3RNN/Lib/site-packages/pandas/tests/frame/methods/test_truncate.py

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2024-05-26 19:49:15 +02:00
import numpy as np
import pytest
import pandas as pd
from pandas import (
DataFrame,
DatetimeIndex,
Index,
Series,
date_range,
)
import pandas._testing as tm
class TestDataFrameTruncate:
def test_truncate(self, datetime_frame, frame_or_series):
ts = datetime_frame[::3]
ts = tm.get_obj(ts, frame_or_series)
start, end = datetime_frame.index[3], datetime_frame.index[6]
start_missing = datetime_frame.index[2]
end_missing = datetime_frame.index[7]
# neither specified
truncated = ts.truncate()
tm.assert_equal(truncated, ts)
# both specified
expected = ts[1:3]
truncated = ts.truncate(start, end)
tm.assert_equal(truncated, expected)
truncated = ts.truncate(start_missing, end_missing)
tm.assert_equal(truncated, expected)
# start specified
expected = ts[1:]
truncated = ts.truncate(before=start)
tm.assert_equal(truncated, expected)
truncated = ts.truncate(before=start_missing)
tm.assert_equal(truncated, expected)
# end specified
expected = ts[:3]
truncated = ts.truncate(after=end)
tm.assert_equal(truncated, expected)
truncated = ts.truncate(after=end_missing)
tm.assert_equal(truncated, expected)
# corner case, empty series/frame returned
truncated = ts.truncate(after=ts.index[0] - ts.index.freq)
assert len(truncated) == 0
truncated = ts.truncate(before=ts.index[-1] + ts.index.freq)
assert len(truncated) == 0
msg = "Truncate: 2000-01-06 00:00:00 must be after 2000-05-16 00:00:00"
with pytest.raises(ValueError, match=msg):
ts.truncate(
before=ts.index[-1] - ts.index.freq, after=ts.index[0] + ts.index.freq
)
def test_truncate_nonsortedindex(self, frame_or_series):
# GH#17935
obj = DataFrame({"A": ["a", "b", "c", "d", "e"]}, index=[5, 3, 2, 9, 0])
obj = tm.get_obj(obj, frame_or_series)
msg = "truncate requires a sorted index"
with pytest.raises(ValueError, match=msg):
obj.truncate(before=3, after=9)
def test_sort_values_nonsortedindex(self):
rng = date_range("2011-01-01", "2012-01-01", freq="W")
ts = DataFrame(
{
"A": np.random.default_rng(2).standard_normal(len(rng)),
"B": np.random.default_rng(2).standard_normal(len(rng)),
},
index=rng,
)
decreasing = ts.sort_values("A", ascending=False)
msg = "truncate requires a sorted index"
with pytest.raises(ValueError, match=msg):
decreasing.truncate(before="2011-11", after="2011-12")
def test_truncate_nonsortedindex_axis1(self):
# GH#17935
df = DataFrame(
{
3: np.random.default_rng(2).standard_normal(5),
20: np.random.default_rng(2).standard_normal(5),
2: np.random.default_rng(2).standard_normal(5),
0: np.random.default_rng(2).standard_normal(5),
},
columns=[3, 20, 2, 0],
)
msg = "truncate requires a sorted index"
with pytest.raises(ValueError, match=msg):
df.truncate(before=2, after=20, axis=1)
@pytest.mark.parametrize(
"before, after, indices",
[(1, 2, [2, 1]), (None, 2, [2, 1, 0]), (1, None, [3, 2, 1])],
)
@pytest.mark.parametrize("dtyp", [*tm.ALL_REAL_NUMPY_DTYPES, "datetime64[ns]"])
def test_truncate_decreasing_index(
self, before, after, indices, dtyp, frame_or_series
):
# https://github.com/pandas-dev/pandas/issues/33756
idx = Index([3, 2, 1, 0], dtype=dtyp)
if isinstance(idx, DatetimeIndex):
before = pd.Timestamp(before) if before is not None else None
after = pd.Timestamp(after) if after is not None else None
indices = [pd.Timestamp(i) for i in indices]
values = frame_or_series(range(len(idx)), index=idx)
result = values.truncate(before=before, after=after)
expected = values.loc[indices]
tm.assert_equal(result, expected)
def test_truncate_multiindex(self, frame_or_series):
# GH 34564
mi = pd.MultiIndex.from_product([[1, 2, 3, 4], ["A", "B"]], names=["L1", "L2"])
s1 = DataFrame(range(mi.shape[0]), index=mi, columns=["col"])
s1 = tm.get_obj(s1, frame_or_series)
result = s1.truncate(before=2, after=3)
df = DataFrame.from_dict(
{"L1": [2, 2, 3, 3], "L2": ["A", "B", "A", "B"], "col": [2, 3, 4, 5]}
)
expected = df.set_index(["L1", "L2"])
expected = tm.get_obj(expected, frame_or_series)
tm.assert_equal(result, expected)
def test_truncate_index_only_one_unique_value(self, frame_or_series):
# GH 42365
obj = Series(0, index=date_range("2021-06-30", "2021-06-30")).repeat(5)
if frame_or_series is DataFrame:
obj = obj.to_frame(name="a")
truncated = obj.truncate("2021-06-28", "2021-07-01")
tm.assert_equal(truncated, obj)