| # |
| # 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 unittest |
| |
| import numpy as np |
| import pandas as pd |
| |
| from pyspark import pandas as ps |
| from pyspark.pandas.exceptions import DataError |
| from pyspark.testing.pandasutils import PandasOnSparkTestCase |
| from pyspark.testing.sqlutils import SQLTestUtils |
| |
| |
| class GroupbyCumulativeMixin: |
| def test_cumcount(self): |
| pdf = pd.DataFrame( |
| { |
| "a": [1, 2, 3, 4, 5, 6] * 3, |
| "b": [1, 1, 2, 3, 5, 8] * 3, |
| "c": [1, 4, 9, 16, 25, 36] * 3, |
| }, |
| index=np.random.rand(6 * 3), |
| ) |
| psdf = ps.from_pandas(pdf) |
| |
| for ascending in [True, False]: |
| self.assert_eq( |
| psdf.groupby("b").cumcount(ascending=ascending).sort_index(), |
| pdf.groupby("b").cumcount(ascending=ascending).sort_index(), |
| ) |
| self.assert_eq( |
| psdf.groupby(["a", "b"]).cumcount(ascending=ascending).sort_index(), |
| pdf.groupby(["a", "b"]).cumcount(ascending=ascending).sort_index(), |
| ) |
| self.assert_eq( |
| psdf.groupby(["b"])["a"].cumcount(ascending=ascending).sort_index(), |
| pdf.groupby(["b"])["a"].cumcount(ascending=ascending).sort_index(), |
| ) |
| self.assert_eq( |
| psdf.groupby(["b"])[["a", "c"]].cumcount(ascending=ascending).sort_index(), |
| pdf.groupby(["b"])[["a", "c"]].cumcount(ascending=ascending).sort_index(), |
| ) |
| self.assert_eq( |
| psdf.groupby(psdf.b // 5).cumcount(ascending=ascending).sort_index(), |
| pdf.groupby(pdf.b // 5).cumcount(ascending=ascending).sort_index(), |
| ) |
| self.assert_eq( |
| psdf.groupby(psdf.b // 5)["a"].cumcount(ascending=ascending).sort_index(), |
| pdf.groupby(pdf.b // 5)["a"].cumcount(ascending=ascending).sort_index(), |
| ) |
| self.assert_eq( |
| psdf.groupby("b").cumcount(ascending=ascending).sum(), |
| pdf.groupby("b").cumcount(ascending=ascending).sum(), |
| ) |
| self.assert_eq( |
| psdf.a.rename().groupby(psdf.b).cumcount(ascending=ascending).sort_index(), |
| pdf.a.rename().groupby(pdf.b).cumcount(ascending=ascending).sort_index(), |
| ) |
| self.assert_eq( |
| psdf.a.groupby(psdf.b.rename()).cumcount(ascending=ascending).sort_index(), |
| pdf.a.groupby(pdf.b.rename()).cumcount(ascending=ascending).sort_index(), |
| ) |
| self.assert_eq( |
| psdf.a.rename().groupby(psdf.b.rename()).cumcount(ascending=ascending).sort_index(), |
| pdf.a.rename().groupby(pdf.b.rename()).cumcount(ascending=ascending).sort_index(), |
| ) |
| |
| # multi-index columns |
| columns = pd.MultiIndex.from_tuples([("x", "a"), ("x", "b"), ("y", "c")]) |
| pdf.columns = columns |
| psdf.columns = columns |
| |
| for ascending in [True, False]: |
| self.assert_eq( |
| psdf.groupby(("x", "b")).cumcount(ascending=ascending).sort_index(), |
| pdf.groupby(("x", "b")).cumcount(ascending=ascending).sort_index(), |
| ) |
| self.assert_eq( |
| psdf.groupby([("x", "a"), ("x", "b")]).cumcount(ascending=ascending).sort_index(), |
| pdf.groupby([("x", "a"), ("x", "b")]).cumcount(ascending=ascending).sort_index(), |
| ) |
| |
| def test_cummin(self): |
| pdf = pd.DataFrame( |
| { |
| "a": [1, 2, 3, 4, 5, 6] * 3, |
| "b": [1, 1, 2, 3, 5, 8] * 3, |
| "c": [1, 4, 9, 16, 25, 36] * 3, |
| }, |
| index=np.random.rand(6 * 3), |
| ) |
| psdf = ps.from_pandas(pdf) |
| |
| self.assert_eq( |
| psdf.groupby("b").cummin().sort_index(), pdf.groupby("b").cummin().sort_index() |
| ) |
| self.assert_eq( |
| psdf.groupby(["a", "b"]).cummin().sort_index(), |
| pdf.groupby(["a", "b"]).cummin().sort_index(), |
| ) |
| self.assert_eq( |
| psdf.groupby(["b"])["a"].cummin().sort_index(), |
| pdf.groupby(["b"])["a"].cummin().sort_index(), |
| ) |
| self.assert_eq( |
| psdf.groupby(["b"])[["a", "c"]].cummin().sort_index(), |
| pdf.groupby(["b"])[["a", "c"]].cummin().sort_index(), |
| ) |
| self.assert_eq( |
| psdf.groupby(psdf.b // 5).cummin().sort_index(), |
| pdf.groupby(pdf.b // 5).cummin().sort_index(), |
| ) |
| self.assert_eq( |
| psdf.groupby(psdf.b // 5)["a"].cummin().sort_index(), |
| pdf.groupby(pdf.b // 5)["a"].cummin().sort_index(), |
| ) |
| self.assert_eq( |
| psdf.groupby("b").cummin().sum().sort_index(), |
| pdf.groupby("b").cummin().sum().sort_index(), |
| ) |
| self.assert_eq( |
| psdf.a.rename().groupby(psdf.b).cummin().sort_index(), |
| pdf.a.rename().groupby(pdf.b).cummin().sort_index(), |
| ) |
| self.assert_eq( |
| psdf.a.groupby(psdf.b.rename()).cummin().sort_index(), |
| pdf.a.groupby(pdf.b.rename()).cummin().sort_index(), |
| ) |
| self.assert_eq( |
| psdf.a.rename().groupby(psdf.b.rename()).cummin().sort_index(), |
| pdf.a.rename().groupby(pdf.b.rename()).cummin().sort_index(), |
| ) |
| |
| # multi-index columns |
| columns = pd.MultiIndex.from_tuples([("x", "a"), ("x", "b"), ("y", "c")]) |
| pdf.columns = columns |
| psdf.columns = columns |
| |
| self.assert_eq( |
| psdf.groupby(("x", "b")).cummin().sort_index(), |
| pdf.groupby(("x", "b")).cummin().sort_index(), |
| ) |
| self.assert_eq( |
| psdf.groupby([("x", "a"), ("x", "b")]).cummin().sort_index(), |
| pdf.groupby([("x", "a"), ("x", "b")]).cummin().sort_index(), |
| ) |
| |
| psdf = ps.DataFrame([["a"], ["b"], ["c"]], columns=["A"]) |
| self.assertRaises(DataError, lambda: psdf.groupby(["A"]).cummin()) |
| psdf = ps.DataFrame([[1, "a"], [2, "b"], [3, "c"]], columns=["A", "B"]) |
| self.assertRaises(DataError, lambda: psdf.groupby(["A"])["B"].cummin()) |
| |
| def test_cummax(self): |
| pdf = pd.DataFrame( |
| { |
| "a": [1, 2, 3, 4, 5, 6] * 3, |
| "b": [1, 1, 2, 3, 5, 8] * 3, |
| "c": [1, 4, 9, 16, 25, 36] * 3, |
| }, |
| index=np.random.rand(6 * 3), |
| ) |
| psdf = ps.from_pandas(pdf) |
| |
| self.assert_eq( |
| psdf.groupby("b").cummax().sort_index(), pdf.groupby("b").cummax().sort_index() |
| ) |
| self.assert_eq( |
| psdf.groupby(["a", "b"]).cummax().sort_index(), |
| pdf.groupby(["a", "b"]).cummax().sort_index(), |
| ) |
| self.assert_eq( |
| psdf.groupby(["b"])["a"].cummax().sort_index(), |
| pdf.groupby(["b"])["a"].cummax().sort_index(), |
| ) |
| self.assert_eq( |
| psdf.groupby(["b"])[["a", "c"]].cummax().sort_index(), |
| pdf.groupby(["b"])[["a", "c"]].cummax().sort_index(), |
| ) |
| self.assert_eq( |
| psdf.groupby(psdf.b // 5).cummax().sort_index(), |
| pdf.groupby(pdf.b // 5).cummax().sort_index(), |
| ) |
| self.assert_eq( |
| psdf.groupby(psdf.b // 5)["a"].cummax().sort_index(), |
| pdf.groupby(pdf.b // 5)["a"].cummax().sort_index(), |
| ) |
| self.assert_eq( |
| psdf.groupby("b").cummax().sum().sort_index(), |
| pdf.groupby("b").cummax().sum().sort_index(), |
| ) |
| self.assert_eq( |
| psdf.a.rename().groupby(psdf.b).cummax().sort_index(), |
| pdf.a.rename().groupby(pdf.b).cummax().sort_index(), |
| ) |
| self.assert_eq( |
| psdf.a.groupby(psdf.b.rename()).cummax().sort_index(), |
| pdf.a.groupby(pdf.b.rename()).cummax().sort_index(), |
| ) |
| self.assert_eq( |
| psdf.a.rename().groupby(psdf.b.rename()).cummax().sort_index(), |
| pdf.a.rename().groupby(pdf.b.rename()).cummax().sort_index(), |
| ) |
| |
| # multi-index columns |
| columns = pd.MultiIndex.from_tuples([("x", "a"), ("x", "b"), ("y", "c")]) |
| pdf.columns = columns |
| psdf.columns = columns |
| |
| self.assert_eq( |
| psdf.groupby(("x", "b")).cummax().sort_index(), |
| pdf.groupby(("x", "b")).cummax().sort_index(), |
| ) |
| self.assert_eq( |
| psdf.groupby([("x", "a"), ("x", "b")]).cummax().sort_index(), |
| pdf.groupby([("x", "a"), ("x", "b")]).cummax().sort_index(), |
| ) |
| |
| psdf = ps.DataFrame([["a"], ["b"], ["c"]], columns=["A"]) |
| self.assertRaises(DataError, lambda: psdf.groupby(["A"]).cummax()) |
| psdf = ps.DataFrame([[1, "a"], [2, "b"], [3, "c"]], columns=["A", "B"]) |
| self.assertRaises(DataError, lambda: psdf.groupby(["A"])["B"].cummax()) |
| |
| def test_cumsum(self): |
| pdf = pd.DataFrame( |
| { |
| "a": [1, 2, 3, 4, 5, 6] * 3, |
| "b": [1, 1, 2, 3, 5, 8] * 3, |
| "c": [1, 4, 9, 16, 25, 36] * 3, |
| }, |
| index=np.random.rand(6 * 3), |
| ) |
| psdf = ps.from_pandas(pdf) |
| |
| self.assert_eq( |
| psdf.groupby("b").cumsum().sort_index(), pdf.groupby("b").cumsum().sort_index() |
| ) |
| self.assert_eq( |
| psdf.groupby(["a", "b"]).cumsum().sort_index(), |
| pdf.groupby(["a", "b"]).cumsum().sort_index(), |
| ) |
| self.assert_eq( |
| psdf.groupby(["b"])["a"].cumsum().sort_index(), |
| pdf.groupby(["b"])["a"].cumsum().sort_index(), |
| ) |
| self.assert_eq( |
| psdf.groupby(["b"])[["a", "c"]].cumsum().sort_index(), |
| pdf.groupby(["b"])[["a", "c"]].cumsum().sort_index(), |
| ) |
| self.assert_eq( |
| psdf.groupby(psdf.b // 5).cumsum().sort_index(), |
| pdf.groupby(pdf.b // 5).cumsum().sort_index(), |
| ) |
| self.assert_eq( |
| psdf.groupby(psdf.b // 5)["a"].cumsum().sort_index(), |
| pdf.groupby(pdf.b // 5)["a"].cumsum().sort_index(), |
| ) |
| self.assert_eq( |
| psdf.groupby("b").cumsum().sum().sort_index(), |
| pdf.groupby("b").cumsum().sum().sort_index(), |
| ) |
| self.assert_eq( |
| psdf.a.rename().groupby(psdf.b).cumsum().sort_index(), |
| pdf.a.rename().groupby(pdf.b).cumsum().sort_index(), |
| ) |
| self.assert_eq( |
| psdf.a.groupby(psdf.b.rename()).cumsum().sort_index(), |
| pdf.a.groupby(pdf.b.rename()).cumsum().sort_index(), |
| ) |
| self.assert_eq( |
| psdf.a.rename().groupby(psdf.b.rename()).cumsum().sort_index(), |
| pdf.a.rename().groupby(pdf.b.rename()).cumsum().sort_index(), |
| ) |
| |
| # multi-index columns |
| columns = pd.MultiIndex.from_tuples([("x", "a"), ("x", "b"), ("y", "c")]) |
| pdf.columns = columns |
| psdf.columns = columns |
| |
| self.assert_eq( |
| psdf.groupby(("x", "b")).cumsum().sort_index(), |
| pdf.groupby(("x", "b")).cumsum().sort_index(), |
| ) |
| self.assert_eq( |
| psdf.groupby([("x", "a"), ("x", "b")]).cumsum().sort_index(), |
| pdf.groupby([("x", "a"), ("x", "b")]).cumsum().sort_index(), |
| ) |
| |
| psdf = ps.DataFrame([["a"], ["b"], ["c"]], columns=["A"]) |
| self.assertRaises(DataError, lambda: psdf.groupby(["A"]).cumsum()) |
| psdf = ps.DataFrame([[1, "a"], [2, "b"], [3, "c"]], columns=["A", "B"]) |
| self.assertRaises(DataError, lambda: psdf.groupby(["A"])["B"].cumsum()) |
| |
| def test_cumprod(self): |
| pdf = pd.DataFrame( |
| { |
| "a": [1, 2, -3, 4, -5, 6] * 3, |
| "b": [1, 1, 2, 3, 5, 8] * 3, |
| "c": [1, 0, 9, 16, 25, 36] * 3, |
| }, |
| index=np.random.rand(6 * 3), |
| ) |
| psdf = ps.from_pandas(pdf) |
| |
| self.assert_eq( |
| psdf.groupby("b").cumprod().sort_index(), |
| pdf.groupby("b").cumprod().sort_index(), |
| check_exact=False, |
| ) |
| self.assert_eq( |
| psdf.groupby(["a", "b"]).cumprod().sort_index(), |
| pdf.groupby(["a", "b"]).cumprod().sort_index(), |
| check_exact=False, |
| ) |
| self.assert_eq( |
| psdf.groupby(["b"])["a"].cumprod().sort_index(), |
| pdf.groupby(["b"])["a"].cumprod().sort_index(), |
| check_exact=False, |
| ) |
| self.assert_eq( |
| psdf.groupby(["b"])[["a", "c"]].cumprod().sort_index(), |
| pdf.groupby(["b"])[["a", "c"]].cumprod().sort_index(), |
| check_exact=False, |
| ) |
| self.assert_eq( |
| psdf.groupby(psdf.b // 3).cumprod().sort_index(), |
| pdf.groupby(pdf.b // 3).cumprod().sort_index(), |
| check_exact=False, |
| ) |
| self.assert_eq( |
| psdf.groupby(psdf.b // 3)["a"].cumprod().sort_index(), |
| pdf.groupby(pdf.b // 3)["a"].cumprod().sort_index(), |
| check_exact=False, |
| ) |
| self.assert_eq( |
| psdf.groupby("b").cumprod().sum().sort_index(), |
| pdf.groupby("b").cumprod().sum().sort_index(), |
| check_exact=False, |
| ) |
| self.assert_eq( |
| psdf.a.rename().groupby(psdf.b).cumprod().sort_index(), |
| pdf.a.rename().groupby(pdf.b).cumprod().sort_index(), |
| check_exact=False, |
| ) |
| self.assert_eq( |
| psdf.a.groupby(psdf.b.rename()).cumprod().sort_index(), |
| pdf.a.groupby(pdf.b.rename()).cumprod().sort_index(), |
| check_exact=False, |
| ) |
| self.assert_eq( |
| psdf.a.rename().groupby(psdf.b.rename()).cumprod().sort_index(), |
| pdf.a.rename().groupby(pdf.b.rename()).cumprod().sort_index(), |
| check_exact=False, |
| ) |
| |
| # multi-index columns |
| columns = pd.MultiIndex.from_tuples([("x", "a"), ("x", "b"), ("y", "c")]) |
| pdf.columns = columns |
| psdf.columns = columns |
| |
| self.assert_eq( |
| psdf.groupby(("x", "b")).cumprod().sort_index(), |
| pdf.groupby(("x", "b")).cumprod().sort_index(), |
| check_exact=False, |
| ) |
| self.assert_eq( |
| psdf.groupby([("x", "a"), ("x", "b")]).cumprod().sort_index(), |
| pdf.groupby([("x", "a"), ("x", "b")]).cumprod().sort_index(), |
| check_exact=False, |
| ) |
| |
| psdf = ps.DataFrame([["a"], ["b"], ["c"]], columns=["A"]) |
| self.assertRaises(DataError, lambda: psdf.groupby(["A"]).cumprod()) |
| psdf = ps.DataFrame([[1, "a"], [2, "b"], [3, "c"]], columns=["A", "B"]) |
| self.assertRaises(DataError, lambda: psdf.groupby(["A"])["B"].cumprod()) |
| |
| |
| class GroupbyCumulativeTests( |
| GroupbyCumulativeMixin, |
| PandasOnSparkTestCase, |
| SQLTestUtils, |
| ): |
| pass |
| |
| |
| if __name__ == "__main__": |
| from pyspark.pandas.tests.groupby.test_cumulative import * # noqa: F401 |
| |
| try: |
| import xmlrunner |
| |
| testRunner = xmlrunner.XMLTestRunner(output="target/test-reports", verbosity=2) |
| except ImportError: |
| testRunner = None |
| unittest.main(testRunner=testRunner, verbosity=2) |
