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TST: Reorganize IntervalIndex tests (pandas-dev#28800)
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import numpy as np | ||
import pytest | ||
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from pandas import IntervalIndex, Series, date_range | ||
from pandas.tests.indexes.common import Base | ||
import pandas.util.testing as tm | ||
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class TestBase(Base): | ||
""" | ||
Tests specific to the shared common index tests; unrelated tests should be placed | ||
in test_interval.py or the specific test file (e.g. test_astype.py) | ||
""" | ||
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_holder = IntervalIndex | ||
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def setup_method(self, method): | ||
self.index = IntervalIndex.from_arrays([0, 1], [1, 2]) | ||
self.index_with_nan = IntervalIndex.from_tuples([(0, 1), np.nan, (1, 2)]) | ||
self.indices = dict(intervalIndex=tm.makeIntervalIndex(10)) | ||
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def create_index(self, closed="right"): | ||
return IntervalIndex.from_breaks(range(11), closed=closed) | ||
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def test_equals(self, closed): | ||
expected = IntervalIndex.from_breaks(np.arange(5), closed=closed) | ||
assert expected.equals(expected) | ||
assert expected.equals(expected.copy()) | ||
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assert not expected.equals(expected.astype(object)) | ||
assert not expected.equals(np.array(expected)) | ||
assert not expected.equals(list(expected)) | ||
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assert not expected.equals([1, 2]) | ||
assert not expected.equals(np.array([1, 2])) | ||
assert not expected.equals(date_range("20130101", periods=2)) | ||
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expected_name1 = IntervalIndex.from_breaks( | ||
np.arange(5), closed=closed, name="foo" | ||
) | ||
expected_name2 = IntervalIndex.from_breaks( | ||
np.arange(5), closed=closed, name="bar" | ||
) | ||
assert expected.equals(expected_name1) | ||
assert expected_name1.equals(expected_name2) | ||
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for other_closed in {"left", "right", "both", "neither"} - {closed}: | ||
expected_other_closed = IntervalIndex.from_breaks( | ||
np.arange(5), closed=other_closed | ||
) | ||
assert not expected.equals(expected_other_closed) | ||
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def test_repr_max_seq_item_setting(self): | ||
# override base test: not a valid repr as we use interval notation | ||
pass | ||
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def test_repr_roundtrip(self): | ||
# override base test: not a valid repr as we use interval notation | ||
pass | ||
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def test_take(self, closed): | ||
index = self.create_index(closed=closed) | ||
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result = index.take(range(10)) | ||
tm.assert_index_equal(result, index) | ||
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result = index.take([0, 0, 1]) | ||
expected = IntervalIndex.from_arrays([0, 0, 1], [1, 1, 2], closed=closed) | ||
tm.assert_index_equal(result, expected) | ||
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@pytest.mark.parametrize("klass", [list, tuple, np.array, Series]) | ||
def test_where(self, closed, klass): | ||
idx = self.create_index(closed=closed) | ||
cond = [True] * len(idx) | ||
expected = idx | ||
result = expected.where(klass(cond)) | ||
tm.assert_index_equal(result, expected) | ||
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cond = [False] + [True] * len(idx[1:]) | ||
expected = IntervalIndex([np.nan] + idx[1:].tolist()) | ||
result = idx.where(klass(cond)) | ||
tm.assert_index_equal(result, expected) |
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import numpy as np | ||
import pytest | ||
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from pandas import DataFrame, IntervalIndex, Series, Timedelta, Timestamp | ||
import pandas.util.testing as tm | ||
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class TestIntervalIndexRendering: | ||
def test_frame_repr(self): | ||
# https://github.com/pandas-dev/pandas/pull/24134/files | ||
df = DataFrame( | ||
{"A": [1, 2, 3, 4]}, index=IntervalIndex.from_breaks([0, 1, 2, 3, 4]) | ||
) | ||
result = repr(df) | ||
expected = " A\n(0, 1] 1\n(1, 2] 2\n(2, 3] 3\n(3, 4] 4" | ||
assert result == expected | ||
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@pytest.mark.parametrize( | ||
"constructor,expected", | ||
[ | ||
( | ||
Series, | ||
( | ||
"(0.0, 1.0] a\n" | ||
"NaN b\n" | ||
"(2.0, 3.0] c\n" | ||
"dtype: object" | ||
), | ||
), | ||
(DataFrame, (" 0\n(0.0, 1.0] a\nNaN b\n(2.0, 3.0] c")), | ||
], | ||
) | ||
def test_repr_missing(self, constructor, expected): | ||
# GH 25984 | ||
index = IntervalIndex.from_tuples([(0, 1), np.nan, (2, 3)]) | ||
obj = constructor(list("abc"), index=index) | ||
result = repr(obj) | ||
assert result == expected | ||
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@pytest.mark.parametrize( | ||
"tuples, closed, expected_data", | ||
[ | ||
([(0, 1), (1, 2), (2, 3)], "left", ["[0, 1)", "[1, 2)", "[2, 3)"]), | ||
( | ||
[(0.5, 1.0), np.nan, (2.0, 3.0)], | ||
"right", | ||
["(0.5, 1.0]", "NaN", "(2.0, 3.0]"], | ||
), | ||
( | ||
[ | ||
(Timestamp("20180101"), Timestamp("20180102")), | ||
np.nan, | ||
((Timestamp("20180102"), Timestamp("20180103"))), | ||
], | ||
"both", | ||
["[2018-01-01, 2018-01-02]", "NaN", "[2018-01-02, 2018-01-03]"], | ||
), | ||
( | ||
[ | ||
(Timedelta("0 days"), Timedelta("1 days")), | ||
(Timedelta("1 days"), Timedelta("2 days")), | ||
np.nan, | ||
], | ||
"neither", | ||
[ | ||
"(0 days 00:00:00, 1 days 00:00:00)", | ||
"(1 days 00:00:00, 2 days 00:00:00)", | ||
"NaN", | ||
], | ||
), | ||
], | ||
) | ||
def test_to_native_types(self, tuples, closed, expected_data): | ||
# GH 28210 | ||
index = IntervalIndex.from_tuples(tuples, closed=closed) | ||
result = index.to_native_types() | ||
expected = np.array(expected_data) | ||
tm.assert_numpy_array_equal(result, expected) |
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