Inzynierka/Lib/site-packages/pandas/tests/indexes/interval/test_formats.py
2023-06-02 12:51:02 +02:00

106 lines
3.2 KiB
Python

import numpy as np
import pytest
from pandas import (
DataFrame,
Index,
Interval,
IntervalIndex,
Series,
Timedelta,
Timestamp,
)
import pandas._testing as tm
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
@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
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, 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._format_native_types()
expected = np.array(expected_data)
tm.assert_numpy_array_equal(result, expected)