal(i, self._holder(i_view, name="Foo"))
|
|
|
|
def test_is_monotonic(self):
|
|
index = self._holder([1, 2, 3, 4])
|
|
assert index.is_monotonic is True
|
|
assert index.is_monotonic_increasing is True
|
|
assert index._is_strictly_monotonic_increasing is True
|
|
assert index.is_monotonic_decreasing is False
|
|
assert index._is_strictly_monotonic_decreasing is False
|
|
|
|
index = self._holder([4, 3, 2, 1])
|
|
assert index.is_monotonic is False
|
|
assert index._is_strictly_monotonic_increasing is False
|
|
assert index._is_strictly_monotonic_decreasing is True
|
|
|
|
index = self._holder([1])
|
|
assert index.is_monotonic is True
|
|
assert index.is_monotonic_increasing is True
|
|
assert index.is_monotonic_decreasing is True
|
|
assert index._is_strictly_monotonic_increasing is True
|
|
assert index._is_strictly_monotonic_decreasing is True
|
|
|
|
def test_is_strictly_monotonic(self):
|
|
index = self._holder([1, 1, 2, 3])
|
|
assert index.is_monotonic_increasing is True
|
|
assert index._is_strictly_monotonic_increasing is False
|
|
|
|
index = self._holder([3, 2, 1, 1])
|
|
assert index.is_monotonic_decreasing is True
|
|
assert index._is_strictly_monotonic_decreasing is False
|
|
|
|
index = self._holder([1, 1])
|
|
assert index.is_monotonic_increasing
|
|
assert index.is_monotonic_decreasing
|
|
assert not index._is_strictly_monotonic_increasing
|
|
assert not index._is_strictly_monotonic_decreasing
|
|
|
|
def test_logical_compat(self):
|
|
idx = self.create_index()
|
|
assert idx.all() == idx.values.all()
|
|
assert idx.any() == idx.values.any()
|
|
|
|
def test_identical(self):
|
|
index = self.create_index()
|
|
i = Index(index.copy())
|
|
assert i.identical(index)
|
|
|
|
same_values_different_type = Index(i, dtype=object)
|
|
assert not i.identical(same_values_different_type)
|
|
|
|
i = index.copy(dtype=object)
|
|
i = i.rename("foo")
|
|
same_values = Index(i, dtype=object)
|
|
assert same_values.identical(i)
|
|
|
|
assert not i.identical(index)
|
|
assert Index(same_values, name="foo", dtype=object).identical(i)
|
|
|
|
assert not index.copy(dtype=object).identical(index.copy(dtype=self._dtype))
|
|
|
|
def test_join_non_unique(self):
|
|
left = Index([4, 4, 3, 3])
|
|
|
|
joined, lidx, ridx = left.join(left, return_indexers=True)
|
|
|
|
exp_joined = Index([3, 3, 3, 3, 4, 4, 4, 4])
|
|
tm.assert_index_equal(joined, exp_joined)
|
|
|
|
exp_lidx = np.array([2, 2, 3, 3, 0, 0, 1, 1], dtype=np.intp)
|
|
tm.assert_numpy_array_equal(lidx, exp_lidx)
|
|
|
|
exp_ridx = np.array([2, 3, 2, 3, 0, 1, 0, 1], dtype=np.intp)
|
|
tm.assert_numpy_array_equal(ridx, exp_ridx)
|
|
|
|
def test_join_self(self, join_type):
|
|
index = self.create_index()
|
|
joined = index.join(index, how=join_type)
|
|
assert index is joined
|
|
|
|
def test_union_noncomparable(self):
|
|
# corner case, non-Int64Index
|
|
index = self.create_index()
|
|
other = Index([datetime.now() + timedelta(i) for i in range(4)], dtype=object)
|
|
result = index.union(other)
|
|
expected = Index(np.concatenate((index, other)))
|
|
tm.assert_index_equal(result, expected)
|
|
|
|
result = other.union(index)
|
|
expected = Index(np.concatenate((other, index)))
|
|
tm.assert_index_equal(result, expected)
|
|
|
|
def test_cant_or_shouldnt_cast(self):
|
|
msg = (
|
|
"String dtype not supported, "
|
|
"you may need to explicitly cast to a numeric type"
|
|
)
|
|
# can't
|
|
data = ["foo", "bar", "baz"]
|
|
with pytest.raises(TypeError, match=msg):
|
|
self._holder(data)
|
|
|
|
# shouldn't
|
|
data = ["0", "1", "2"]
|
|
with pytest.raises(TypeError, match=msg):
|
|
self._holder(data)
|
|
|
|
def test_view_index(self):
|
|
index = self.create_index()
|
|
index.view(Index)
|
|
|
|
def test_prevent_casting(self):
|
|
index = self.create_index()
|
|
result = index.astype("O")
|
|
assert result.dtype == np.object_
|
|
|
|
def test_take_preserve_name(self):
|
|
index = self._holder([1, 2, 3, 4], name="foo")
|
|
taken = index.take([3, 0, 1])
|
|
assert index.name == taken.name
|
|
|
|
def test_take_fill_value(self):
|
|
# see gh-12631
|
|
idx = self._holder([1, 2, 3], name="xxx")
|
|
result = idx.take(np.array([1, 0, -1]))
|
|
expected = self._holder([2, 1, 3], name="xxx")
|
|
tm.assert_index_equal(result, expected)
|
|
|
|
name = self._holder.__name__
|
|
msg = f"Unable to fill values because {name} cannot contain NA"
|
|
|
|
# fill_value=True
|
|
with pytest.raises(ValueError, match=msg):
|
|
idx.take(np.array([1, 0, -1]), fill_value=True)
|
|
|
|
# allow_fill=False
|
|
result = idx.take(np.array([1, 0, -1]), allow_fill=False, fill_value=True)
|
|
expected = self._holder([2, 1, 3], name="xxx")
|
|
tm.assert_index_equal(result, expected)
|
|
|
|
with pytest.raises(ValueError, match=msg):
|
|
idx.take(np.array([1, 0, -2]), fill_value=True)
|
|
with pytest.raises(ValueError, match=msg):
|
|
idx.take(np.array([1, 0, -5]), fill_value=True)
|
|
|
|
with pytest.raises(IndexError):
|
|
idx.take(np.array([1, -5]))
|
|
|
|
def test_slice_keep_name(self):
|
|
idx = self._holder([1, 2], name="asdf")
|
|
assert idx.name == idx[1:].name
|
|
|
|
|
|
class TestInt64Index(NumericInt):
|
|
_dtype = "int64"
|
|
_holder = Int64Index
|
|
|
|
@pytest.fixture(
|
|
params=[range(0, 20, 2), range(19, -1, -1)], ids=["index_inc", "index_dec"]
|
|
)
|
|
def indices(self, request):
|
|
return Int64Index(request.param)
|
|
|
|
def create_index(self):
|
|
# return Int64Index(np.arange(5, dtype="int64"))
|
|
return Int64Index(range(0, 20, 2))
|
|
|
|
def test_constructor(self):
|
|
# pass list, coerce fine
|
|
index = Int64Index([-5, 0, 1, 2])
|
|
expected = Index([-5, 0, 1, 2], dtype=np.int64)
|
|
tm.assert_index_equal(index, expected)
|
|
|
|
# from iterable
|
|
index = Int64Index(iter([-5, 0, 1, 2]))
|
|
tm.assert_index_equal(index, expected)
|
|
|
|
# scalar raise Exception
|
|
msg = (
|
|
r"Int64Index\(\.\.\.\) must be called with a collection of some "
|
|
"kind, 5 was passed"
|
|
)
|
|
with pytest.raises(TypeError, match=msg):
|
|
Int64Index(5)
|
|
|
|
# copy
|
|
arr = index.values
|
|
new_index = Int64Index(arr, copy=True)
|
|
tm.assert_index_equal(new_index, index)
|
|
val = arr[0] + 3000
|
|
|
|
# this should not change index
|
|
arr[0] = val
|
|
assert new_index[0] != val
|
|
|
|
# interpret list-like
|
|
expected = Int64Index([5, 0])
|
|
for cls in [Index, Int64Index]:
|
|
for idx in [
|
|
cls([5, 0], dtype="int64"),
|
|
cls(np.array([5, 0]), dtype="int64"),
|
|
cls(Series([5, 0]), dtype="int64"),
|
|
]:
|
|
tm.assert_index_equal(idx, expected)
|
|
|
|
def test_constructor_corner(self):
|
|
arr = np.array([1, 2, 3, 4], dtype=object)
|
|
index = Int64Index(arr)
|
|
assert index.values.dtype == np.int64
|
|
tm.assert_index_equal(index, Index(arr))
|
|
|
|
# preventing casting
|
|
arr = np.array([1, "2", 3, "4"], dtype=object)
|
|
with pytest.raises(TypeError, match="casting"):
|
|
Int64Index(arr)
|
|
|
|
arr_with_floats = [0, 2, 3, 4, 5, 1.25, 3, -1]
|
|
with pytest.raises(TypeError, match="casting"):
|
|
Int64Index(arr_with_floats)
|
|
|
|
def test_constructor_coercion_signed_to_unsigned(self, uint_dtype):
|
|
|
|
# see gh-15832
|
|
msg = "Trying to coerce negative values to unsigned integers"
|
|
|
|
with pytest.raises(OverflowError, match=msg):
|
|
Index([-1], dtype=uint_dtype)
|
|
|
|
def test_constructor_unwraps_index(self):
|
|
idx = pd.Index([1, 2])
|
|
result = pd.Int64Index(idx)
|
|
expected = np.array([1, 2], dtype="int64")
|
|
tm.assert_numpy_array_equal(result._data, expected)
|
|
|
|
def test_coerce_list(self):
|
|
# coerce things
|
|
arr = Index([1, 2, 3, 4])
|
|
assert isinstance(arr, Int64Index)
|
|
|
|
# but not if explicit dtype passed
|
|
arr = Index([1, 2, 3, 4], dtype=object)
|
|
assert isinstance(arr, Index)
|
|
|
|
def test_get_indexer(self):
|
|
index = self.create_index()
|
|
target = Int64Index(np.arange(10))
|
|
indexer = index.get_indexer(target)
|
|
expected = np.array([0, -1, 1, -1, 2, -1, 3, -1, 4, -1], dtype=np.intp)
|
|
tm.assert_numpy_array_equal(indexer, expected)
|
|
|
|
target = Int64Index(np.arange(10))
|
|
indexer = index.get_indexer(target, method="pad")
|
|
expected = np.array([0, 0, 1, 1, 2, 2, 3, 3, 4, 4], dtype=np.intp)
|
|
tm.assert_numpy_array_equal(indexer, expected)
|
|
|
|
target = Int64Index(np.arange(10))
|
|
indexer = index.get_indexer(target, method="backfill")
|
|
expected = np.array([0, 1, 1, 2, 2, 3, 3, 4, 4, 5], dtype=np.intp)
|
|
tm.assert_numpy_array_equal(indexer, expected)
|
|
|
|
def test_get_indexer_nan(self):
|
|
# GH 7820
|
|
result = Index([1, 2, np.nan]).get_indexer([np.nan])
|
|
expected = np.array([2], dtype=np.intp)
|
|
tm.assert_numpy_array_equal(result, expected)
|
|
|
|
def test_intersection(self):
|
|
index = self.create_index()
|
|
other = Index([1, 2, 3, 4, 5])
|
|
result = index.intersection(other)
|
|
expected = Index(np.sort(np.intersect1d(index.values, other.values)))
|
|
tm.assert_index_equal(result, expected)
|
|
|
|
result = other.intersection(index)
|
|
expected = Index(
|
|
np.sort(np.asarray(np.intersect1d(index.values, other.values)))
|
|
)
|
|
tm.assert_index_equal(result, expected)
|
|
|
|
def test_join_inner(self):
|
|
index = self.create_index()
|
|
other = Int64Index([7, 12, 25, 1, 2, 5])
|
|
other_mono = Int64Index([1, 2, 5, 7, 12, 25])
|
|
|
|
# not monotonic
|
|
res, lidx, ridx = index.join(other, how="inner", return_indexers=True)
|
|
|
|
# no guarantee of sortedness, so sort for comparison purposes
|
|
ind = res.argsort()
|
|
res = res.take(ind)
|
|
lidx = lidx.take(ind)
|
|
ridx = ridx.take(ind)
|
|
|
|
eres = Int64Index([2, 12])
|
|
elidx = np.array([1, 6], dtype=np.intp)
|
|
eridx = np.array([4, 1], dtype=np.intp)
|
|
|
|
assert isinstance(res, Int64Index)
|
|
tm.assert_index_equal(res, eres)
|
|
tm.assert_numpy_array_equal(lidx, elidx)
|
|
tm.assert_numpy_array_equal(ridx, eridx)
|
|
|
|
# monotonic
|
|
res, lidx, ridx = index.join(other_mono, how="inner", return_indexers=True)
|
|
|
|
res2 = index.intersection(other_mono)
|
|
tm.assert_index_equal(res, res2)
|
|
|
|
elidx = np.array([1, 6], dtype=np.intp)
|
|
eridx = np.array([1, 4], dtype=np.intp)
|
|
assert isinstance(res, Int64Index)
|
|
tm.assert_index_equal(res, eres)
|
|
tm.assert_numpy_array_equal(lidx, elidx)
|
|
tm.assert_numpy_array_equal(ridx, eridx)
|
|
|
|
def test_join_left(self):
|
|
index = self.create_index()
|
|
other = Int64Index([7, 12, 25, 1, 2, 5])
|
|
other_mono = Int64Index([1, 2, 5, 7, 12, 25])
|
|
|
|
# not monotonic
|
|
res, lidx, ridx = index.join(other, how="left", return_indexers=True)
|
|
eres = index
|
|
eridx = np.array([-1, 4, -1, -1, -1, -1, 1, -1, -1, -1], dtype=np.intp)
|
|
|
|
assert isinstance(res, Int64Index)
|
|
tm.assert_index_equal(res, eres)
|
|
assert lidx is None
|
|
tm.assert_numpy_array_equal(ridx, eridx)
|
|
|
|
# monotonic
|
|
res, lidx, ridx = index.join(other_mono, how="left", return_indexers=True)
|
|
eridx = np.array([-1, 1, -1, -1, -1, -1, 4, -1, -1, -1], dtype=np.intp)
|
|
assert isinstance(res, Int64Index)
|
|
tm.assert_index_equal(res, eres)
|
|
assert lidx is None
|
|
tm.assert_numpy_array_equal(ridx, eridx)
|
|
|
|
# non-unique
|
|
idx = Index([1, 1, 2, 5])
|
|
idx2 = Index([1, 2, 5, 7, 9])
|
|
res, lidx, ridx = idx2.join(idx, how="left", return_indexers=True)
|
|
eres = Index([1, 1, 2, 5, 7, 9]) # 1 is in idx2, so it should be x2
|
|
eridx = np.array([0, 1, 2, 3, -1, -1], dtype=np.intp)
|
|
elidx = np.array([0, 0, 1, 2, 3, 4], dtype=np.intp)
|
|
tm.assert_index_equal(res, eres)
|
|
tm.assert_numpy_array_equal(lidx, elidx)
|
|
tm.assert_numpy_array_equal(ridx, eridx)
|
|
|
|
def test_join_right(self):
|
|
index = self.create_index()
|
|
other = Int64Index([7, 12, 25, 1, 2, 5])
|
|
other_mono = Int64Index([1, 2, 5, 7, 12, 25])
|
|
|
|
# not monotonic
|
|
res, lidx, ridx = index.join(other, how="right", return_indexers=True)
|
|
eres = other
|
|
elidx = np.array([-1, 6, -1, -1, 1, -1], dtype=np.intp)
|
|
|
|
assert isinstance(other, Int64Index)
|
|
tm.assert_index_equal(res, eres)
|
|
tm.assert_numpy_array_equal(lidx, elidx)
|
|
assert ridx is None
|
|
|
|
# monotonic
|
|
res, lidx, ridx = index.join(other_mono, how="right", return_indexers=True)
|
|
eres = other_mono
|
|
elidx = np.array([-1, 1, -1, -1, 6, -1], dtype=np.intp)
|
|
assert isinstance(other, Int64Index)
|
|
tm.assert_index_equal(res, eres)
|
|
tm.assert_numpy_array_equal(lidx, elidx)
|
|
assert ridx is None
|
|
|
|
# non-unique
|
|
idx = Index([1, 1, 2, 5])
|
|
idx2 = Index([1, 2, 5, 7, 9])
|
|
res, lidx, ridx = idx.join(idx2, how="right", return_indexers=True)
|
|
eres = Index([1, 1, 2, 5, 7, 9]) # 1 is in idx2, so it should be x2
|
|
elidx = np.array([0, 1, 2, 3, -1, -1], dtype=np.intp)
|
|
eridx = np.array([0, 0, 1, 2, 3, 4], dtype=np.intp)
|
|
tm.assert_index_equal(res, eres)
|
|
tm.assert_numpy_array_equal(lidx, elidx)
|
|
tm.assert_numpy_array_equal(ridx, eridx)
|
|
|
|
def test_join_non_int_index(self):
|
|
index = self.create_index()
|
|
other = Index([3, 6, 7, 8, 10], dtype=object)
|
|
|
|
outer = index.join(other, how="outer")
|
|
outer2 = other.join(index, how="outer")
|
|
expected = Index([0, 2, 3, 4, 6, 7, 8, 10, 12, 14, 16, 18])
|
|
tm.assert_index_equal(outer, outer2)
|
|
tm.assert_index_equal(outer, expected)
|
|
|
|
inner = index.join(other, how="inner")
|
|
inner2 = other.join(index, how="inner")
|
|
expected = Index([6, 8, 10])
|
|
tm.assert_index_equal(inner, inner2)
|
|
tm.assert_index_equal(inner, expected)
|
|
|
|
left = index.join(other, how="left")
|
|
tm.assert_index_equal(left, index.astype(object))
|
|
|
|
left2 = other.join(index, how="left")
|
|
tm.assert_index_equal(left2, other)
|
|
|
|
right = index.join(other, how="right")
|
|
tm.assert_index_equal(right, other)
|
|
|
|
right2 = other.join(index, how="right")
|
|
tm.assert_index_equal(right2, index.astype(object))
|
|
|
|
def test_join_outer(self):
|
|
index = self.create_index()
|
|
other = Int64Index([7, 12, 25, 1, 2, 5])
|
|
other_mono = Int64Index([1, 2, 5, 7, 12, 25])
|
|
|
|
# not monotonic
|
|
# guarantee of sortedness
|
|
res, lidx, ridx = index.join(other, how="outer", return_indexers=True)
|
|
noidx_res = index.join(other, how="outer")
|
|
tm.assert_index_equal(res, noidx_res)
|
|
|
|
eres = Int64Index([0, 1, 2, 4, 5, 6, 7, 8, 10, 12, 14, 16, 18, 25])
|
|
elidx = np.array([0, -1, 1, 2, -1, 3, -1, 4, 5, 6, 7, 8, 9, -1], dtype=np.intp)
|
|
eridx = np.array(
|
|
[-1, 3, 4, -1, 5, -1, 0, -1, -1, 1, -1, -1, -1, 2], dtype=np.intp
|
|
)
|
|
|
|
assert isinstance(res, Int64Index)
|
|
tm.assert_index_equal(res, eres)
|
|
tm.assert_numpy_array_equal(lidx, elidx)
|
|
tm.assert_numpy_array_equal(ridx, eridx)
|
|
|
|
# monotonic
|
|
res, lidx, ridx = index.join(other_mono, how="outer", return_indexers=True)
|
|
noidx_res = index.join(other_mono, how="outer")
|
|
tm.assert_index_equal(res, noidx_res)
|
|
|
|
elidx = np.array([0, -1, 1, 2, -1, 3, -1, 4, 5, 6, 7, 8, 9, -1], dtype=np.intp)
|
|
eridx = np.array(
|
|
[-1, 0, 1, -1, 2, -1, 3, -1, -1, 4, -1, -1, -1, 5], dtype=np.intp
|
|
)
|
|
assert isinstance(res, Int64Index)
|
|
tm.assert_index_equal(res, eres)
|
|
tm.assert_numpy_array_equal(lidx, elidx)
|
|
tm.assert_numpy_array_equal(ridx, eridx)
|
|
|
|
|
|
class TestUInt64Index(NumericInt):
|
|
|
|
_dtype = "uint64"
|
|
_holder = UInt64Index
|
|
|
|
@pytest.fixture(
|
|
params=[
|
|
[2 ** 63, 2 ** 63 + 10, 2 ** 63 + 15, 2 ** 63 + 20, 2 ** 63 + 25],
|
|
[2 ** 63 + 25, 2 ** 63 + 20, 2 ** 63 + 15, 2 ** 63 + 10, 2 ** 63],
|
|
],
|
|
ids=["index_inc", "index_dec"],
|
|
)
|
|
def indices(self, request):
|
|
return UInt64Index(request.param)
|
|
|
|
@pytest.fixture
|
|
def index_large(self):
|
|
# large values used in TestUInt64Index where no compat needed with Int64/Float64
|
|
large = [2 ** 63, 2 ** 63 + 10, 2 ** 63 + 15, 2 ** 63 + 20, 2 ** 63 + 25]
|
|
return UInt64Index(large)
|
|
|
|
def create_index(self):
|
|
# compat with shared Int64/Float64 tests; use index_large for UInt64 only tests
|
|
return UInt64Index(np.arange(5, dtype="uint64"))
|
|
|
|
def test_constructor(self):
|
|
idx = UInt64Index([1, 2, 3])
|
|
res = Index([1, 2, 3], dtype=np.uint64)
|
|
tm.assert_index_equal(res, idx)
|
|
|
|
idx = UInt64Index([1, 2 ** 63])
|
|
res = Index([1, 2 ** 63], dtype=np.uint64)
|
|
tm.assert_index_equal(res, idx)
|
|
|
|
idx = UInt64Index([1, 2 ** 63])
|
|
res = Index([1, 2 ** 63])
|
|
tm.assert_index_equal(res, idx)
|
|
|
|
idx = Index([-1, 2 ** 63], dtype=object)
|
|
res = Index(np.array([-1, 2 ** 63], dtype=object))
|
|
tm.assert_index_equal(res, idx)
|
|
|
|
# https://github.com/pandas-dev/pandas/issues/29526
|
|
idx = UInt64Index([1, 2 ** 63 + 1], dtype=np.uint64)
|
|
res = Index([1, 2 ** 63 + 1], dtype=np.uint64)
|
|
tm.assert_index_equal(res, idx)
|
|
|
|
def test_get_indexer(self, index_large):
|
|
target = UInt64Index(np.arange(10).astype("uint64") * 5 + 2 ** 63)
|
|
indexer = index_large.get_indexer(target)
|
|
expected = np.array([0, -1, 1, 2, 3, 4, -1, -1, -1, -1], dtype=np.intp)
|
|
tm.assert_numpy_array_equal(indexer, expected)
|
|
|
|
target = UInt64Index(np.arange(10).astype("uint64") * 5 + 2 ** 63)
|
|
indexer = index_large.get_indexer(target, method="pad")
|
|
expected = np.array([0, 0, 1, 2, 3, 4, 4, 4, 4, 4], dtype=np.intp)
|
|
tm.assert_numpy_array_equal(indexer, expected)
|
|
|
|
target = UInt64Index(np.arange(10).astype("uint64") * 5 + 2 ** 63)
|
|
indexer = index_large.get_indexer(target, method="backfill")
|
|
expected = np.array([0, 1, 1, 2, 3, 4, -1, -1, -1, -1], dtype=np.intp)
|
|
tm.assert_numpy_array_equal(indexer, expected)
|
|
|
|
def test_intersection(self, index_large):
|
|
other = Index([2 ** 63, 2 ** 63 + 5, 2 ** 63 + 10, 2 ** 63 + 15, 2 ** 63 + 20])
|
|
result = index_large.intersection(other)
|
|
expected = Index(np.sort(np.intersect1d(index_large.values, other.values)))
|
|
tm.assert_index_equal(result, expected)
|
|
|
|
result = other.intersection(index_large)
|
|
expected = Index(
|
|
np.sort(np.asarray(np.intersect1d(index_large.values, other.values)))
|
|
)
|
|
tm.assert_index_equal(result, expected)
|
|
|
|
def test_join_inner(self, index_large):
|
|
other = UInt64Index(2 ** 63 + np.array([7, 12, 25, 1, 2, 10], dtype="uint64"))
|
|
other_mono = UInt64Index(
|
|
2 ** 63 + np.array([1, 2, 7, 10, 12, 25], dtype="uint64")
|
|
)
|
|
|
|
# not monotonic
|
|
res, lidx, ridx = index_large.join(other, how="inner", return_indexers=True)
|
|
|
|
# no guarantee of sortedness, so sort for comparison purposes
|
|
ind = res.argsort()
|
|
res = res.take(ind)
|
|
lidx = lidx.take(ind)
|
|
ridx = ridx.take(ind)
|
|
|
|
eres = UInt64Index(2 ** 63 + np.array([10, 25], dtype="uint64"))
|
|
elidx = np.array([1, 4], dtype=np.intp)
|
|
eridx = np.array([5, 2], dtype=np.intp)
|
|
|
|
assert isinstance(res, UInt64Index)
|
|
tm.assert_index_equal(res, eres)
|
|
tm.assert_numpy_array_equal(lidx, elidx)
|
|
tm.assert_numpy_array_equal(ridx, eridx)
|
|
|
|
# monotonic
|
|
res, lidx, ridx = index_large.join(
|
|
other_mono, how="inner", return_indexers=True
|
|
)
|
|
|
|
res2 = index_large.intersection(other_mono)
|
|
tm.assert_index_equal(res, res2)
|
|
|
|
elidx = np.array([1, 4], dtype=np.intp)
|
|
eridx = np.array([3, 5], dtype=np.intp)
|
|
|
|
assert isinstance(res, UInt64Index)
|
|
tm.assert_index_equal(res, eres)
|
|
tm.assert_numpy_array_equal(lidx, elidx)
|
|
tm.assert_numpy_array_equal(ridx, eridx)
|
|
|
|
def test_join_left(self, index_large):
|
|
other = UInt64Index(2 ** 63 + np.array([7, 12, 25, 1, 2, 10], dtype="uint64"))
|
|
other_mono = UInt64Index(
|
|
2 ** 63 + np.array([1, 2, 7, 10, 12, 25], dtype="uint64")
|
|
)
|
|
|
|
# not monotonic
|
|
res, lidx, ridx = index_large.join(other, how="left", return_indexers=True)
|
|
eres = index_large
|
|
eridx = np.array([-1, 5, -1, -1, 2], dtype=np.intp)
|
|
|
|
assert isinstance(res, UInt64Index)
|
|
tm.assert_index_equal(res, eres)
|
|
assert lidx is None
|
|
tm.assert_numpy_array_equal(ridx, eridx)
|
|
|
|
# monotonic
|
|
res, lidx, ridx = index_large.join(other_mono, how="left", return_indexers=True)
|
|
eridx = np.array([-1, 3, -1, -1, 5], dtype=np.intp)
|
|
|
|
assert isinstance(res, UInt64Index)
|
|
tm.assert_index_equal(res, eres)
|
|
assert lidx is None
|
|
tm.assert_numpy_array_equal(ridx, eridx)
|
|
|
|
# non-unique
|
|
idx = UInt64Index(2 ** 63 + np.array([1, 1, 2, 5], dtype="uint64"))
|
|
idx2 = UInt64Index(2 ** 63 + np.array([1, 2, 5, 7, 9], dtype="uint64"))
|
|
res, lidx, ridx = idx2.join(idx, how="left", return_indexers=True)
|
|
|
|
# 1 is in idx2, so it should be x2
|
|
eres = UInt64Index(2 ** 63 + np.array([1, 1, 2, 5, 7, 9], dtype="uint64"))
|
|
eridx = np.array([0, 1, 2, 3, -1, -1], dtype=np.intp)
|
|
elidx = np.array([0, 0, 1, 2, 3, 4], dtype=np.intp)
|
|
|
|
tm.assert_index_equal(res, eres)
|
|
tm.assert_numpy_array_equal(lidx, elidx)
|
|
tm.assert_numpy_array_equal(ridx, eridx)
|
|
|
|
def test_join_right(self, index_large):
|
|
other = UInt64Index(2 ** 63 + np.array([7, 12, 25, 1, 2, 10], dtype="uint64"))
|
|
other_mono = UInt64Index(
|
|
2 ** 63 + np.array([1, 2, 7, 10, 12, 25], dtype="uint64")
|
|
)
|
|
|
|
# not monotonic
|
|
res, lidx, ridx = index_large.join(other, how="right", return_indexers=True)
|
|
eres = other
|
|
elidx = np.array([-1, -1, 4, -1, -1, 1], dtype=np.intp)
|
|
|
|
tm.assert_numpy_array_equal(lidx, elidx)
|
|
assert isinstance(other, UInt64Index)
|
|
tm.assert_index_equal(res, eres)
|
|
assert ridx is None
|
|
|
|
# monotonic
|
|
res, lidx, ridx = index_large.join(
|
|
other_mono, how="right", return_indexers=True
|
|
)
|
|
eres = other_mono
|
|
elidx = np.array([-1, -1, -1, 1, -1, 4], dtype=np.intp)
|
|
|
|
assert isinstance(other, UInt64Index)
|
|
tm.assert_numpy_array_equal(lidx, elidx)
|
|
tm.assert_index_equal(res, eres)
|
|
assert ridx is None
|
|
|
|
# non-unique
|
|
idx = UInt64Index(2 ** 63 + np.array([1, 1, 2, 5], dtype="uint64"))
|
|
idx2 = UInt64Index(2 ** 63 + np.array([1, 2, 5, 7, 9], dtype="uint64"))
|
|
res, lidx, ridx = idx.join(idx2, how="right", return_indexers=True)
|
|
|
|
# 1 is in idx2, so it should be x2
|
|
eres = UInt64Index(2 ** 63 + np.array([1, 1, 2, 5, 7, 9], dtype="uint64"))
|
|
elidx = np.array([0, 1, 2, 3, -1, -1], dtype=np.intp)
|
|
eridx = np.array([0, 0, 1, 2, 3, 4], dtype=np.intp)
|
|
|
|
tm.assert_index_equal(res, eres)
|
|
tm.assert_numpy_array_equal(lidx, elidx)
|
|
tm.assert_numpy_array_equal(ridx, eridx)
|
|
|
|
def test_join_non_int_index(self, index_large):
|
|
other = Index(
|
|
2 ** 63 + np.array([1, 5, 7, 10, 20], dtype="uint64"), dtype=object
|
|
)
|
|
|
|
outer = index_large.join(other, how="outer")
|
|
outer2 = other.join(index_large, how="outer")
|
|
expected = Index(
|
|
2 ** 63 + np.array([0, 1, 5, 7, 10, 15, 20, 25], dtype="uint64")
|
|
)
|
|
tm.assert_index_equal(outer, outer2)
|
|
tm.assert_index_equal(outer, expected)
|
|
|
|
inner = index_large.join(other, how="inner")
|
|
inner2 = other.join(index_large, how="inner")
|
|
expected = Index(2 ** 63 + np.array([10, 20], dtype="uint64"))
|
|
tm.assert_index_equal(inner, inner2)
|
|
tm.assert_index_equal(inner, expected)
|
|
|
|
left = index_large.join(other, how="left")
|
|
tm.assert_index_equal(left, index_large.astype(object))
|
|
|
|
left2 = other.join(index_large, how="left")
|
|
tm.assert_index_equal(left2, other)
|
|
|
|
right = index_large.join(other, how="right")
|
|
tm.assert_index_equal(right, other)
|
|
|
|
right2 = other.join(index_large, how="right")
|
|
tm.assert_index_equal(right2, index_large.astype(object))
|
|
|
|
def test_join_outer(self, index_large):
|
|
other = UInt64Index(2 ** 63 + np.array([7, 12, 25, 1, 2, 10], dtype="uint64"))
|
|
other_mono = UInt64Index(
|
|
2 ** 63 + np.array([1, 2, 7, 10, 12, 25], dtype="uint64")
|
|
)
|
|
|
|
# not monotonic
|
|
# guarantee of sortedness
|
|
res, lidx, ridx = index_large.join(other, how="outer", return_indexers=True)
|
|
noidx_res = index_large.join(other, how="outer")
|
|
tm.assert_index_equal(res, noidx_res)
|
|
|
|
eres = UInt64Index(
|
|
2 ** 63 + np.array([0, 1, 2, 7, 10, 12, 15, 20, 25], dtype="uint64")
|
|
)
|
|
elidx = np.array([0, -1, -1, -1, 1, -1, 2, 3, 4], dtype=np.intp)
|
|
eridx = np.array([-1, 3, 4, 0, 5, 1, -1, -1, 2], dtype=np.intp)
|
|
|
|
assert isinstance(res, UInt64Index)
|
|
tm.assert_index_equal(res, eres)
|
|
tm.assert_numpy_array_equal(lidx, elidx)
|
|
tm.assert_numpy_array_equal(ridx, eridx)
|
|
|
|
# monotonic
|
|
res, lidx, ridx = index_large.join(
|
|
other_mono, how="outer", return_indexers=True
|
|
)
|
|
noidx_res = index_large.join(other_mono, how="outer")
|
|
tm.assert_index_equal(res, noidx_res)
|
|
|
|
elidx = np.array([0, -1, -1, -1, 1, -1, 2, 3, 4], dtype=np.intp)
|
|
eridx = np.array([-1, 0, 1, 2, 3, 4, -1, -1, 5], dtype=np.intp)
|
|
|
|
assert isinstance(res, UInt64Index)
|
|
tm.assert_index_equal(res, eres)
|
|
tm.assert_numpy_array_equal(lidx, elidx)
|
|
tm.assert_numpy_array_equal(ridx, eridx)
|
|
|
|
|
|
@pytest.mark.parametrize("dtype", ["int64", "uint64"])
|
|
def test_int_float_union_dtype(dtype):
|
|
# https://github.com/pandas-dev/pandas/issues/26778
|
|
# [u]int | float -> float
|
|
index = pd.Index([0, 2, 3], dtype=dtype)
|
|
other = pd.Float64Index([0.5, 1.5])
|
|
expected = pd.Float64Index([0.0, 0.5, 1.5, 2.0, 3.0])
|
|
result = index.union(other)
|
|
tm.assert_index_equal(result, expected)
|
|
|
|
result = other.union(index)
|
|
tm.assert_index_equal(result, expected)
|
|
|
|
|
|
def test_range_float_union_dtype():
|
|
# https://github.com/pandas-dev/pandas/issues/26778
|
|
index = pd.RangeIndex(start=0, stop=3)
|
|
other = pd.Float64Index([0.5, 1.5])
|
|
result = index.union(other)
|
|
expected = pd.Float64Index([0.0, 0.5, 1, 1.5, 2.0])
|
|
tm.assert_index_equal(result, expected)
|
|
|
|
result = other.union(index)
|
|
tm.assert_index_equal(result, expected)
|
|
|
|
|
|
def test_uint_index_does_not_convert_to_float64():
|
|
# https://github.com/pandas-dev/pandas/issues/28279
|
|
# https://github.com/pandas-dev/pandas/issues/28023
|
|
series = pd.Series(
|
|
[0, 1, 2, 3, 4, 5],
|
|
index=[
|
|
7606741985629028552,
|
|
17876870360202815256,
|
|
17876870360202815256,
|
|
13106359306506049338,
|
|
8991270399732411471,
|
|
8991270399732411472,
|
|
],
|
|
)
|
|
|
|
result = series.loc[[7606741985629028552, 17876870360202815256]]
|
|
|
|
expected = UInt64Index(
|
|
[7606741985629028552, 17876870360202815256, 17876870360202815256],
|
|
dtype="uint64",
|
|
)
|
|
tm.assert_index_equal(result.index, expected)
|
|
|
|
tm.assert_equal(result, series[:3])
|