Python pandas.Series.plot() Examples

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_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)) 

def test_hist_kde_color(self):
        if not self.mpl_ge_1_5_0:
            pytest.skip("mpl is not supported")

        _, 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']) 

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_kde_kwargs(self):
        _skip_if_no_scipy_gaussian_kde()
        if not self.mpl_ge_1_5_0:
            pytest.skip("mpl is not supported")

        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') 

def test_hist_kde(self):
        if not self.mpl_ge_1_5_0:
            pytest.skip("mpl is not supported")

        _, 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)) 

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_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_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_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)) 

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_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 == '' 

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_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_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_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) 

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_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) 

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)() 

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)) 

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_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) 

def test_kde_missing_vals(self):
        _skip_if_no_scipy_gaussian_kde()
        if not self.mpl_ge_1_5_0:
            pytest.skip("mpl is not supported")

        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())) 

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_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) 

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() 

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 

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 

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])