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| import numpy as np
| import pytest
|
| 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
|
| def test_repr_floats(self):
| # GH 32553
|
| markers = Series(
| [1, 2],
| 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] 1\n(345.137, 360.191] 2\ndtype: int64"
| assert result == expected
|
| @pytest.mark.filterwarnings(
| "ignore:invalid value encountered in cast:RuntimeWarning"
| )
| @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
|
|
