code: """ Test cases for GroupBy.plot """
  
  
  import numpy as np
  import pytest
  
  from pandas.compat import is_platform_windows
  import pandas.util._test_decorators as td
  
  from pandas import DataFrame, Index, Series
  import pandas._testing as tm
  from pandas.tests.plotting.common import TestPlotBase
  
  pytestmark = pytest.mark.slow
  
  
  @td.skip_if_no_mpl
  class TestDataFrameGroupByPlots(TestPlotBase):
      @pytest.mark.xfail(
          is_platform_windows(),
          reason="Looks like LinePlot._is_ts_plot is wrong",
          strict=False,
      )
      def test_series_groupby_plotting_nominally_works(self):
          n = 10
          weight = Series(np.random.normal(166, 20, size=n))
          height = Series(np.random.normal(60, 10, size=n))
          with tm.RNGContext(42):
              gender = np.random.choice(["male", "female"], size=n)
  
          weight.groupby(gender).plot()
          tm.close()
          height.groupby(gender).hist()
          tm.close()
          # Regression test for GH8733
          height.groupby(gender).plot(alpha=0.5)
          tm.close()
  
      def test_plotting_with_float_index_works(self):
          # GH 7025
          df = DataFrame(
              {"def": [1, 1, 1, 2, 2, 2, 3, 3, 3], "val": np.random.randn(9)},
              index=[1.0, 2.0, 3.0, 1.0, 2.0, 3.0, 1.0, 2.0, 3.0],
          )
  
          df.groupby("def")["val"].plot()
          tm.close()
          df.groupby("def")["val"].apply(lambda x: x.plot())
          tm.close()
  
      def test_hist_single_row(self):
          # GH10214
          bins = np.arange(80, 100 + 2, 1)
          df = DataFrame({"Name": ["AAA", "BBB"], "ByCol": [1, 2], "Mark": [85, 89]})
          df["Mark"].hist(by=df["ByCol"], bins=bins)
          df = DataFrame({"Name": ["AAA"], "ByCol": [1], "Mark": [85]})
          df["Mark"].hist(by=df["ByCol"], bins=bins)
  
      def test_plot_submethod_works(self):
          df = DataFrame({"x": [1, 2, 3, 4, 5], "y": [1, 2, 3, 2, 1], "z": list("ababa")})
          df.groupby("z").plot.scatter("x", "y")
          tm.close()
          df.groupby("z")["x"].plot.line()
          tm.close()
  
      def test_plot_kwargs(self):
  
          df = DataFrame({"x": [1, 2, 3, 4, 5], "y": [1, 2, 3, 2, 1], "z": list("ababa")})
  
          res = df.groupby("z").plot(kind="scatter", x="x", y="y")
          # check that a scatter plot is effectively plotted: the axes should
          # contain a PathCollection from the scatter plot (GH11805)
          assert len(res["a"].collections) == 1
  
          res = df.groupby("z").plot.scatter(x="x", y="y")
          assert len(res["a"].collections) == 1
  
      @pytest.mark.parametrize("column, expected_axes_num", [(None, 2), ("b", 1)])
      def test_groupby_hist_frame_with_legend(self, column, expected_axes_num):
          # GH 6279 - DataFrameGroupBy histogram can have a legend
          expected_layout = (1, expected_axes_num)
          expected_labels = column or [["a"], ["b"]]
  
          index = Index(15 * ["1"] + 15 * ["2"], name="c")
          df = DataFrame(np.random.randn(30, 2), index=index, columns=["a", "b"])
          g = df.groupby("c")
  
          for axes in g.hist(legend=True, column=column):
              self._check_axes_shape(
                  axes, axes_num=expected_axes_num, layout=expected_layout
              )
              for ax, expected_label in zip(axes[0], expected_labels):
                  self._check_legend_labels(ax, expected_label)
  
      @pytest.mark.parametrize("column", [None, "b"])
      def test_groupby_hist_frame_with_legend_raises(self, column):
          # GH 6279 - DataFrameGroupBy histogram with legend and label raises
          index = Index(15 * ["1"] + 15 * ["2"], name="c")
          df = DataFrame(np.random.randn(30, 2), index=index, columns=["a", "b"])
          g = df.groupby("c")
  
          with pytest.raises(ValueError, match="Cannot use both legend and label"):
              g.hist(legend=True, column=column, label="d")
  
      def test_groupby_hist_series_with_legend(self):
          # GH 6279 - SeriesGroupBy histogram can have a legend
          index = Index(15 * ["1"] + 15 * ["2"], name="c")
          df = DataFrame(np.random.randn(30, 2), index=index, columns=["a", "b"])
          g = df.groupby("c")
  
          for ax in g["a"].hist(legend=True):
              self._check_axes_shape(ax, axes_num=1, layout=(1, 1))
              self._check_legend_labels(ax, ["1", "2"])
  
      def test_groupby_hist_series_with_legend_raises(self):
          # GH 6279 - SeriesGroupBy histogram with legend and label raises
          index = Index(15 * ["1"] + 15 * ["2"], name="c")
          df = DataFrame(np.random.randn(30, 2), index=index, columns=["a", "b"])
          g = df.groupby("c")
  
          with pytest.raises(ValueError, match="Cannot use both legend and label"):
              g.hist(legend=True, label="d")
  
apis: pandas.compat.is_platform_windows pandas.DataFrame numpy.random.randn numpy.random.choice pandas._testing.close numpy.arange numpy.random.normal pandas.Index pandas._testing.RNGContext