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import numpy as np import pytest from pandas._config import using_pyarrow_string_dtype from pandas import ( DataFrame, DatetimeIndex, Index, Interval, IntervalIndex, Series, Timedelta, Timestamp, ) import pandas._testing as tm class TestIntervalIndexRendering: # TODO: this is a test for DataFrame/Series, not IntervalIndex @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, using_infer_string, request): # GH 25984 if using_infer_string and constructor is Series: request.applymarker(pytest.mark.xfail(reason="repr different")) index = IntervalIndex.from_tuples([(0, 1), np.nan, (2, 3)]) obj = constructor(list("abc"), index=index) result = repr(obj) assert result == expected @pytest.mark.xfail(using_pyarrow_string_dtype(), reason="repr different") def test_repr_floats(self): # GH 32553 markers = Series( ["foo", "bar"], index=IntervalIndex( [ Interval(left, right) for left, right in zip( Index([329.973, 345.137], dtype="float64"), Index([345.137, 360.191], dtype="float64"), ) ] ), ) result = str(markers) expected = "(329.973, 345.137] foo\n(345.137, 360.191] bar\ndtype: object" assert result == expected @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 00:00:00, 2018-01-02 00:00:00]", "NaN", "[2018-01-02 00:00:00, 2018-01-03 00:00:00]", ], ), ( [ (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_get_values_for_csv(self, tuples, closed, expected_data): # GH 28210 index = IntervalIndex.from_tuples(tuples, closed=closed) result = index._get_values_for_csv(na_rep="NaN") expected = np.array(expected_data) tm.assert_numpy_array_equal(result, expected) def test_timestamp_with_timezone(self, unit): # GH 55035 left = DatetimeIndex(["2020-01-01"], dtype=f"M8[{unit}, UTC]") right = DatetimeIndex(["2020-01-02"], dtype=f"M8[{unit}, UTC]") index = IntervalIndex.from_arrays(left, right) result = repr(index) expected = ( "IntervalIndex([(2020-01-01 00:00:00+00:00, 2020-01-02 00:00:00+00:00]], " f"dtype='interval[datetime64[{unit}, UTC], right]')" ) assert result == expected
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