2021-04-14 22:45:15 -04:00
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#
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# Licensed to the Apache Software Foundation (ASF) under one or more
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# contributor license agreements. See the NOTICE file distributed with
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# this work for additional information regarding copyright ownership.
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# The ASF licenses this file to You under the Apache License, Version 2.0
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# (the "License"); you may not use this file except in compliance with
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# the License. You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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import numpy as np
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import pandas as pd
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import pyspark.pandas as ps
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2021-04-22 16:07:35 -04:00
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from pyspark.testing.pandasutils import PandasOnSparkTestCase, TestUtils
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2021-04-14 22:45:15 -04:00
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from pyspark.pandas.window import Rolling
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2021-04-22 16:07:35 -04:00
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class RollingTest(PandasOnSparkTestCase, TestUtils):
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2021-04-14 22:45:15 -04:00
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def test_rolling_error(self):
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with self.assertRaisesRegex(ValueError, "window must be >= 0"):
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ps.range(10).rolling(window=-1)
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with self.assertRaisesRegex(ValueError, "min_periods must be >= 0"):
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ps.range(10).rolling(window=1, min_periods=-1)
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with self.assertRaisesRegex(
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TypeError, "kdf_or_kser must be a series or dataframe; however, got:.*int"
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):
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Rolling(1, 2)
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def _test_rolling_func(self, f):
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pser = pd.Series([1, 2, 3], index=np.random.rand(3), name="a")
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kser = ps.from_pandas(pser)
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self.assert_eq(getattr(kser.rolling(2), f)(), getattr(pser.rolling(2), f)())
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self.assert_eq(getattr(kser.rolling(2), f)().sum(), getattr(pser.rolling(2), f)().sum())
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# Multiindex
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pser = pd.Series(
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[1, 2, 3],
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index=pd.MultiIndex.from_tuples([("a", "x"), ("a", "y"), ("b", "z")]),
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name="a",
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)
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kser = ps.from_pandas(pser)
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self.assert_eq(getattr(kser.rolling(2), f)(), getattr(pser.rolling(2), f)())
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pdf = pd.DataFrame(
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{"a": [1.0, 2.0, 3.0, 2.0], "b": [4.0, 2.0, 3.0, 1.0]}, index=np.random.rand(4)
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)
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kdf = ps.from_pandas(pdf)
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self.assert_eq(getattr(kdf.rolling(2), f)(), getattr(pdf.rolling(2), f)())
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self.assert_eq(getattr(kdf.rolling(2), f)().sum(), getattr(pdf.rolling(2), f)().sum())
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# Multiindex column
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columns = pd.MultiIndex.from_tuples([("a", "x"), ("a", "y")])
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pdf.columns = columns
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kdf.columns = columns
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self.assert_eq(getattr(kdf.rolling(2), f)(), getattr(pdf.rolling(2), f)())
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def test_rolling_min(self):
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self._test_rolling_func("min")
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def test_rolling_max(self):
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self._test_rolling_func("max")
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def test_rolling_mean(self):
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self._test_rolling_func("mean")
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def test_rolling_sum(self):
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self._test_rolling_func("sum")
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def test_rolling_count(self):
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self._test_rolling_func("count")
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def test_rolling_std(self):
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self._test_rolling_func("std")
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def test_rolling_var(self):
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self._test_rolling_func("var")
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def _test_groupby_rolling_func(self, f):
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pser = pd.Series([1, 2, 3, 2], index=np.random.rand(4), name="a")
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kser = ps.from_pandas(pser)
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self.assert_eq(
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getattr(kser.groupby(kser).rolling(2), f)().sort_index(),
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getattr(pser.groupby(pser).rolling(2), f)().sort_index(),
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)
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self.assert_eq(
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getattr(kser.groupby(kser).rolling(2), f)().sum(),
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getattr(pser.groupby(pser).rolling(2), f)().sum(),
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)
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# Multiindex
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pser = pd.Series(
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[1, 2, 3, 2],
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index=pd.MultiIndex.from_tuples([("a", "x"), ("a", "y"), ("b", "z"), ("c", "z")]),
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name="a",
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)
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kser = ps.from_pandas(pser)
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self.assert_eq(
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getattr(kser.groupby(kser).rolling(2), f)().sort_index(),
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getattr(pser.groupby(pser).rolling(2), f)().sort_index(),
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)
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pdf = pd.DataFrame({"a": [1.0, 2.0, 3.0, 2.0], "b": [4.0, 2.0, 3.0, 1.0]})
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kdf = ps.from_pandas(pdf)
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self.assert_eq(
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getattr(kdf.groupby(kdf.a).rolling(2), f)().sort_index(),
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getattr(pdf.groupby(pdf.a).rolling(2), f)().sort_index(),
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)
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self.assert_eq(
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getattr(kdf.groupby(kdf.a).rolling(2), f)().sum(),
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getattr(pdf.groupby(pdf.a).rolling(2), f)().sum(),
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)
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self.assert_eq(
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getattr(kdf.groupby(kdf.a + 1).rolling(2), f)().sort_index(),
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getattr(pdf.groupby(pdf.a + 1).rolling(2), f)().sort_index(),
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)
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self.assert_eq(
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getattr(kdf.b.groupby(kdf.a).rolling(2), f)().sort_index(),
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getattr(pdf.b.groupby(pdf.a).rolling(2), f)().sort_index(),
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)
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self.assert_eq(
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getattr(kdf.groupby(kdf.a)["b"].rolling(2), f)().sort_index(),
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getattr(pdf.groupby(pdf.a)["b"].rolling(2), f)().sort_index(),
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)
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self.assert_eq(
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getattr(kdf.groupby(kdf.a)[["b"]].rolling(2), f)().sort_index(),
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getattr(pdf.groupby(pdf.a)[["b"]].rolling(2), f)().sort_index(),
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)
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# Multiindex column
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columns = pd.MultiIndex.from_tuples([("a", "x"), ("a", "y")])
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pdf.columns = columns
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kdf.columns = columns
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self.assert_eq(
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getattr(kdf.groupby(("a", "x")).rolling(2), f)().sort_index(),
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getattr(pdf.groupby(("a", "x")).rolling(2), f)().sort_index(),
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)
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self.assert_eq(
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getattr(kdf.groupby([("a", "x"), ("a", "y")]).rolling(2), f)().sort_index(),
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getattr(pdf.groupby([("a", "x"), ("a", "y")]).rolling(2), f)().sort_index(),
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)
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def test_groupby_rolling_count(self):
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self._test_groupby_rolling_func("count")
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def test_groupby_rolling_min(self):
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self._test_groupby_rolling_func("min")
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def test_groupby_rolling_max(self):
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self._test_groupby_rolling_func("max")
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def test_groupby_rolling_mean(self):
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self._test_groupby_rolling_func("mean")
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def test_groupby_rolling_sum(self):
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self._test_groupby_rolling_func("sum")
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def test_groupby_rolling_std(self):
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# TODO: `std` now raise error in pandas 1.0.0
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self._test_groupby_rolling_func("std")
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def test_groupby_rolling_var(self):
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self._test_groupby_rolling_func("var")
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if __name__ == "__main__":
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import unittest
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from pyspark.pandas.tests.test_rolling import * # noqa: F401
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try:
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import xmlrunner # type: ignore[import]
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testRunner = xmlrunner.XMLTestRunner(output='target/test-reports', verbosity=2)
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except ImportError:
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testRunner = None
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unittest.main(testRunner=testRunner, verbosity=2)
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