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#
# 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
#
# 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 numpy as np
import pandas as pd
import pyspark.pandas as ps
from pyspark.testing.pandasutils import PandasOnSparkTestCase, TestUtils
from pyspark.pandas.window import Rolling
class RollingTest(PandasOnSparkTestCase, TestUtils):
def test_rolling_error(self):
with self.assertRaisesRegex(ValueError, "window must be >= 0"):
ps.range(10).rolling(window=-1)
with self.assertRaisesRegex(ValueError, "min_periods must be >= 0"):
ps.range(10).rolling(window=1, min_periods=-1)
with self.assertRaisesRegex(
TypeError, "psdf_or_psser must be a series or dataframe; however, got:.*int"
):
Rolling(1, 2)
def _test_rolling_func(self, f):
pser = pd.Series([1, 2, 3], index=np.random.rand(3), name="a")
psser = ps.from_pandas(pser)
self.assert_eq(getattr(psser.rolling(2), f)(), getattr(pser.rolling(2), f)())
self.assert_eq(getattr(psser.rolling(2), f)().sum(), getattr(pser.rolling(2), f)().sum())
# Multiindex
pser = pd.Series(
[1, 2, 3],
index=pd.MultiIndex.from_tuples([("a", "x"), ("a", "y"), ("b", "z")]),
name="a",
)
psser = ps.from_pandas(pser)
self.assert_eq(getattr(psser.rolling(2), f)(), getattr(pser.rolling(2), f)())
pdf = pd.DataFrame(
{"a": [1.0, 2.0, 3.0, 2.0], "b": [4.0, 2.0, 3.0, 1.0]}, index=np.random.rand(4)
)
psdf = ps.from_pandas(pdf)
self.assert_eq(getattr(psdf.rolling(2), f)(), getattr(pdf.rolling(2), f)())
self.assert_eq(getattr(psdf.rolling(2), f)().sum(), getattr(pdf.rolling(2), f)().sum())
# Multiindex column
columns = pd.MultiIndex.from_tuples([("a", "x"), ("a", "y")])
pdf.columns = columns
psdf.columns = columns
self.assert_eq(getattr(psdf.rolling(2), f)(), getattr(pdf.rolling(2), f)())
def test_rolling_min(self):
self._test_rolling_func("min")
def test_rolling_max(self):
self._test_rolling_func("max")
def test_rolling_mean(self):
self._test_rolling_func("mean")
def test_rolling_sum(self):
self._test_rolling_func("sum")
def test_rolling_count(self):
self._test_rolling_func("count")
def test_rolling_std(self):
self._test_rolling_func("std")
def test_rolling_var(self):
self._test_rolling_func("var")
def _test_groupby_rolling_func(self, f):
pser = pd.Series([1, 2, 3, 2], index=np.random.rand(4), name="a")
psser = ps.from_pandas(pser)
self.assert_eq(
getattr(psser.groupby(psser).rolling(2), f)().sort_index(),
getattr(pser.groupby(pser).rolling(2), f)().sort_index(),
)
self.assert_eq(
getattr(psser.groupby(psser).rolling(2), f)().sum(),
getattr(pser.groupby(pser).rolling(2), f)().sum(),
)
# Multiindex
pser = pd.Series(
[1, 2, 3, 2],
index=pd.MultiIndex.from_tuples([("a", "x"), ("a", "y"), ("b", "z"), ("c", "z")]),
name="a",
)
psser = ps.from_pandas(pser)
self.assert_eq(
getattr(psser.groupby(psser).rolling(2), f)().sort_index(),
getattr(pser.groupby(pser).rolling(2), f)().sort_index(),
)
pdf = pd.DataFrame({"a": [1.0, 2.0, 3.0, 2.0], "b": [4.0, 2.0, 3.0, 1.0]})
psdf = ps.from_pandas(pdf)
self.assert_eq(
getattr(psdf.groupby(psdf.a).rolling(2), f)().sort_index(),
getattr(pdf.groupby(pdf.a).rolling(2), f)().sort_index(),
)
self.assert_eq(
getattr(psdf.groupby(psdf.a).rolling(2), f)().sum(),
getattr(pdf.groupby(pdf.a).rolling(2), f)().sum(),
)
self.assert_eq(
getattr(psdf.groupby(psdf.a + 1).rolling(2), f)().sort_index(),
getattr(pdf.groupby(pdf.a + 1).rolling(2), f)().sort_index(),
)
self.assert_eq(
getattr(psdf.b.groupby(psdf.a).rolling(2), f)().sort_index(),
getattr(pdf.b.groupby(pdf.a).rolling(2), f)().sort_index(),
)
self.assert_eq(
getattr(psdf.groupby(psdf.a)["b"].rolling(2), f)().sort_index(),
getattr(pdf.groupby(pdf.a)["b"].rolling(2), f)().sort_index(),
)
self.assert_eq(
getattr(psdf.groupby(psdf.a)[["b"]].rolling(2), f)().sort_index(),
getattr(pdf.groupby(pdf.a)[["b"]].rolling(2), f)().sort_index(),
)
# Multiindex column
columns = pd.MultiIndex.from_tuples([("a", "x"), ("a", "y")])
pdf.columns = columns
psdf.columns = columns
self.assert_eq(
getattr(psdf.groupby(("a", "x")).rolling(2), f)().sort_index(),
getattr(pdf.groupby(("a", "x")).rolling(2), f)().sort_index(),
)
self.assert_eq(
getattr(psdf.groupby([("a", "x"), ("a", "y")]).rolling(2), f)().sort_index(),
getattr(pdf.groupby([("a", "x"), ("a", "y")]).rolling(2), f)().sort_index(),
)
def test_groupby_rolling_count(self):
self._test_groupby_rolling_func("count")
def test_groupby_rolling_min(self):
self._test_groupby_rolling_func("min")
def test_groupby_rolling_max(self):
self._test_groupby_rolling_func("max")
def test_groupby_rolling_mean(self):
self._test_groupby_rolling_func("mean")
def test_groupby_rolling_sum(self):
self._test_groupby_rolling_func("sum")
def test_groupby_rolling_std(self):
# TODO: `std` now raise error in pandas 1.0.0
self._test_groupby_rolling_func("std")
def test_groupby_rolling_var(self):
self._test_groupby_rolling_func("var")
if __name__ == "__main__":
import unittest
from pyspark.pandas.tests.test_rolling import * # noqa: F401
try:
import xmlrunner # type: ignore[import]
testRunner = xmlrunner.XMLTestRunner(output="target/test-reports", verbosity=2)
except ImportError:
testRunner = None
unittest.main(testRunner=testRunner, verbosity=2)