content: # coding: utf-8
  
  """ Test cases for Series.plot """
  
  
  import itertools
  import pytest
  
  from datetime import datetime
  
  import pandas as pd
  from pandas import Series, DataFrame, date_range
  from pandas.compat import range, lrange
  import pandas.util.testing as tm
  
  import numpy as np
  from numpy.random import randn
  
  import pandas.plotting as plotting
  from pandas.tests.plotting.common import (TestPlotBase, _check_plot_works,
                                            _skip_if_no_scipy_gaussian_kde,
                                            _ok_for_gaussian_kde)
  
  tm._skip_if_no_mpl()
  
  
  class TestSeriesPlots(TestPlotBase):
  
      def setup_method(self, method):
          TestPlotBase.setup_method(self, method)
          import matplotlib as mpl
          mpl.rcdefaults()
  
          self.ts = tm.makeTimeSeries()
          self.ts.name = 'ts'
  
          self.series = tm.makeStringSeries()
          self.series.name = 'series'
  
          self.iseries = tm.makePeriodSeries()
          self.iseries.name = 'iseries'
  
      @pytest.mark.slow
      def test_plot(self):
          _check_plot_works(self.ts.plot, label='foo')
          _check_plot_works(self.ts.plot, use_index=False)
          axes = _check_plot_works(self.ts.plot, rot=0)
          self._check_ticks_props(axes, xrot=0)
  
          ax = _check_plot_works(self.ts.plot, style='.', logy=True)
          self._check_ax_scales(ax, yaxis='log')
  
          ax = _check_plot_works(self.ts.plot, style='.', logx=True)
          self._check_ax_scales(ax, xaxis='log')
  
          ax = _check_plot_works(self.ts.plot, style='.', loglog=True)
          self._check_ax_scales(ax, xaxis='log', yaxis='log')
  
          _check_plot_works(self.ts[:10].plot.bar)
          _check_plot_works(self.ts.plot.area, stacked=False)
          _check_plot_works(self.iseries.plot)
  
          for kind in ['line', 'bar', 'barh', 'kde', 'hist', 'box']:
              if not _ok_for_gaussian_kde(kind):
                  continue
              _check_plot_works(self.series[:5].plot, kind=kind)
  
          _check_plot_works(self.series[:10].plot.barh)
          ax = _check_plot_works(Series(randn(10)).plot.bar, color='black')
          self._check_colors([ax.patches[0]], facecolors=['black'])
  
          # GH 6951
          ax = _check_plot_works(self.ts.plot, subplots=True)
          self._check_axes_shape(ax, axes_num=1, layout=(1, 1))
  
          ax = _check_plot_works(self.ts.plot, subplots=True, layout=(-1, 1))
          self._check_axes_shape(ax, axes_num=1, layout=(1, 1))
          ax = _check_plot_works(self.ts.plot, subplots=True, layout=(1, -1))
          self._check_axes_shape(ax, axes_num=1, layout=(1, 1))
  
      @pytest.mark.slow
      def test_plot_figsize_and_title(self):
          # figsize and title
          _, ax = self.plt.subplots()
          ax = self.series.plot(title='Test', figsize=(16, 8), ax=ax)
          self._check_text_labels(ax.title, 'Test')
          self._check_axes_shape(ax, axes_num=1, layout=(1, 1), figsize=(16, 8))
  
      def test_dont_modify_rcParams(self):
          # GH 8242
          if self.mpl_ge_1_5_0:
              key = 'axes.prop_cycle'
          else:
              key = 'axes.color_cycle'
          colors = self.plt.rcParams[key]
          _, ax = self.plt.subplots()
          Series([1, 2, 3]).plot(ax=ax)
          assert colors == self.plt.rcParams[key]
  
      def test_ts_line_lim(self):
          fig, ax = self.plt.subplots()
          ax = self.ts.plot(ax=ax)
          xmin, xmax = ax.get_xlim()
          lines = ax.get_lines()
          assert xmin == lines[0].get_data(orig=False)[0][0]
          assert xmax == lines[0].get_data(orig=False)[0][-1]
          tm.close()
  
          ax = self.ts.plot(secondary_y=True, ax=ax)
          xmin, xmax = ax.get_xlim()
          lines = ax.get_lines()
          assert xmin == lines[0].get_data(orig=False)[0][0]
          assert xmax == lines[0].get_data(orig=False)[0][-1]
  
      def test_ts_area_lim(self):
          _, ax = self.plt.subplots()
          ax = self.ts.plot.area(stacked=False, ax=ax)
          xmin, xmax = ax.get_xlim()
          line = ax.get_lines()[0].get_data(orig=False)[0]
          assert xmin == line[0]
          assert xmax == line[-1]
          tm.close()
  
          # GH 7471
          _, ax = self.plt.subplots()
          ax = self.ts.plot.area(stacked=False, x_compat=True, ax=ax)
          xmin, xmax = ax.get_xlim()
          line = ax.get_lines()[0].get_data(orig=False)[0]
          assert xmin == line[0]
          assert xmax == line[-1]
          tm.close()
  
          tz_ts = self.ts.copy()
          tz_ts.index = tz_ts.tz_localize('GMT').tz_convert('CET')
          _, ax = self.plt.subplots()
          ax = tz_ts.plot.area(stacked=False, x_compat=True, ax=ax)
          xmin, xmax = ax.get_xlim()
          line = ax.get_lines()[0].get_data(orig=False)[0]
          assert xmin == line[0]
          assert xmax == line[-1]
          tm.close()
  
          _, ax = self.plt.subplots()
          ax = tz_ts.plot.area(stacked=False, secondary_y=True, ax=ax)
          xmin, xmax = ax.get_xlim()
          line = ax.get_lines()[0].get_data(orig=False)[0]
          assert xmin == line[0]
          assert xmax == line[-1]
  
      def test_label(self):
          s = Series([1, 2])
          _, ax = self.plt.subplots()
          ax = s.plot(label='LABEL', legend=True, ax=ax)
          self._check_legend_labels(ax, labels=['LABEL'])
          self.plt.close()
          _, ax = self.plt.subplots()
          ax = s.plot(legend=True, ax=ax)
          self._check_legend_labels(ax, labels=['None'])
          self.plt.close()
          # get name from index
          s.name = 'NAME'
          _, ax = self.plt.subplots()
          ax = s.plot(legend=True, ax=ax)
          self._check_legend_labels(ax, labels=['NAME'])
          self.plt.close()
          # override the default
          _, ax = self.plt.subplots()
          ax = s.plot(legend=True, label='LABEL', ax=ax)
          self._check_legend_labels(ax, labels=['LABEL'])
          self.plt.close()
          # Add lebel info, but don't draw
          _, ax = self.plt.subplots()
          ax = s.plot(legend=False, label='LABEL', ax=ax)
          assert ax.get_legend() is None  # Hasn't been drawn
          ax.legend()  # draw it
          self._check_legend_labels(ax, labels=['LABEL'])
  
      def test_line_area_nan_series(self):
          values = [1, 2, np.nan, 3]
          s = Series(values)
          ts = Series(values, index=tm.makeDateIndex(k=4))
  
          for d in [s, ts]:
              ax = _check_plot_works(d.plot)
              masked = ax.lines[0].get_ydata()
              # remove nan for comparison purpose
              exp = np.array([1, 2, 3], dtype=np.float64)
              tm.assert_numpy_array_equal(np.delete(masked.data, 2), exp)
              tm.assert_numpy_array_equal(
                  masked.mask, np.array([False, False, True, False]))
  
              expected = np.array([1, 2, 0, 3], dtype=np.float64)
              ax = _check_plot_works(d.plot, stacked=True)
              tm.assert_numpy_array_equal(ax.lines[0].get_ydata(), expected)
              ax = _check_plot_works(d.plot.area)
              tm.assert_numpy_array_equal(ax.lines[0].get_ydata(), expected)
              ax = _check_plot_works(d.plot.area, stacked=False)
              tm.assert_numpy_array_equal(ax.lines[0].get_ydata(), expected)
  
      def test_line_use_index_false(self):
          s = Series([1, 2, 3], index=['a', 'b', 'c'])
          s.index.name = 'The Index'
          _, ax = self.plt.subplots()
          ax = s.plot(use_index=False, ax=ax)
          label = ax.get_xlabel()
          assert label == ''
          _, ax = self.plt.subplots()
          ax2 = s.plot.bar(use_index=False, ax=ax)
          label2 = ax2.get_xlabel()
          assert label2 == ''
  
      @pytest.mark.slow
      def test_bar_log(self):
          expected = np.array([1., 10., 100., 1000.])
  
          if not self.mpl_le_1_2_1:
              expected = np.hstack((.1, expected, 1e4))
  
          _, ax = self.plt.subplots()
          ax = Series([200, 500]).plot.bar(log=True, ax=ax)
          tm.assert_numpy_array_equal(ax.yaxis.get_ticklocs(), expected)
          tm.close()
  
          _, ax = self.plt.subplots()
          ax = Series([200, 500]).plot.barh(log=True, ax=ax)
          tm.assert_numpy_array_equal(ax.xaxis.get_ticklocs(), expected)
          tm.close()
  
          # GH 9905
          expected = np.array([1.0e-03, 1.0e-02, 1.0e-01, 1.0e+00])
  
          if not self.mpl_le_1_2_1:
              expected = np.hstack((1.0e-04, expected, 1.0e+01))
          if self.mpl_ge_2_0_0:
              expected = np.hstack((1.0e-05, expected))
  
          _, ax = self.plt.subplots()
          ax = Series([0.1, 0.01, 0.001]).plot(log=True, kind='bar', ax=ax)
          ymin = 0.0007943282347242822 if self.mpl_ge_2_0_0 else 0.001
          ymax = 0.12589254117941673 if self.mpl_ge_2_0_0 else .10000000000000001
          res = ax.get_ylim()
          tm.assert_almost_equal(res[0], ymin)
          tm.assert_almost_equal(res[1], ymax)
          tm.assert_numpy_array_equal(ax.yaxis.get_ticklocs(), expected)
          tm.close()
  
          _, ax = self.plt.subplots()
          ax = Series([0.1, 0.01, 0.001]).plot(log=True, kind='barh', ax=ax)
          res = ax.get_xlim()
          tm.assert_almost_equal(res[0], ymin)
          tm.assert_almost_equal(res[1], ymax)
          tm.assert_numpy_array_equal(ax.xaxis.get_ticklocs(), expected)
  
      @pytest.mark.slow
      def test_bar_ignore_index(self):
          df = Series([1, 2, 3, 4], index=['a', 'b', 'c', 'd'])
          _, ax = self.plt.subplots()
          ax = df.plot.bar(use_index=False, ax=ax)
          self._check_text_labels(ax.get_xticklabels(), ['0', '1', '2', '3'])
  
      def test_rotation(self):
          df = DataFrame(randn(5, 5))
          # Default rot 0
          _, ax = self.plt.subplots()
          axes = df.plot(ax=ax)
          self._check_ticks_props(axes, xrot=0)
  
          _, ax = self.plt.subplots()
          axes = df.plot(rot=30, ax=ax)
          self._check_ticks_props(axes, xrot=30)
  
      def test_irregular_datetime(self):
          rng = date_range('1/1/2000', '3/1/2000')
          rng = rng[[0, 1, 2, 3, 5, 9, 10, 11, 12]]
          ser = Series(randn(len(rng)), rng)
          _, ax = self.plt.subplots()
          ax = ser.plot(ax=ax)
          xp = datetime(1999, 1, 1).toordinal()
          ax.set_xlim('1/1/1999', '1/1/2001')
          assert xp == ax.get_xlim()[0]
  
      @pytest.mark.slow
      def test_pie_series(self):
          # if sum of values is less than 1.0, pie handle them as rate and draw
          # semicircle.
          series = Series(np.random.randint(1, 5),
                          index=['a', 'b', 'c', 'd', 'e'], name='YLABEL')
          ax = _check_plot_works(series.plot.pie)
          self._check_text_labels(ax.texts, series.index)
          assert ax.get_ylabel() == 'YLABEL'
  
          # without wedge labels
          ax = _check_plot_works(series.plot.pie, labels=None)
          self._check_text_labels(ax.texts, [''] * 5)
  
          # with less colors than elements
          color_args = ['r', 'g', 'b']
          ax = _check_plot_works(series.plot.pie, colors=color_args)
  
          color_expected = ['r', 'g', 'b', 'r', 'g']
          self._check_colors(ax.patches, facecolors=color_expected)
  
          # with labels and colors
          labels = ['A', 'B', 'C', 'D', 'E']
          color_args = ['r', 'g', 'b', 'c', 'm']
          ax = _check_plot_works(series.plot.pie, labels=labels,
                                 colors=color_args)
          self._check_text_labels(ax.texts, labels)
          self._check_colors(ax.patches, facecolors=color_args)
  
          # with autopct and fontsize
          ax = _check_plot_works(series.plot.pie, colors=color_args,
                                 autopct='%.2f', fontsize=7)
          pcts = ['{0:.2f}'.format(s * 100)
                  for s in series.values / float(series.sum())]
          iters = [iter(series.index), iter(pcts)]
          expected_texts = list(next(it) for it in itertools.cycle(iters))
          self._check_text_labels(ax.texts, expected_texts)
          for t in ax.texts:
              assert t.get_fontsize() == 7
  
          # includes negative value
          with pytest.raises(ValueError):
              series = Series([1, 2, 0, 4, -1], index=['a', 'b', 'c', 'd', 'e'])
              series.plot.pie()
  
          # includes nan
          series = Series([1, 2, np.nan, 4], index=['a', 'b', 'c', 'd'],
                          name='YLABEL')
          ax = _check_plot_works(series.plot.pie)
          self._check_text_labels(ax.texts, ['a', 'b', '', 'd'])
  
      def test_pie_nan(self):
          s = Series([1, np.nan, 1, 1])
          _, ax = self.plt.subplots()
          ax = s.plot.pie(legend=True, ax=ax)
          expected = ['0', '', '2', '3']
          result = [x.get_text() for x in ax.texts]
          assert result == expected
  
      @pytest.mark.slow
      def test_hist_df_kwargs(self):
          df = DataFrame(np.random.randn(10, 2))
          _, ax = self.plt.subplots()
          ax = df.plot.hist(bins=5, ax=ax)
          assert len(ax.patches) == 10
  
      @pytest.mark.slow
      def test_hist_df_with_nonnumerics(self):
          # GH 9853
          with tm.RNGContext(1):
              df = DataFrame(
                  np.random.randn(10, 4), columns=['A', 'B', 'C', 'D'])
          df['E'] = ['x', 'y'] * 5
          _, ax = self.plt.subplots()
          ax = df.plot.hist(bins=5, ax=ax)
          assert len(ax.patches) == 20
  
          _, ax = self.plt.subplots()
          ax = df.plot.hist(ax=ax)  # bins=10
          assert len(ax.patches) == 40
  
      @pytest.mark.slow
      def test_hist_legacy(self):
          _check_plot_works(self.ts.hist)
          _check_plot_works(self.ts.hist, grid=False)
          _check_plot_works(self.ts.hist, figsize=(8, 10))
          # _check_plot_works adds an ax so catch warning. see GH #13188
          with tm.assert_produces_warning(UserWarning):
              _check_plot_works(self.ts.hist,
                                by=self.ts.index.month)
          with tm.assert_produces_warning(UserWarning):
              _check_plot_works(self.ts.hist,
                                by=self.ts.index.month, bins=5)
  
          fig, ax = self.plt.subplots(1, 1)
          _check_plot_works(self.ts.hist, ax=ax)
          _check_plot_works(self.ts.hist, ax=ax, figure=fig)
          _check_plot_works(self.ts.hist, figure=fig)
          tm.close()
  
          fig, (ax1, ax2) = self.plt.subplots(1, 2)
          _check_plot_works(self.ts.hist, figure=fig, ax=ax1)
          _check_plot_works(self.ts.hist, figure=fig, ax=ax2)
  
          with pytest.raises(ValueError):
              self.ts.hist(by=self.ts.index, figure=fig)
  
      @pytest.mark.slow
      def test_hist_bins_legacy(self):
          df = DataFrame(np.random.randn(10, 2))
          ax = df.hist(bins=2)[0][0]
          assert len(ax.patches) == 2
  
      @pytest.mark.slow
      def test_hist_layout(self):
          df = self.hist_df
          with pytest.raises(ValueError):
              df.height.hist(layout=(1, 1))
  
          with pytest.raises(ValueError):
              df.height.hist(layout=[1, 1])
  
      @pytest.mark.slow
      def test_hist_layout_with_by(self):
          df = self.hist_df
  
          # _check_plot_works adds an ax so catch warning. see GH #13188
          with tm.assert_produces_warning(UserWarning):
              axes = _check_plot_works(df.height.hist,
                                       by=df.gender, layout=(2, 1))
          self._check_axes_shape(axes, axes_num=2, layout=(2, 1))
  
          with tm.assert_produces_warning(UserWarning):
              axes = _check_plot_works(df.height.hist,
                                       by=df.gender, layout=(3, -1))
          self._check_axes_shape(axes, axes_num=2, layout=(3, 1))
  
          with tm.assert_produces_warning(UserWarning):
              axes = _check_plot_works(df.height.hist,
                                       by=df.category, layout=(4, 1))
          self._check_axes_shape(axes, axes_num=4, layout=(4, 1))
  
          with tm.assert_produces_warning(UserWarning):
              axes = _check_plot_works(df.height.hist,
                                       by=df.category, layout=(2, -1))
          self._check_axes_shape(axes, axes_num=4, layout=(2, 2))
  
          with tm.assert_produces_warning(UserWarning):
              axes = _check_plot_works(df.height.hist,
                                       by=df.category, layout=(3, -1))
          self._check_axes_shape(axes, axes_num=4, layout=(3, 2))
  
          with tm.assert_produces_warning(UserWarning):
              axes = _check_plot_works(df.height.hist,
                                       by=df.category, layout=(-1, 4))
          self._check_axes_shape(axes, axes_num=4, layout=(1, 4))
  
          with tm.assert_produces_warning(UserWarning):
              axes = _check_plot_works(df.height.hist,
                                       by=df.classroom, layout=(2, 2))
          self._check_axes_shape(axes, axes_num=3, layout=(2, 2))
  
          axes = df.height.hist(by=df.category, layout=(4, 2), figsize=(12, 7))
          self._check_axes_shape(axes, axes_num=4, layout=(4, 2),
                                 figsize=(12, 7))
  
      @pytest.mark.slow
      def test_hist_no_overlap(self):
          from matplotlib.pyplot import subplot, gcf
          x = Series(randn(2))
          y = Series(randn(2))
          subplot(121)
          x.hist()
          subplot(122)
          y.hist()
          fig = gcf()
          axes = fig.axes if self.mpl_ge_1_5_0 else fig.get_axes()
          assert len(axes) == 2
  
      @pytest.mark.slow
      def test_hist_secondary_legend(self):
          # GH 9610
          df = DataFrame(np.random.randn(30, 4), columns=list('abcd'))
  
          # primary -> secondary
          _, ax = self.plt.subplots()
          ax = df['a'].plot.hist(legend=True, ax=ax)
          df['b'].plot.hist(ax=ax, legend=True, secondary_y=True)
          # both legends are dran on left ax
          # left and right axis must be visible
          self._check_legend_labels(ax, labels=['a', 'b (right)'])
          assert ax.get_yaxis().get_visible()
          assert ax.right_ax.get_yaxis().get_visible()
          tm.close()
  
          # secondary -> secondary
          _, ax = self.plt.subplots()
          ax = df['a'].plot.hist(legend=True, secondary_y=True, ax=ax)
          df['b'].plot.hist(ax=ax, legend=True, secondary_y=True)
          # both legends are draw on left ax
          # left axis must be invisible, right axis must be visible
          self._check_legend_labels(ax.left_ax,
                                    labels=['a (right)', 'b (right)'])
          assert not ax.left_ax.get_yaxis().get_visible()
          assert ax.get_yaxis().get_visible()
          tm.close()
  
          # secondary -> primary
          _, ax = self.plt.subplots()
          ax = df['a'].plot.hist(legend=True, secondary_y=True, ax=ax)
          # right axes is returned
          df['b'].plot.hist(ax=ax, legend=True)
          # both legends are draw on left ax
          # left and right axis must be visible
          self._check_legend_labels(ax.left_ax, labels=['a (right)', 'b'])
          assert ax.left_ax.get_yaxis().get_visible()
          assert ax.get_yaxis().get_visible()
          tm.close()
  
      @pytest.mark.slow
      def test_df_series_secondary_legend(self):
          # GH 9779
          df = DataFrame(np.random.randn(30, 3), columns=list('abc'))
          s = Series(np.random.randn(30), name='x')
  
          # primary -> secondary (without passing ax)
          _, ax = self.plt.subplots()
          ax = df.plot(ax=ax)
          s.plot(legend=True, secondary_y=True, ax=ax)
          # both legends are dran on left ax
          # left and right axis must be visible
          self._check_legend_labels(ax, labels=['a', 'b', 'c', 'x (right)'])
          assert ax.get_yaxis().get_visible()
          assert ax.right_ax.get_yaxis().get_visible()
          tm.close()
  
          # primary -> secondary (with passing ax)
          _, ax = self.plt.subplots()
          ax = df.plot(ax=ax)
          s.plot(ax=ax, legend=True, secondary_y=True)
          # both legends are dran on left ax
          # left and right axis must be visible
          self._check_legend_labels(ax, labels=['a', 'b', 'c', 'x (right)'])
          assert ax.get_yaxis().get_visible()
          assert ax.right_ax.get_yaxis().get_visible()
          tm.close()
  
          # seconcary -> secondary (without passing ax)
          _, ax = self.plt.subplots()
          ax = df.plot(secondary_y=True, ax=ax)
          s.plot(legend=True, secondary_y=True, ax=ax)
          # both legends are dran on left ax
          # left axis must be invisible and right axis must be visible
          expected = ['a (right)', 'b (right)', 'c (right)', 'x (right)']
          self._check_legend_labels(ax.left_ax, labels=expected)
          assert not ax.left_ax.get_yaxis().get_visible()
          assert ax.get_yaxis().get_visible()
          tm.close()
  
          # secondary -> secondary (with passing ax)
          _, ax = self.plt.subplots()
          ax = df.plot(secondary_y=True, ax=ax)
          s.plot(ax=ax, legend=True, secondary_y=True)
          # both legends are dran on left ax
          # left axis must be invisible and right axis must be visible
          expected = ['a (right)', 'b (right)', 'c (right)', 'x (right)']
          self._check_legend_labels(ax.left_ax, expected)
          assert not ax.left_ax.get_yaxis().get_visible()
          assert ax.get_yaxis().get_visible()
          tm.close()
  
          # secondary -> secondary (with passing ax)
          _, ax = self.plt.subplots()
          ax = df.plot(secondary_y=True, mark_right=False, ax=ax)
          s.plot(ax=ax, legend=True, secondary_y=True)
          # both legends are dran on left ax
          # left axis must be invisible and right axis must be visible
          expected = ['a', 'b', 'c', 'x (right)']
          self._check_legend_labels(ax.left_ax, expected)
          assert not ax.left_ax.get_yaxis().get_visible()
          assert ax.get_yaxis().get_visible()
          tm.close()
  
      @pytest.mark.slow
      def test_plot_fails_with_dupe_color_and_style(self):
          x = Series(randn(2))
          with pytest.raises(ValueError):
              _, ax = self.plt.subplots()
              x.plot(style='k--', color='k', ax=ax)
  
      @pytest.mark.slow
      def test_hist_kde(self):
          _, ax = self.plt.subplots()
          ax = self.ts.plot.hist(logy=True, ax=ax)
          self._check_ax_scales(ax, yaxis='log')
          xlabels = ax.get_xticklabels()
          # ticks are values, thus ticklabels are blank
          self._check_text_labels(xlabels, [''] * len(xlabels))
          ylabels = ax.get_yticklabels()
          self._check_text_labels(ylabels, [''] * len(ylabels))
  
          tm._skip_if_no_scipy()
          _skip_if_no_scipy_gaussian_kde()
          _check_plot_works(self.ts.plot.kde)
          _check_plot_works(self.ts.plot.density)
          _, ax = self.plt.subplots()
          ax = self.ts.plot.kde(logy=True, ax=ax)
          self._check_ax_scales(ax, yaxis='log')
          xlabels = ax.get_xticklabels()
          self._check_text_labels(xlabels, [''] * len(xlabels))
          ylabels = ax.get_yticklabels()
          self._check_text_labels(ylabels, [''] * len(ylabels))
  
      @pytest.mark.slow
      def test_kde_kwargs(self):
          tm._skip_if_no_scipy()
          _skip_if_no_scipy_gaussian_kde()
          from numpy import linspace
          _check_plot_works(self.ts.plot.kde, bw_method=.5,
                            ind=linspace(-100, 100, 20))
          _check_plot_works(self.ts.plot.density, bw_method=.5,
                            ind=linspace(-100, 100, 20))
          _, ax = self.plt.subplots()
          ax = self.ts.plot.kde(logy=True, bw_method=.5,
                                ind=linspace(-100, 100, 20), ax=ax)
          self._check_ax_scales(ax, yaxis='log')
          self._check_text_labels(ax.yaxis.get_label(), 'Density')
  
      @pytest.mark.slow
      def test_kde_missing_vals(self):
          tm._skip_if_no_scipy()
          _skip_if_no_scipy_gaussian_kde()
          s = Series(np.random.uniform(size=50))
          s[0] = np.nan
          axes = _check_plot_works(s.plot.kde)
  
          # gh-14821: check if the values have any missing values
          assert any(~np.isnan(axes.lines[0].get_xdata()))
  
      @pytest.mark.slow
      def test_hist_kwargs(self):
          _, ax = self.plt.subplots()
          ax = self.ts.plot.hist(bins=5, ax=ax)
          assert len(ax.patches) == 5
          self._check_text_labels(ax.yaxis.get_label(), 'Frequency')
          tm.close()
  
          if self.mpl_ge_1_3_1:
              _, ax = self.plt.subplots()
              ax = self.ts.plot.hist(orientation='horizontal', ax=ax)
              self._check_text_labels(ax.xaxis.get_label(), 'Frequency')
              tm.close()
  
              _, ax = self.plt.subplots()
              ax = self.ts.plot.hist(align='left', stacked=True, ax=ax)
              tm.close()
  
      @pytest.mark.slow
      def test_hist_kde_color(self):
          _, ax = self.plt.subplots()
          ax = self.ts.plot.hist(logy=True, bins=10, color='b', ax=ax)
          self._check_ax_scales(ax, yaxis='log')
          assert len(ax.patches) == 10
          self._check_colors(ax.patches, facecolors=['b'] * 10)
  
          tm._skip_if_no_scipy()
          _skip_if_no_scipy_gaussian_kde()
          _, ax = self.plt.subplots()
          ax = self.ts.plot.kde(logy=True, color='r', ax=ax)
          self._check_ax_scales(ax, yaxis='log')
          lines = ax.get_lines()
          assert len(lines) == 1
          self._check_colors(lines, ['r'])
  
      @pytest.mark.slow
      def test_boxplot_series(self):
          _, ax = self.plt.subplots()
          ax = self.ts.plot.box(logy=True, ax=ax)
          self._check_ax_scales(ax, yaxis='log')
          xlabels = ax.get_xticklabels()
          self._check_text_labels(xlabels, [self.ts.name])
          ylabels = ax.get_yticklabels()
          self._check_text_labels(ylabels, [''] * len(ylabels))
  
      @pytest.mark.slow
      def test_kind_both_ways(self):
          s = Series(range(3))
          kinds = (plotting._core._common_kinds +
                   plotting._core._series_kinds)
          _, ax = self.plt.subplots()
          for kind in kinds:
              if not _ok_for_gaussian_kde(kind):
                  continue
              s.plot(kind=kind, ax=ax)
              getattr(s.plot, kind)()
  
      @pytest.mark.slow
      def test_invalid_plot_data(self):
          s = Series(list('abcd'))
          _, ax = self.plt.subplots()
          for kind in plotting._core._common_kinds:
              if not _ok_for_gaussian_kde(kind):
                  continue
              with pytest.raises(TypeError):
                  s.plot(kind=kind, ax=ax)
  
      @pytest.mark.slow
      def test_valid_object_plot(self):
          s = Series(lrange(10), dtype=object)
          for kind in plotting._core._common_kinds:
              if not _ok_for_gaussian_kde(kind):
                  continue
              _check_plot_works(s.plot, kind=kind)
  
      def test_partially_invalid_plot_data(self):
          s = Series(['a', 'b', 1.0, 2])
          _, ax = self.plt.subplots()
          for kind in plotting._core._common_kinds:
              if not _ok_for_gaussian_kde(kind):
                  continue
              with pytest.raises(TypeError):
                  s.plot(kind=kind, ax=ax)
  
      def test_invalid_kind(self):
          s = Series([1, 2])
          with pytest.raises(ValueError):
              s.plot(kind='aasdf')
  
      @pytest.mark.slow
      def test_dup_datetime_index_plot(self):
          dr1 = date_range('1/1/2009', periods=4)
          dr2 = date_range('1/2/2009', periods=4)
          index = dr1.append(dr2)
          values = randn(index.size)
          s = Series(values, index=index)
          _check_plot_works(s.plot)
  
      @pytest.mark.slow
      def test_errorbar_plot(self):
  
          s = Series(np.arange(10), name='x')
          s_err = np.random.randn(10)
          d_err = DataFrame(randn(10, 2), index=s.index, columns=['x', 'y'])
          # test line and bar plots
          kinds = ['line', 'bar']
          for kind in kinds:
              ax = _check_plot_works(s.plot, yerr=Series(s_err), kind=kind)
              self._check_has_errorbars(ax, xerr=0, yerr=1)
              ax = _check_plot_works(s.plot, yerr=s_err, kind=kind)
              self._check_has_errorbars(ax, xerr=0, yerr=1)
              ax = _check_plot_works(s.plot, yerr=s_err.tolist(), kind=kind)
              self._check_has_errorbars(ax, xerr=0, yerr=1)
              ax = _check_plot_works(s.plot, yerr=d_err, kind=kind)
              self._check_has_errorbars(ax, xerr=0, yerr=1)
              ax = _check_plot_works(s.plot, xerr=0.2, yerr=0.2, kind=kind)
              self._check_has_errorbars(ax, xerr=1, yerr=1)
  
          ax = _check_plot_works(s.plot, xerr=s_err)
          self._check_has_errorbars(ax, xerr=1, yerr=0)
  
          # test time series plotting
          ix = date_range('1/1/2000', '1/1/2001', freq='M')
          ts = Series(np.arange(12), index=ix, name='x')
          ts_err = Series(np.random.randn(12), index=ix)
          td_err = DataFrame(randn(12, 2), index=ix, columns=['x', 'y'])
  
          ax = _check_plot_works(ts.plot, yerr=ts_err)
          self._check_has_errorbars(ax, xerr=0, yerr=1)
          ax = _check_plot_works(ts.plot, yerr=td_err)
          self._check_has_errorbars(ax, xerr=0, yerr=1)
  
          # check incorrect lengths and types
          with pytest.raises(ValueError):
              s.plot(yerr=np.arange(11))
  
          s_err = ['zzz'] * 10
          # in mpl 1.5+ this is a TypeError
          with pytest.raises((ValueError, TypeError)):
              s.plot(yerr=s_err)
  
      def test_table(self):
          _check_plot_works(self.series.plot, table=True)
          _check_plot_works(self.series.plot, table=self.series)
  
      @pytest.mark.slow
      def test_series_grid_settings(self):
          # Make sure plot defaults to rcParams['axes.grid'] setting, GH 9792
          self._check_grid_settings(Series([1, 2, 3]),
                                    plotting._core._series_kinds +
                                    plotting._core._common_kinds)
  
      @pytest.mark.slow
      def test_standard_colors(self):
          from pandas.plotting._style import _get_standard_colors
  
          for c in ['r', 'red', 'green', '#FF0000']:
              result = _get_standard_colors(1, color=c)
              assert result == [c]
  
              result = _get_standard_colors(1, color=[c])
              assert result == [c]
  
              result = _get_standard_colors(3, color=c)
              assert result == [c] * 3
  
              result = _get_standard_colors(3, color=[c])
              assert result == [c] * 3
  
      @pytest.mark.slow
      def test_standard_colors_all(self):
          import matplotlib.colors as colors
          from pandas.plotting._style import _get_standard_colors
  
          # multiple colors like mediumaquamarine
          for c in colors.cnames:
              result = _get_standard_colors(num_colors=1, color=c)
              assert result == [c]
  
              result = _get_standard_colors(num_colors=1, color=[c])
              assert result == [c]
  
              result = _get_standard_colors(num_colors=3, color=c)
              assert result == [c] * 3
  
              result = _get_standard_colors(num_colors=3, color=[c])
              assert result == [c] * 3
  
          # single letter colors like k
          for c in colors.ColorConverter.colors:
              result = _get_standard_colors(num_colors=1, color=c)
              assert result == [c]
  
              result = _get_standard_colors(num_colors=1, color=[c])
              assert result == [c]
  
              result = _get_standard_colors(num_colors=3, color=c)
              assert result == [c] * 3
  
              result = _get_standard_colors(num_colors=3, color=[c])
              assert result == [c] * 3
  
      def test_series_plot_color_kwargs(self):
          # GH1890
          _, ax = self.plt.subplots()
          ax = Series(np.arange(12) + 1).plot(color='green', ax=ax)
          self._check_colors(ax.get_lines(), linecolors=['green'])
  
      def test_time_series_plot_color_kwargs(self):
          # #1890
          _, ax = self.plt.subplots()
          ax = Series(np.arange(12) + 1, index=date_range(
              '1/1/2000', periods=12)).plot(color='green', ax=ax)
          self._check_colors(ax.get_lines(), linecolors=['green'])
  
      def test_time_series_plot_color_with_empty_kwargs(self):
          import matplotlib as mpl
  
          if self.mpl_ge_1_5_0:
              def_colors = self._maybe_unpack_cycler(mpl.rcParams)
          else:
              def_colors = mpl.rcParams['axes.color_cycle']
          index = date_range('1/1/2000', periods=12)
          s = Series(np.arange(1, 13), index=index)
  
          ncolors = 3
  
          _, ax = self.plt.subplots()
          for i in range(ncolors):
              ax = s.plot(ax=ax)
          self._check_colors(ax.get_lines(), linecolors=def_colors[:ncolors])
  
      def test_xticklabels(self):
          # GH11529
          s = Series(np.arange(10), index=['P%02d' % i for i in range(10)])
          _, ax = self.plt.subplots()
          ax = s.plot(xticks=[0, 3, 5, 9], ax=ax)
          exp = ['P%02d' % i for i in [0, 3, 5, 9]]
          self._check_text_labels(ax.get_xticklabels(), exp)
  
      def test_custom_business_day_freq(self):
          # GH7222
          from pandas.tseries.offsets import CustomBusinessDay
          s = Series(range(100, 121), index=pd.bdate_range(
              start='2014-05-01', end='2014-06-01',
              freq=CustomBusinessDay(holidays=['2014-05-26'])))
  
          _check_plot_works(s.plot)
  