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- # coding: utf-8
- """ Test cases for Series.plot """
- from datetime import datetime
- from itertools import chain
- import numpy as np
- from numpy.random import randn
- import pytest
- from pandas.compat import lrange, range
- import pandas.util._test_decorators as td
- import pandas as pd
- from pandas import DataFrame, Series, date_range
- from pandas.tests.plotting.common import (
- TestPlotBase, _check_plot_works, _ok_for_gaussian_kde,
- _skip_if_no_scipy_gaussian_kde)
- import pandas.util.testing as tm
- import pandas.plotting as plotting
- @td.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
- key = 'axes.prop_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([1e-1, 1e0, 1e1, 1e2, 1e3, 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([1e-5, 1e-4, 1e-3, 1e-2, 1e-1, 1e0, 1e1])
- _, ax = self.plt.subplots()
- ax = Series([0.1, 0.01, 0.001]).plot(log=True, kind='bar', ax=ax)
- ymin = 0.0007943282347242822
- ymax = 0.12589254117941673
- 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_bar_user_colors(self):
- s = Series([1, 2, 3, 4])
- ax = s.plot.bar(color=['red', 'blue', 'blue', 'red'])
- result = [p.get_facecolor() for p in ax.patches]
- expected = [(1., 0., 0., 1.),
- (0., 0., 1., 1.),
- (0., 0., 1., 1.),
- (1., 0., 0., 1.)]
- assert result == expected
- 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]
- def test_unsorted_index_xlim(self):
- ser = Series([0., 1., np.nan, 3., 4., 5., 6.],
- index=[1., 0., 3., 2., np.nan, 3., 2.])
- _, ax = self.plt.subplots()
- ax = ser.plot(ax=ax)
- xmin, xmax = ax.get_xlim()
- lines = ax.get_lines()
- assert xmin <= np.nanmin(lines[0].get_data(orig=False)[0])
- assert xmax >= np.nanmax(lines[0].get_data(orig=False)[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())]
- expected_texts = list(chain.from_iterable(zip(series.index, pcts)))
- 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
- 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_secondary_logy(self):
- # GH 25545
- s1 = Series(np.random.randn(30))
- s2 = Series(np.random.randn(30))
- ax1 = s1.plot(logy=True)
- ax2 = s2.plot(secondary_y=True, logy=True)
- assert ax1.get_yscale() == 'log'
- assert ax2.get_yscale() == 'log'
- @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
- @td.skip_if_no_scipy
- 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))
- _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
- @td.skip_if_no_scipy
- def test_kde_kwargs(self):
- _skip_if_no_scipy_gaussian_kde()
- sample_points = np.linspace(-100, 100, 20)
- _check_plot_works(self.ts.plot.kde, bw_method='scott', ind=20)
- _check_plot_works(self.ts.plot.kde, bw_method=None, ind=20)
- _check_plot_works(self.ts.plot.kde, bw_method=None, ind=np.int(20))
- _check_plot_works(self.ts.plot.kde, bw_method=.5, ind=sample_points)
- _check_plot_works(self.ts.plot.density, bw_method=.5,
- ind=sample_points)
- _, ax = self.plt.subplots()
- ax = self.ts.plot.kde(logy=True, bw_method=.5, ind=sample_points,
- ax=ax)
- self._check_ax_scales(ax, yaxis='log')
- self._check_text_labels(ax.yaxis.get_label(), 'Density')
- @pytest.mark.slow
- @td.skip_if_no_scipy
- def test_kde_missing_vals(self):
- _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()
- _, 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
- @td.skip_if_no_scipy
- 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)
- _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
- # MPL > 2.0.0 will most likely use TypeError here
- with pytest.raises((TypeError, ValueError)):
- s.plot(yerr=s_err)
- # This XPASSES when tested with mpl == 3.0.1
- @td.xfail_if_mpl_2_2
- 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
- def_colors = self._unpack_cycler(mpl.rcParams)
- 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)
- @pytest.mark.xfail
- def test_plot_accessor_updates_on_inplace(self):
- s = Series([1, 2, 3, 4])
- _, ax = self.plt.subplots()
- ax = s.plot(ax=ax)
- before = ax.xaxis.get_ticklocs()
- s.drop([0, 1], inplace=True)
- _, ax = self.plt.subplots()
- after = ax.xaxis.get_ticklocs()
- tm.assert_numpy_array_equal(before, after)
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