# # 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, "kdf_or_kser 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") kser = ps.from_pandas(pser) self.assert_eq(getattr(kser.rolling(2), f)(), getattr(pser.rolling(2), f)()) self.assert_eq(getattr(kser.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", ) kser = ps.from_pandas(pser) self.assert_eq(getattr(kser.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) ) kdf = ps.from_pandas(pdf) self.assert_eq(getattr(kdf.rolling(2), f)(), getattr(pdf.rolling(2), f)()) self.assert_eq(getattr(kdf.rolling(2), f)().sum(), getattr(pdf.rolling(2), f)().sum()) # Multiindex column columns = pd.MultiIndex.from_tuples([("a", "x"), ("a", "y")]) pdf.columns = columns kdf.columns = columns self.assert_eq(getattr(kdf.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") kser = ps.from_pandas(pser) self.assert_eq( getattr(kser.groupby(kser).rolling(2), f)().sort_index(), getattr(pser.groupby(pser).rolling(2), f)().sort_index(), ) self.assert_eq( getattr(kser.groupby(kser).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", ) kser = ps.from_pandas(pser) self.assert_eq( getattr(kser.groupby(kser).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]}) kdf = ps.from_pandas(pdf) self.assert_eq( getattr(kdf.groupby(kdf.a).rolling(2), f)().sort_index(), getattr(pdf.groupby(pdf.a).rolling(2), f)().sort_index(), ) self.assert_eq( getattr(kdf.groupby(kdf.a).rolling(2), f)().sum(), getattr(pdf.groupby(pdf.a).rolling(2), f)().sum(), ) self.assert_eq( getattr(kdf.groupby(kdf.a + 1).rolling(2), f)().sort_index(), getattr(pdf.groupby(pdf.a + 1).rolling(2), f)().sort_index(), ) self.assert_eq( getattr(kdf.b.groupby(kdf.a).rolling(2), f)().sort_index(), getattr(pdf.b.groupby(pdf.a).rolling(2), f)().sort_index(), ) self.assert_eq( getattr(kdf.groupby(kdf.a)["b"].rolling(2), f)().sort_index(), getattr(pdf.groupby(pdf.a)["b"].rolling(2), f)().sort_index(), ) self.assert_eq( getattr(kdf.groupby(kdf.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 kdf.columns = columns self.assert_eq( getattr(kdf.groupby(("a", "x")).rolling(2), f)().sort_index(), getattr(pdf.groupby(("a", "x")).rolling(2), f)().sort_index(), ) self.assert_eq( getattr(kdf.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)