| # |
| # 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.groupby import is_multi_agg_with_relabel, SeriesGroupBy |
| from pyspark.testing.pandasutils import PandasOnSparkTestCase, TestUtils |
| |
| |
| class GroupByTestsMixin: |
| def test_groupby_simple(self): |
| pdf = pd.DataFrame( |
| { |
| "a": [1, 2, 6, 4, 4, 6, 4, 3, 7], |
| "b": [4, 2, 7, 3, 3, 1, 1, 1, 2], |
| "c": [4, 2, 7, 3, None, 1, 1, 1, 2], |
| "d": list("abcdefght"), |
| "e": [True, False, True, False, True, False, True, False, True], |
| }, |
| index=[0, 1, 3, 5, 6, 8, 9, 9, 9], |
| ) |
| psdf = ps.from_pandas(pdf) |
| |
| for as_index in [True, False]: |
| if as_index: |
| |
| def sort(df): |
| return df.sort_index() |
| |
| else: |
| |
| def sort(df): |
| return df.sort_values("a").reset_index(drop=True) |
| |
| self.assert_eq( |
| sort(psdf.groupby("a", as_index=as_index).sum()), |
| sort(pdf.groupby("a", as_index=as_index).sum()), |
| ) |
| self.assert_eq( |
| sort(psdf.groupby("a", as_index=as_index).b.sum()), |
| sort(pdf.groupby("a", as_index=as_index).b.sum()), |
| ) |
| self.assert_eq( |
| sort(psdf.groupby("a", as_index=as_index)["b"].sum()), |
| sort(pdf.groupby("a", as_index=as_index)["b"].sum()), |
| ) |
| self.assert_eq( |
| sort(psdf.groupby("a", as_index=as_index)[["b", "c"]].sum()), |
| sort(pdf.groupby("a", as_index=as_index)[["b", "c"]].sum()), |
| ) |
| self.assert_eq( |
| sort(psdf.groupby("a", as_index=as_index)[[]].sum()), |
| sort(pdf.groupby("a", as_index=as_index)[[]].sum()), |
| ) |
| self.assert_eq( |
| sort(psdf.groupby("a", as_index=as_index)["c"].sum()), |
| sort(pdf.groupby("a", as_index=as_index)["c"].sum()), |
| ) |
| |
| self.assert_eq( |
| psdf.groupby("a").a.sum().sort_index(), pdf.groupby("a").a.sum().sort_index() |
| ) |
| self.assert_eq( |
| psdf.groupby("a")["a"].sum().sort_index(), pdf.groupby("a")["a"].sum().sort_index() |
| ) |
| self.assert_eq( |
| psdf.groupby("a")[["a"]].sum().sort_index(), pdf.groupby("a")[["a"]].sum().sort_index() |
| ) |
| self.assert_eq( |
| psdf.groupby("a")[["a", "c"]].sum().sort_index(), |
| pdf.groupby("a")[["a", "c"]].sum().sort_index(), |
| ) |
| |
| self.assert_eq( |
| psdf.a.groupby(psdf.b).sum().sort_index(), pdf.a.groupby(pdf.b).sum().sort_index() |
| ) |
| |
| for axis in [0, "index"]: |
| self.assert_eq( |
| psdf.groupby("a", axis=axis).a.sum().sort_index(), |
| pdf.groupby("a", axis=axis).a.sum().sort_index(), |
| ) |
| self.assert_eq( |
| psdf.groupby("a", axis=axis)["a"].sum().sort_index(), |
| pdf.groupby("a", axis=axis)["a"].sum().sort_index(), |
| ) |
| self.assert_eq( |
| psdf.groupby("a", axis=axis)[["a"]].sum().sort_index(), |
| pdf.groupby("a", axis=axis)[["a"]].sum().sort_index(), |
| ) |
| self.assert_eq( |
| psdf.groupby("a", axis=axis)[["a", "c"]].sum().sort_index(), |
| pdf.groupby("a", axis=axis)[["a", "c"]].sum().sort_index(), |
| ) |
| |
| self.assert_eq( |
| psdf.a.groupby(psdf.b, axis=axis).sum().sort_index(), |
| pdf.a.groupby(pdf.b, axis=axis).sum().sort_index(), |
| ) |
| |
| self.assertRaises(ValueError, lambda: psdf.groupby("a", as_index=False).a) |
| self.assertRaises(ValueError, lambda: psdf.groupby("a", as_index=False)["a"]) |
| self.assertRaises(ValueError, lambda: psdf.groupby("a", as_index=False)[["a"]]) |
| self.assertRaises(ValueError, lambda: psdf.groupby("a", as_index=False)[["a", "c"]]) |
| self.assertRaises(KeyError, lambda: psdf.groupby("z", as_index=False)[["a", "c"]]) |
| self.assertRaises(KeyError, lambda: psdf.groupby(["z"], as_index=False)[["a", "c"]]) |
| |
| self.assertRaises(TypeError, lambda: psdf.a.groupby(psdf.b, as_index=False)) |
| |
| self.assertRaises(NotImplementedError, lambda: psdf.groupby("a", axis=1)) |
| self.assertRaises(NotImplementedError, lambda: psdf.groupby("a", axis="columns")) |
| self.assertRaises(ValueError, lambda: psdf.groupby("a", "b")) |
| self.assertRaises(TypeError, lambda: psdf.a.groupby(psdf.a, psdf.b)) |
| |
| # we can't use column name/names as a parameter `by` for `SeriesGroupBy`. |
| self.assertRaises(KeyError, lambda: psdf.a.groupby(by="a")) |
| self.assertRaises(KeyError, lambda: psdf.a.groupby(by=["a", "b"])) |
| self.assertRaises(KeyError, lambda: psdf.a.groupby(by=("a", "b"))) |
| self.assertRaises(KeyError, lambda: psdf.a.groupby(by=[("a", "b")])) |
| |
| # we can't use DataFrame as a parameter `by` for `DataFrameGroupBy`/`SeriesGroupBy`. |
| self.assertRaises(ValueError, lambda: psdf.groupby(psdf)) |
| self.assertRaises(ValueError, lambda: psdf.a.groupby(psdf)) |
| self.assertRaises(ValueError, lambda: psdf.a.groupby((psdf,))) |
| |
| with self.assertRaisesRegex(ValueError, "Grouper for 'list' not 1-dimensional"): |
| psdf.groupby(by=[["a", "b"]]) |
| |
| # non-string names |
| pdf = pd.DataFrame( |
| { |
| 10: [1, 2, 6, 4, 4, 6, 4, 3, 7], |
| 20: [4, 2, 7, 3, 3, 1, 1, 1, 2], |
| 30: [4, 2, 7, 3, None, 1, 1, 1, 2], |
| 40: list("abcdefght"), |
| }, |
| index=[0, 1, 3, 5, 6, 8, 9, 9, 9], |
| ) |
| psdf = ps.from_pandas(pdf) |
| |
| for as_index in [True, False]: |
| if as_index: |
| |
| def sort(df): |
| return df.sort_index() |
| |
| else: |
| |
| def sort(df): |
| return df.sort_values(10).reset_index(drop=True) |
| |
| self.assert_eq( |
| sort(psdf.groupby(10, as_index=as_index).sum()), |
| sort(pdf.groupby(10, as_index=as_index).sum()), |
| ) |
| self.assert_eq( |
| sort(psdf.groupby(10, as_index=as_index)[20].sum()), |
| sort(pdf.groupby(10, as_index=as_index)[20].sum()), |
| ) |
| self.assert_eq( |
| sort(psdf.groupby(10, as_index=as_index)[[20, 30]].sum()), |
| sort(pdf.groupby(10, as_index=as_index)[[20, 30]].sum()), |
| ) |
| |
| def test_shift(self): |
| pdf = pd.DataFrame( |
| { |
| "a": [1, 1, 2, 2, 3, 3] * 3, |
| "b": [1, 1, 2, 2, 3, 4] * 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("a").shift().sort_index(), pdf.groupby("a").shift().sort_index() |
| ) |
| self.assert_eq( |
| psdf.groupby(["a", "b"]).shift(periods=-1, fill_value=0).sort_index(), |
| pdf.groupby(["a", "b"]).shift(periods=-1, fill_value=0).sort_index(), |
| ) |
| self.assert_eq( |
| psdf.groupby(["b"])["a"].shift().sort_index(), |
| pdf.groupby(["b"])["a"].shift().sort_index(), |
| ) |
| self.assert_eq( |
| psdf.groupby(["a", "b"])["c"].shift().sort_index(), |
| pdf.groupby(["a", "b"])["c"].shift().sort_index(), |
| ) |
| self.assert_eq( |
| psdf.groupby(psdf.b // 5).shift().sort_index(), |
| pdf.groupby(pdf.b // 5).shift().sort_index(), |
| ) |
| self.assert_eq( |
| psdf.groupby(psdf.b // 5)["a"].shift().sort_index(), |
| pdf.groupby(pdf.b // 5)["a"].shift().sort_index(), |
| ) |
| self.assert_eq( |
| psdf.a.rename().groupby(psdf.b).shift().sort_index(), |
| pdf.a.rename().groupby(pdf.b).shift().sort_index(), |
| ) |
| self.assert_eq( |
| psdf.a.groupby(psdf.b.rename()).shift().sort_index(), |
| pdf.a.groupby(pdf.b.rename()).shift().sort_index(), |
| ) |
| self.assert_eq( |
| psdf.a.rename().groupby(psdf.b.rename()).shift().sort_index(), |
| pdf.a.rename().groupby(pdf.b.rename()).shift().sort_index(), |
| ) |
| |
| self.assert_eq(psdf.groupby("a").shift().sum(), pdf.groupby("a").shift().sum().astype(int)) |
| self.assert_eq( |
| psdf.a.rename().groupby(psdf.b).shift().sum(), |
| pdf.a.rename().groupby(pdf.b).shift().sum(), |
| ) |
| |
| # 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", "a")).shift().sort_index(), |
| pdf.groupby(("x", "a")).shift().sort_index(), |
| ) |
| self.assert_eq( |
| psdf.groupby([("x", "a"), ("x", "b")]).shift(periods=-1, fill_value=0).sort_index(), |
| pdf.groupby([("x", "a"), ("x", "b")]).shift(periods=-1, fill_value=0).sort_index(), |
| ) |
| |
| @staticmethod |
| def test_is_multi_agg_with_relabel(): |
| assert is_multi_agg_with_relabel(a="max") is False |
| assert is_multi_agg_with_relabel(a_min=("a", "max"), a_max=("a", "min")) is True |
| |
| def test_all_any(self): |
| pdf = pd.DataFrame( |
| { |
| "A": [1, 1, 2, 2, 3, 3, 4, 4, 5, 5], |
| "B": [True, True, True, False, False, False, None, True, None, False], |
| } |
| ) |
| psdf = ps.from_pandas(pdf) |
| |
| for as_index in [True, False]: |
| if as_index: |
| |
| def sort(df): |
| return df.sort_index() |
| |
| else: |
| |
| def sort(df): |
| return df.sort_values("A").reset_index(drop=True) |
| |
| self.assert_eq( |
| sort(psdf.groupby("A", as_index=as_index).all()), |
| sort(pdf.groupby("A", as_index=as_index).all()), |
| ) |
| self.assert_eq( |
| sort(psdf.groupby("A", as_index=as_index).any()), |
| sort(pdf.groupby("A", as_index=as_index).any()), |
| ) |
| |
| self.assert_eq( |
| sort(psdf.groupby("A", as_index=as_index).all()).B, |
| sort(pdf.groupby("A", as_index=as_index).all()).B, |
| ) |
| self.assert_eq( |
| sort(psdf.groupby("A", as_index=as_index).any()).B, |
| sort(pdf.groupby("A", as_index=as_index).any()).B, |
| ) |
| |
| self.assert_eq( |
| psdf.B.groupby(psdf.A).all().sort_index(), pdf.B.groupby(pdf.A).all().sort_index() |
| ) |
| self.assert_eq( |
| psdf.B.groupby(psdf.A).any().sort_index(), pdf.B.groupby(pdf.A).any().sort_index() |
| ) |
| |
| # multi-index columns |
| columns = pd.MultiIndex.from_tuples([("X", "A"), ("Y", "B")]) |
| pdf.columns = columns |
| psdf.columns = columns |
| |
| for as_index in [True, False]: |
| if as_index: |
| |
| def sort(df): |
| return df.sort_index() |
| |
| else: |
| |
| def sort(df): |
| return df.sort_values(("X", "A")).reset_index(drop=True) |
| |
| self.assert_eq( |
| sort(psdf.groupby(("X", "A"), as_index=as_index).all()), |
| sort(pdf.groupby(("X", "A"), as_index=as_index).all()), |
| ) |
| self.assert_eq( |
| sort(psdf.groupby(("X", "A"), as_index=as_index).any()), |
| sort(pdf.groupby(("X", "A"), as_index=as_index).any()), |
| ) |
| |
| # Test skipna |
| pdf = pd.DataFrame({"A": [True, True], "B": [1, np.nan], "C": [True, None]}) |
| pdf.name = "x" |
| psdf = ps.from_pandas(pdf) |
| self.assert_eq( |
| psdf.groupby("A").all(skipna=False).sort_index(), |
| pdf.groupby("A").all(skipna=False).sort_index(), |
| ) |
| self.assert_eq( |
| psdf.groupby("A").all(skipna=True).sort_index(), |
| pdf.groupby("A").all(skipna=True).sort_index(), |
| ) |
| |
| def test_nunique(self): |
| pdf = pd.DataFrame( |
| {"a": [1, 1, 1, 1, 1, 0, 0, 0, 0, 0], "b": [2, 2, 2, 3, 3, 4, 4, 5, 5, 5]} |
| ) |
| psdf = ps.from_pandas(pdf) |
| self.assert_eq( |
| psdf.groupby("a").agg({"b": "nunique"}).sort_index(), |
| pdf.groupby("a").agg({"b": "nunique"}).sort_index(), |
| ) |
| self.assert_eq( |
| psdf.groupby("a").nunique().sort_index(), pdf.groupby("a").nunique().sort_index() |
| ) |
| self.assert_eq( |
| psdf.groupby("a").nunique(dropna=False).sort_index(), |
| pdf.groupby("a").nunique(dropna=False).sort_index(), |
| ) |
| self.assert_eq( |
| psdf.groupby("a")["b"].nunique().sort_index(), |
| pdf.groupby("a")["b"].nunique().sort_index(), |
| ) |
| self.assert_eq( |
| psdf.groupby("a")["b"].nunique(dropna=False).sort_index(), |
| pdf.groupby("a")["b"].nunique(dropna=False).sort_index(), |
| ) |
| |
| nunique_psdf = psdf.groupby("a", as_index=False).agg({"b": "nunique"}) |
| nunique_pdf = pdf.groupby("a", as_index=False).agg({"b": "nunique"}) |
| self.assert_eq( |
| nunique_psdf.sort_values(["a", "b"]).reset_index(drop=True), |
| nunique_pdf.sort_values(["a", "b"]).reset_index(drop=True), |
| ) |
| |
| # multi-index columns |
| columns = pd.MultiIndex.from_tuples([("x", "a"), ("y", "b")]) |
| pdf.columns = columns |
| psdf.columns = columns |
| |
| self.assert_eq( |
| psdf.groupby(("x", "a")).nunique().sort_index(), |
| pdf.groupby(("x", "a")).nunique().sort_index(), |
| ) |
| self.assert_eq( |
| psdf.groupby(("x", "a")).nunique(dropna=False).sort_index(), |
| pdf.groupby(("x", "a")).nunique(dropna=False).sort_index(), |
| ) |
| |
| def test_unique(self): |
| for pdf in [ |
| pd.DataFrame( |
| {"a": [1, 1, 1, 1, 1, 0, 0, 0, 0, 0], "b": [2, 2, 2, 3, 3, 4, 4, 5, 5, 5]} |
| ), |
| pd.DataFrame( |
| { |
| "a": [1, 1, 1, 1, 1, 0, 0, 0, 0, 0], |
| "b": ["w", "w", "w", "x", "x", "y", "y", "z", "z", "z"], |
| } |
| ), |
| ]: |
| with self.subTest(pdf=pdf): |
| psdf = ps.from_pandas(pdf) |
| |
| actual = psdf.groupby("a")["b"].unique().sort_index()._to_pandas() |
| expect = pdf.groupby("a")["b"].unique().sort_index() |
| self.assert_eq(len(actual), len(expect)) |
| for act, exp in zip(actual, expect): |
| self.assertTrue(sorted(act) == sorted(exp)) |
| |
| def test_diff(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, |
| } |
| ) |
| psdf = ps.from_pandas(pdf) |
| |
| self.assert_eq(psdf.groupby("b").diff().sort_index(), pdf.groupby("b").diff().sort_index()) |
| self.assert_eq( |
| psdf.groupby(["a", "b"]).diff().sort_index(), |
| pdf.groupby(["a", "b"]).diff().sort_index(), |
| ) |
| self.assert_eq( |
| psdf.groupby(["b"])["a"].diff().sort_index(), |
| pdf.groupby(["b"])["a"].diff().sort_index(), |
| ) |
| self.assert_eq( |
| psdf.groupby(["b"])[["a", "b"]].diff().sort_index(), |
| pdf.groupby(["b"])[["a", "b"]].diff().sort_index(), |
| ) |
| self.assert_eq( |
| psdf.groupby(psdf.b // 5).diff().sort_index(), |
| pdf.groupby(pdf.b // 5).diff().sort_index(), |
| ) |
| self.assert_eq( |
| psdf.groupby(psdf.b // 5)["a"].diff().sort_index(), |
| pdf.groupby(pdf.b // 5)["a"].diff().sort_index(), |
| ) |
| |
| self.assert_eq(psdf.groupby("b").diff().sum(), pdf.groupby("b").diff().sum().astype(int)) |
| self.assert_eq(psdf.groupby(["b"])["a"].diff().sum(), pdf.groupby(["b"])["a"].diff().sum()) |
| |
| # 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")).diff().sort_index(), |
| pdf.groupby(("x", "b")).diff().sort_index(), |
| ) |
| self.assert_eq( |
| psdf.groupby([("x", "a"), ("x", "b")]).diff().sort_index(), |
| pdf.groupby([("x", "a"), ("x", "b")]).diff().sort_index(), |
| ) |
| |
| def test_aggregate_relabel_index_false(self): |
| pdf = pd.DataFrame( |
| { |
| "A": [0, 0, 1, 1, 1], |
| "B": ["a", "a", "b", "a", "b"], |
| "C": [10, 15, 10, 20, 30], |
| } |
| ) |
| psdf = ps.from_pandas(pdf) |
| |
| self.assert_eq( |
| pdf.groupby(["B", "A"], as_index=False) |
| .agg(C_MAX=("C", "max")) |
| .sort_values(["B", "A"]) |
| .reset_index(drop=True), |
| psdf.groupby(["B", "A"], as_index=False) |
| .agg(C_MAX=("C", "max")) |
| .sort_values(["B", "A"]) |
| .reset_index(drop=True), |
| ) |
| |
| |
| class GroupByTests( |
| GroupByTestsMixin, |
| PandasOnSparkTestCase, |
| TestUtils, |
| ): |
| pass |
| |
| |
| if __name__ == "__main__": |
| from pyspark.pandas.tests.groupby.test_groupby 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) |
