text: #
  # 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 pandas as pd
  
  from pyspark import pandas as ps
  from pyspark.pandas.config import set_option, reset_option
  from pyspark.testing.pandasutils import PandasOnSparkTestCase
  from pyspark.testing.sqlutils import SQLTestUtils
  
  
  class OpsOnDiffFramesGroupByTest(PandasOnSparkTestCase, SQLTestUtils):
      @classmethod
      def setUpClass(cls):
          super().setUpClass()
          set_option("compute.ops_on_diff_frames", True)
  
      @classmethod
      def tearDownClass(cls):
          reset_option("compute.ops_on_diff_frames")
          super().tearDownClass()
  
      def test_groupby_different_lengths(self):
          pdfs1 = [
              pd.DataFrame({"c": [4, 2, 7, 3, None, 1, 1, 1, 2], "d": list("abcdefght")}),
              pd.DataFrame({"c": [4, 2, 7, None, 1, 1, 2], "d": list("abcdefg")}),
              pd.DataFrame({"c": [4, 2, 7, 3, None, 1, 1, 1, 2, 2], "d": list("abcdefghti")}),
          ]
          pdfs2 = [
              pd.DataFrame({"a": [1, 2, 6, 4, 4, 6, 4, 3, 7], "b": [4, 2, 7, 3, 3, 1, 1, 1, 2]}),
              pd.DataFrame({"a": [1, 2, 6, 4, 4, 6, 4, 7], "b": [4, 2, 7, 3, 3, 1, 1, 2]}),
              pd.DataFrame({"a": [1, 2, 6, 4, 4, 6, 4, 3, 7], "b": [4, 2, 7, 3, 3, 1, 1, 1, 2]}),
          ]
  
          for pdf1, pdf2 in zip(pdfs1, pdfs2):
              kdf1 = ps.from_pandas(pdf1)
              kdf2 = ps.from_pandas(pdf2)
  
              for as_index in [True, False]:
                  if as_index:
                      sort = lambda df: df.sort_index()
                  else:
                      sort = lambda df: df.sort_values("c").reset_index(drop=True)
                  self.assert_eq(
                      sort(kdf1.groupby(kdf2.a, as_index=as_index).sum()),
                      sort(pdf1.groupby(pdf2.a, as_index=as_index).sum()),
                      almost=as_index,
                  )
  
                  self.assert_eq(
                      sort(kdf1.groupby(kdf2.a, as_index=as_index).c.sum()),
                      sort(pdf1.groupby(pdf2.a, as_index=as_index).c.sum()),
                      almost=as_index,
                  )
                  self.assert_eq(
                      sort(kdf1.groupby(kdf2.a, as_index=as_index)["c"].sum()),
                      sort(pdf1.groupby(pdf2.a, as_index=as_index)["c"].sum()),
                      almost=as_index,
                  )
  
      def test_groupby_multiindex_columns(self):
          pdf1 = pd.DataFrame(
              {("y", "c"): [4, 2, 7, 3, None, 1, 1, 1, 2], ("z", "d"): list("abcdefght")}
          )
          pdf2 = pd.DataFrame(
              {("x", "a"): [1, 2, 6, 4, 4, 6, 4, 3, 7], ("x", "b"): [4, 2, 7, 3, 3, 1, 1, 1, 2]}
          )
          kdf1 = ps.from_pandas(pdf1)
          kdf2 = ps.from_pandas(pdf2)
  
          self.assert_eq(
              kdf1.groupby(kdf2[("x", "a")]).sum().sort_index(),
              pdf1.groupby(pdf2[("x", "a")]).sum().sort_index(),
          )
  
          self.assert_eq(
              kdf1.groupby(kdf2[("x", "a")], as_index=False)
              .sum()
              .sort_values(("y", "c"))
              .reset_index(drop=True),
              pdf1.groupby(pdf2[("x", "a")], as_index=False)
              .sum()
              .sort_values(("y", "c"))
              .reset_index(drop=True),
          )
          self.assert_eq(
              kdf1.groupby(kdf2[("x", "a")])[[("y", "c")]].sum().sort_index(),
              pdf1.groupby(pdf2[("x", "a")])[[("y", "c")]].sum().sort_index(),
          )
  
      def test_split_apply_combine_on_series(self):
          pdf1 = pd.DataFrame({"C": [0.362, 0.227, 1.267, -0.562], "B": [1, 2, 3, 4]})
          pdf2 = pd.DataFrame({"A": [1, 1, 2, 2]})
          kdf1 = ps.from_pandas(pdf1)
          kdf2 = ps.from_pandas(pdf2)
  
          for as_index in [True, False]:
              if as_index:
                  sort = lambda df: df.sort_index()
              else:
                  sort = lambda df: df.sort_values(list(df.columns)).reset_index(drop=True)
  
              with self.subTest(as_index=as_index):
                  self.assert_eq(
                      sort(kdf1.groupby(kdf2.A, as_index=as_index).sum()),
                      sort(pdf1.groupby(pdf2.A, as_index=as_index).sum()),
                  )
                  self.assert_eq(
                      sort(kdf1.groupby(kdf2.A, as_index=as_index).B.sum()),
                      sort(pdf1.groupby(pdf2.A, as_index=as_index).B.sum()),
                  )
                  self.assert_eq(
                      sort(kdf1.groupby([kdf1.C, kdf2.A], as_index=as_index).sum()),
                      sort(pdf1.groupby([pdf1.C, pdf2.A], as_index=as_index).sum()),
                  )
                  self.assert_eq(
                      sort(kdf1.groupby([kdf1.C + 1, kdf2.A], as_index=as_index).sum()),
                      sort(pdf1.groupby([pdf1.C + 1, pdf2.A], as_index=as_index).sum()),
                  )
  
          self.assert_eq(
              kdf1.B.groupby(kdf2.A).sum().sort_index(), pdf1.B.groupby(pdf2.A).sum().sort_index(),
          )
          self.assert_eq(
              (kdf1.B + 1).groupby(kdf2.A).sum().sort_index(),
              (pdf1.B + 1).groupby(pdf2.A).sum().sort_index(),
          )
  
          self.assert_eq(
              kdf1.B.groupby(kdf2.A.rename()).sum().sort_index(),
              pdf1.B.groupby(pdf2.A.rename()).sum().sort_index(),
          )
          self.assert_eq(
              kdf1.B.rename().groupby(kdf2.A).sum().sort_index(),
              pdf1.B.rename().groupby(pdf2.A).sum().sort_index(),
          )
          self.assert_eq(
              kdf1.B.rename().groupby(kdf2.A.rename()).sum().sort_index(),
              pdf1.B.rename().groupby(pdf2.A.rename()).sum().sort_index(),
          )
  
      def test_aggregate(self):
          pdf1 = pd.DataFrame({"C": [0.362, 0.227, 1.267, -0.562], "B": [1, 2, 3, 4]})
          pdf2 = pd.DataFrame({"A": [1, 1, 2, 2]})
          kdf1 = ps.from_pandas(pdf1)
          kdf2 = ps.from_pandas(pdf2)
  
          for as_index in [True, False]:
              if as_index:
                  sort = lambda df: df.sort_index()
              else:
                  sort = lambda df: df.sort_values(list(df.columns)).reset_index(drop=True)
  
              with self.subTest(as_index=as_index):
                  self.assert_eq(
                      sort(kdf1.groupby(kdf2.A, as_index=as_index).agg("sum")),
                      sort(pdf1.groupby(pdf2.A, as_index=as_index).agg("sum")),
                  )
                  self.assert_eq(
                      sort(kdf1.groupby(kdf2.A, as_index=as_index).agg({"B": "min", "C": "sum"})),
                      sort(pdf1.groupby(pdf2.A, as_index=as_index).agg({"B": "min", "C": "sum"})),
                  )
                  self.assert_eq(
                      sort(
                          kdf1.groupby(kdf2.A, as_index=as_index).agg(
                              {"B": ["min", "max"], "C": "sum"}
                          )
                      ),
                      sort(
                          pdf1.groupby(pdf2.A, as_index=as_index).agg(
                              {"B": ["min", "max"], "C": "sum"}
                          )
                      ),
                  )
                  self.assert_eq(
                      sort(kdf1.groupby([kdf1.C, kdf2.A], as_index=as_index).agg("sum")),
                      sort(pdf1.groupby([pdf1.C, pdf2.A], as_index=as_index).agg("sum")),
                  )
                  self.assert_eq(
                      sort(kdf1.groupby([kdf1.C + 1, kdf2.A], as_index=as_index).agg("sum")),
                      sort(pdf1.groupby([pdf1.C + 1, pdf2.A], as_index=as_index).agg("sum")),
                  )
  
          # multi-index columns
          columns = pd.MultiIndex.from_tuples([("Y", "C"), ("X", "B")])
          pdf1.columns = columns
          kdf1.columns = columns
  
          columns = pd.MultiIndex.from_tuples([("X", "A")])
          pdf2.columns = columns
          kdf2.columns = columns
  
          for as_index in [True, False]:
              stats_kdf = kdf1.groupby(kdf2[("X", "A")], as_index=as_index).agg(
                  {("X", "B"): "min", ("Y", "C"): "sum"}
              )
              stats_pdf = pdf1.groupby(pdf2[("X", "A")], as_index=as_index).agg(
                  {("X", "B"): "min", ("Y", "C"): "sum"}
              )
              self.assert_eq(
                  stats_kdf.sort_values(by=[("X", "B"), ("Y", "C")]).reset_index(drop=True),
                  stats_pdf.sort_values(by=[("X", "B"), ("Y", "C")]).reset_index(drop=True),
              )
  
          stats_kdf = kdf1.groupby(kdf2[("X", "A")]).agg(
              {("X", "B"): ["min", "max"], ("Y", "C"): "sum"}
          )
          stats_pdf = pdf1.groupby(pdf2[("X", "A")]).agg(
              {("X", "B"): ["min", "max"], ("Y", "C"): "sum"}
          )
          self.assert_eq(
              stats_kdf.sort_values(
                  by=[("X", "B", "min"), ("X", "B", "max"), ("Y", "C", "sum")]
              ).reset_index(drop=True),
              stats_pdf.sort_values(
                  by=[("X", "B", "min"), ("X", "B", "max"), ("Y", "C", "sum")]
              ).reset_index(drop=True),
          )
  
      def test_duplicated_labels(self):
          pdf1 = pd.DataFrame({"A": [3, 2, 1]})
          pdf2 = pd.DataFrame({"A": [1, 2, 3]})
          kdf1 = ps.from_pandas(pdf1)
          kdf2 = ps.from_pandas(pdf2)
  
          self.assert_eq(
              kdf1.groupby(kdf2.A).sum().sort_index(), pdf1.groupby(pdf2.A).sum().sort_index()
          )
          self.assert_eq(
              kdf1.groupby(kdf2.A, as_index=False).sum().sort_values("A").reset_index(drop=True),
              pdf1.groupby(pdf2.A, as_index=False).sum().sort_values("A").reset_index(drop=True),
          )
  
      def test_apply(self):
          pdf = pd.DataFrame(
              {"a": [1, 2, 3, 4, 5, 6], "b": [1, 1, 2, 3, 5, 8], "c": [1, 4, 9, 16, 25, 36]},
              columns=["a", "b", "c"],
          )
          pkey = pd.Series([1, 1, 2, 3, 5, 8])
          kdf = ps.from_pandas(pdf)
          kkey = ps.from_pandas(pkey)
  
          self.assert_eq(
              kdf.groupby(kkey).apply(lambda x: x + x.min()).sort_index(),
              pdf.groupby(pkey).apply(lambda x: x + x.min()).sort_index(),
          )
          self.assert_eq(
              kdf.groupby(kkey)["a"].apply(lambda x: x + x.min()).sort_index(),
              pdf.groupby(pkey)["a"].apply(lambda x: x + x.min()).sort_index(),
          )
          self.assert_eq(
              kdf.groupby(kkey)[["a"]].apply(lambda x: x + x.min()).sort_index(),
              pdf.groupby(pkey)[["a"]].apply(lambda x: x + x.min()).sort_index(),
          )
          self.assert_eq(
              kdf.groupby(["a", kkey]).apply(lambda x: x + x.min()).sort_index(),
              pdf.groupby(["a", pkey]).apply(lambda x: x + x.min()).sort_index(),
          )
  
      def test_transform(self):
          pdf = pd.DataFrame(
              {"a": [1, 2, 3, 4, 5, 6], "b": [1, 1, 2, 3, 5, 8], "c": [1, 4, 9, 16, 25, 36]},
              columns=["a", "b", "c"],
          )
          pkey = pd.Series([1, 1, 2, 3, 5, 8])
          kdf = ps.from_pandas(pdf)
          kkey = ps.from_pandas(pkey)
  
          self.assert_eq(
              kdf.groupby(kkey).transform(lambda x: x + x.min()).sort_index(),
              pdf.groupby(pkey).transform(lambda x: x + x.min()).sort_index(),
          )
          self.assert_eq(
              kdf.groupby(kkey)["a"].transform(lambda x: x + x.min()).sort_index(),
              pdf.groupby(pkey)["a"].transform(lambda x: x + x.min()).sort_index(),
          )
          self.assert_eq(
              kdf.groupby(kkey)[["a"]].transform(lambda x: x + x.min()).sort_index(),
              pdf.groupby(pkey)[["a"]].transform(lambda x: x + x.min()).sort_index(),
          )
          self.assert_eq(
              kdf.groupby(["a", kkey]).transform(lambda x: x + x.min()).sort_index(),
              pdf.groupby(["a", pkey]).transform(lambda x: x + x.min()).sort_index(),
          )
  
      def test_filter(self):
          pdf = pd.DataFrame(
              {"a": [1, 2, 3, 4, 5, 6], "b": [1, 1, 2, 3, 5, 8], "c": [1, 4, 9, 16, 25, 36]},
              columns=["a", "b", "c"],
          )
          pkey = pd.Series([1, 1, 2, 3, 5, 8])
          kdf = ps.from_pandas(pdf)
          kkey = ps.from_pandas(pkey)
  
          self.assert_eq(
              kdf.groupby(kkey).filter(lambda x: any(x.a == 2)).sort_index(),
              pdf.groupby(pkey).filter(lambda x: any(x.a == 2)).sort_index(),
          )
          self.assert_eq(
              kdf.groupby(kkey)["a"].filter(lambda x: any(x == 2)).sort_index(),
              pdf.groupby(pkey)["a"].filter(lambda x: any(x == 2)).sort_index(),
          )
          self.assert_eq(
              kdf.groupby(kkey)[["a"]].filter(lambda x: any(x.a == 2)).sort_index(),
              pdf.groupby(pkey)[["a"]].filter(lambda x: any(x.a == 2)).sort_index(),
          )
          self.assert_eq(
              kdf.groupby(["a", kkey]).filter(lambda x: any(x.a == 2)).sort_index(),
              pdf.groupby(["a", pkey]).filter(lambda x: any(x.a == 2)).sort_index(),
          )
  
      def test_head(self):
          pdf = pd.DataFrame(
              {
                  "a": [1, 1, 1, 1, 2, 2, 2, 3, 3, 3] * 3,
                  "b": [2, 3, 1, 4, 6, 9, 8, 10, 7, 5] * 3,
                  "c": [3, 5, 2, 5, 1, 2, 6, 4, 3, 6] * 3,
              },
          )
          pkey = pd.Series([1, 1, 1, 1, 2, 2, 2, 3, 3, 3] * 3)
          kdf = ps.from_pandas(pdf)
          kkey = ps.from_pandas(pkey)
  
          self.assert_eq(
              pdf.groupby(pkey).head(2).sort_index(), kdf.groupby(kkey).head(2).sort_index()
          )
          self.assert_eq(
              pdf.groupby("a")["b"].head(2).sort_index(), kdf.groupby("a")["b"].head(2).sort_index()
          )
          self.assert_eq(
              pdf.groupby("a")[["b"]].head(2).sort_index(),
              kdf.groupby("a")[["b"]].head(2).sort_index(),
          )
          self.assert_eq(
              pdf.groupby([pkey, "b"]).head(2).sort_index(),
              kdf.groupby([kkey, "b"]).head(2).sort_index(),
          )
  
      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,
              },
          )
          pkey = pd.Series([1, 1, 2, 3, 5, 8] * 3)
          kdf = ps.from_pandas(pdf)
          kkey = ps.from_pandas(pkey)
  
          for ascending in [True, False]:
              self.assert_eq(
                  kdf.groupby(kkey).cumcount(ascending=ascending).sort_index(),
                  pdf.groupby(pkey).cumcount(ascending=ascending).sort_index(),
              )
              self.assert_eq(
                  kdf.groupby(kkey)["a"].cumcount(ascending=ascending).sort_index(),
                  pdf.groupby(pkey)["a"].cumcount(ascending=ascending).sort_index(),
              )
              self.assert_eq(
                  kdf.groupby(kkey)[["a"]].cumcount(ascending=ascending).sort_index(),
                  pdf.groupby(pkey)[["a"]].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,
              },
          )
          pkey = pd.Series([1, 1, 2, 3, 5, 8] * 3)
          kdf = ps.from_pandas(pdf)
          kkey = ps.from_pandas(pkey)
  
          self.assert_eq(
              kdf.groupby(kkey).cummin().sort_index(), pdf.groupby(pkey).cummin().sort_index()
          )
          self.assert_eq(
              kdf.groupby(kkey)["a"].cummin().sort_index(),
              pdf.groupby(pkey)["a"].cummin().sort_index(),
          )
          self.assert_eq(
              kdf.groupby(kkey)[["a"]].cummin().sort_index(),
              pdf.groupby(pkey)[["a"]].cummin().sort_index(),
          )
  
      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,
              },
          )
          pkey = pd.Series([1, 1, 2, 3, 5, 8] * 3)
          kdf = ps.from_pandas(pdf)
          kkey = ps.from_pandas(pkey)
  
          self.assert_eq(
              kdf.groupby(kkey).cummax().sort_index(), pdf.groupby(pkey).cummax().sort_index()
          )
          self.assert_eq(
              kdf.groupby(kkey)["a"].cummax().sort_index(),
              pdf.groupby(pkey)["a"].cummax().sort_index(),
          )
          self.assert_eq(
              kdf.groupby(kkey)[["a"]].cummax().sort_index(),
              pdf.groupby(pkey)[["a"]].cummax().sort_index(),
          )
  
      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,
              },
          )
          pkey = pd.Series([1, 1, 2, 3, 5, 8] * 3)
          kdf = ps.from_pandas(pdf)
          kkey = ps.from_pandas(pkey)
  
          self.assert_eq(
              kdf.groupby(kkey).cumsum().sort_index(), pdf.groupby(pkey).cumsum().sort_index()
          )
          self.assert_eq(
              kdf.groupby(kkey)["a"].cumsum().sort_index(),
              pdf.groupby(pkey)["a"].cumsum().sort_index(),
          )
          self.assert_eq(
              kdf.groupby(kkey)[["a"]].cumsum().sort_index(),
              pdf.groupby(pkey)[["a"]].cumsum().sort_index(),
          )
  
      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, 4, 9, 16, 25, 36] * 3,
              },
          )
          pkey = pd.Series([1, 1, 2, 3, 5, 8] * 3)
          kdf = ps.from_pandas(pdf)
          kkey = ps.from_pandas(pkey)
  
          self.assert_eq(
              kdf.groupby(kkey).cumprod().sort_index(),
              pdf.groupby(pkey).cumprod().sort_index(),
              almost=True,
          )
          self.assert_eq(
              kdf.groupby(kkey)["a"].cumprod().sort_index(),
              pdf.groupby(pkey)["a"].cumprod().sort_index(),
              almost=True,
          )
          self.assert_eq(
              kdf.groupby(kkey)[["a"]].cumprod().sort_index(),
              pdf.groupby(pkey)[["a"]].cumprod().sort_index(),
              almost=True,
          )
  
      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,
              }
          )
          pkey = pd.Series([1, 1, 2, 3, 5, 8] * 3)
          kdf = ps.from_pandas(pdf)
          kkey = ps.from_pandas(pkey)
  
          self.assert_eq(kdf.groupby(kkey).diff().sort_index(), pdf.groupby(pkey).diff().sort_index())
          self.assert_eq(
              kdf.groupby(kkey)["a"].diff().sort_index(), pdf.groupby(pkey)["a"].diff().sort_index()
          )
          self.assert_eq(
              kdf.groupby(kkey)[["a"]].diff().sort_index(),
              pdf.groupby(pkey)[["a"]].diff().sort_index(),
          )
  
          self.assert_eq(kdf.groupby(kkey).diff().sum(), pdf.groupby(pkey).diff().sum().astype(int))
          self.assert_eq(kdf.groupby(kkey)["a"].diff().sum(), pdf.groupby(pkey)["a"].diff().sum())
  
      def test_rank(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,
              },
          )
          pkey = pd.Series([1, 1, 2, 3, 5, 8] * 3)
          kdf = ps.from_pandas(pdf)
          kkey = ps.from_pandas(pkey)
  
          self.assert_eq(kdf.groupby(kkey).rank().sort_index(), pdf.groupby(pkey).rank().sort_index())
          self.assert_eq(
              kdf.groupby(kkey)["a"].rank().sort_index(), pdf.groupby(pkey)["a"].rank().sort_index()
          )
          self.assert_eq(
              kdf.groupby(kkey)[["a"]].rank().sort_index(),
              pdf.groupby(pkey)[["a"]].rank().sort_index(),
          )
  
          self.assert_eq(kdf.groupby(kkey).rank().sum(), pdf.groupby(pkey).rank().sum())
          self.assert_eq(kdf.groupby(kkey)["a"].rank().sum(), pdf.groupby(pkey)["a"].rank().sum())
  
      @unittest.skipIf(pd.__version__ < "0.24.0", "not supported before pandas 0.24.0")
      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,
              },
          )
          pkey = pd.Series([1, 1, 2, 2, 3, 4] * 3)
          kdf = ps.from_pandas(pdf)
          kkey = ps.from_pandas(pkey)
  
          self.assert_eq(
              kdf.groupby(kkey).shift().sort_index(), pdf.groupby(pkey).shift().sort_index()
          )
          self.assert_eq(
              kdf.groupby(kkey)["a"].shift().sort_index(), pdf.groupby(pkey)["a"].shift().sort_index()
          )
          self.assert_eq(
              kdf.groupby(kkey)[["a"]].shift().sort_index(),
              pdf.groupby(pkey)[["a"]].shift().sort_index(),
          )
  
          self.assert_eq(kdf.groupby(kkey).shift().sum(), pdf.groupby(pkey).shift().sum().astype(int))
          self.assert_eq(kdf.groupby(kkey)["a"].shift().sum(), pdf.groupby(pkey)["a"].shift().sum())
  
      def test_fillna(self):
          pdf = pd.DataFrame(
              {
                  "A": [1, 1, 2, 2] * 3,
                  "B": [2, 4, None, 3] * 3,
                  "C": [None, None, None, 1] * 3,
                  "D": [0, 1, 5, 4] * 3,
              }
          )
          pkey = pd.Series([1, 1, 2, 2] * 3)
          kdf = ps.from_pandas(pdf)
          kkey = ps.from_pandas(pkey)
  
          self.assert_eq(
              kdf.groupby(kkey).fillna(0).sort_index(), pdf.groupby(pkey).fillna(0).sort_index()
          )
          self.assert_eq(
              kdf.groupby(kkey)["C"].fillna(0).sort_index(),
              pdf.groupby(pkey)["C"].fillna(0).sort_index(),
          )
          self.assert_eq(
              kdf.groupby(kkey)[["C"]].fillna(0).sort_index(),
              pdf.groupby(pkey)[["C"]].fillna(0).sort_index(),
          )
          self.assert_eq(
              kdf.groupby(kkey).fillna(method="bfill").sort_index(),
              pdf.groupby(pkey).fillna(method="bfill").sort_index(),
          )
          self.assert_eq(
              kdf.groupby(kkey)["C"].fillna(method="bfill").sort_index(),
              pdf.groupby(pkey)["C"].fillna(method="bfill").sort_index(),
          )
          self.assert_eq(
              kdf.groupby(kkey)[["C"]].fillna(method="bfill").sort_index(),
              pdf.groupby(pkey)[["C"]].fillna(method="bfill").sort_index(),
          )
          self.assert_eq(
              kdf.groupby(kkey).fillna(method="ffill").sort_index(),
              pdf.groupby(pkey).fillna(method="ffill").sort_index(),
          )
          self.assert_eq(
              kdf.groupby(kkey)["C"].fillna(method="ffill").sort_index(),
              pdf.groupby(pkey)["C"].fillna(method="ffill").sort_index(),
          )
          self.assert_eq(
              kdf.groupby(kkey)[["C"]].fillna(method="ffill").sort_index(),
              pdf.groupby(pkey)[["C"]].fillna(method="ffill").sort_index(),
          )
  
  
  if __name__ == "__main__":
      from pyspark.pandas.tests.test_ops_on_diff_frames_groupby 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)
  