python/pyspark/pandas/tests/resample/test_frame.py - master - githubmirror/spark

python/pyspark/pandas/tests/resample/test_frame.py
147 строк5 KB
Takuya Ueshin
[SPARK-55293][PS][TESTS][FOLLOW-UP] Avoid more old offset aliases
03 фев 2026, 08:37
03 фев 2026, 08:378ffd150
#
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements.  See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "License"); you may not use this file except in compliance with
# the License.  You may obtain a copy of the License at
#
#    http://www.apache.org/licenses/LICENSE-2.0
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# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#


import datetime

import numpy as np
import pandas as pd

from pyspark import pandas as ps
from pyspark.testing.pandasutils import PandasOnSparkTestCase, TestUtils


class ResampleFrameMixin:
    @property
    def pdf1(self):
        np.random.seed(11)
        dates = [
            pd.NaT,
            datetime.datetime(2011, 12, 31),
            datetime.datetime(2011, 12, 31, 0, 0, 1),
            datetime.datetime(2011, 12, 31, 23, 59, 59),
            datetime.datetime(2012, 1, 1),
            datetime.datetime(2012, 1, 1, 0, 0, 1),
            pd.NaT,
            datetime.datetime(2012, 1, 1, 23, 59, 59),
            datetime.datetime(2012, 1, 2),
            pd.NaT,
            datetime.datetime(2012, 1, 30, 23, 59, 59),
            datetime.datetime(2012, 1, 31),
            datetime.datetime(2012, 1, 31, 0, 0, 1),
            datetime.datetime(2012, 3, 31),
            datetime.datetime(2013, 5, 3),
            datetime.datetime(2022, 5, 3),
        ]
        return pd.DataFrame(
            np.random.rand(len(dates), 2), index=pd.DatetimeIndex(dates), columns=list("AB")
        )

    @property
    def pdf2(self):
        np.random.seed(22)
        dates = [
            datetime.datetime(2022, 5, 1, 4, 5, 6),
            datetime.datetime(2022, 5, 3),
            datetime.datetime(2022, 5, 3, 23, 59, 59),
            datetime.datetime(2022, 5, 4),
            pd.NaT,
            datetime.datetime(2022, 5, 4, 0, 0, 1),
            datetime.datetime(2022, 5, 11),
        ]
        return pd.DataFrame(
            np.random.rand(len(dates), 2), index=pd.DatetimeIndex(dates), columns=list("AB")
        )

    @property
    def pdf3(self):
        np.random.seed(22)
        index = pd.date_range(start="2011-01-02", end="2022-05-01", freq="1D")
        return pd.DataFrame(np.random.rand(len(index), 2), index=index, columns=list("AB"))

    @property
    def pdf4(self):
        np.random.seed(33)
        index = pd.date_range(start="2020-12-12", end="2022-05-01", freq="1h")
        return pd.DataFrame(np.random.rand(len(index), 2), index=index, columns=list("AB"))

    @property
    def pdf5(self):
        np.random.seed(44)
        index = pd.date_range(start="2021-12-30 03:04:05", end="2022-01-02 06:07:08", freq="1min")
        return pd.DataFrame(np.random.rand(len(index), 2), index=index, columns=list("AB"))

    @property
    def pdf6(self):
        np.random.seed(55)
        index = pd.date_range(start="2022-05-02 03:04:05", end="2022-05-02 06:07:08", freq="1s")
        return pd.DataFrame(np.random.rand(len(index), 2), index=index, columns=list("AB"))

    @property
    def psdf1(self):
        return ps.from_pandas(self.pdf1)

    @property
    def psdf2(self):
        return ps.from_pandas(self.pdf2)

    @property
    def psdf3(self):
        return ps.from_pandas(self.pdf3)

    @property
    def psdf4(self):
        return ps.from_pandas(self.pdf4)

    @property
    def psdf5(self):
        return ps.from_pandas(self.pdf5)

    @property
    def psdf6(self):
        return ps.from_pandas(self.pdf6)

    def _test_resample(self, pobj, psobj, rules, closed, label, func):
        for rule in rules:
            p_resample = pobj.resample(rule=rule, closed=closed, label=label)
            ps_resample = psobj.resample(rule=rule, closed=closed, label=label)
            self.assert_eq(
                getattr(p_resample, func)().sort_index(),
                getattr(ps_resample, func)().sort_index(),
                almost=True,
                check_exact=False,
            )

    def test_dataframe_resample(self):
        self._test_resample(self.pdf4, self.psdf4, ["11h", "21D"], "left", None, "mean")
        self._test_resample(self.pdf5, self.psdf5, ["55min", "2h", "D"], "left", "left", "std")
        self._test_resample(self.pdf6, self.psdf6, ["29s", "10min", "3h"], "left", "right", "var")

        with self.assertRaisesRegex(ValueError, "rule code YE-DEC is not supported"):
            self._test_resample(self.pdf2, self.psdf2, ["3YE", "11ME", "D"], None, "left", "max")
        with self.assertRaisesRegex(ValueError, "rule code YE-DEC is not supported"):
            self._test_resample(self.pdf1, self.psdf1, ["3YE", "9ME", "17D"], None, None, "min")


class ResampleFrameTests(ResampleFrameMixin, PandasOnSparkTestCase, TestUtils):
    pass


if __name__ == "__main__":
    from pyspark.testing import main

    main()