""" Test cases for Series.plot """ from datetime import datetime from itertools import chain import numpy as np import pytest import pandas.util._test_decorators as td import pandas as pd from pandas import ( DataFrame, Series, date_range, ) import pandas._testing as tm from pandas.tests.plotting.common import ( TestPlotBase, _check_plot_works, ) import pandas.plotting as plotting pytestmark = pytest.mark.slow @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" 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"]: _check_plot_works(self.series[:5].plot, kind=kind) _check_plot_works(self.series[:10].plot.barh) ax = _check_plot_works(Series(np.random.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_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] self._check_ticks_props(ax, xrot=0) 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] self._check_ticks_props(ax, xrot=30) 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] self._check_ticks_props(ax, xrot=0) 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] self._check_ticks_props(ax, xrot=0) def test_area_sharey_dont_overwrite(self): # GH37942 fig, (ax1, ax2) = self.plt.subplots(1, 2, sharey=True) abs(self.ts).plot(ax=ax1, kind="area") abs(self.ts).plot(ax=ax2, kind="area") assert self.get_y_axis(ax1).joined(ax1, ax2) assert self.get_y_axis(ax2).joined(ax1, ax2) 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_boolean(self): # GH 23719 s = Series([False, False, True]) _check_plot_works(s.plot, include_bool=True) msg = "no numeric data to plot" with pytest.raises(TypeError, match=msg): _check_plot_works(s.plot) 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 == "" 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_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, 0.0, 0.0, 1.0), (0.0, 0.0, 1.0, 1.0), (0.0, 0.0, 1.0, 1.0), (1.0, 0.0, 0.0, 1.0), ] assert result == expected def test_rotation(self): df = DataFrame(np.random.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): from pandas.plotting._matplotlib.converter import DatetimeConverter rng = date_range("1/1/2000", "3/1/2000") rng = rng[[0, 1, 2, 3, 5, 9, 10, 11, 12]] ser = Series(np.random.randn(len(rng)), rng) _, ax = self.plt.subplots() ax = ser.plot(ax=ax) xp = DatetimeConverter.convert(datetime(1999, 1, 1), "", ax) ax.set_xlim("1/1/1999", "1/1/2001") assert xp == ax.get_xlim()[0] self._check_ticks_props(ax, xrot=30) def test_unsorted_index_xlim(self): ser = Series( [0.0, 1.0, np.nan, 3.0, 4.0, 5.0, 6.0], index=[1.0, 0.0, 3.0, 2.0, np.nan, 3.0, 2.0], ) _, 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]) 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 = [f"{s*100:.2f}" for s in series.values / 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 series = Series([1, 2, 0, 4, -1], index=["a", "b", "c", "d", "e"]) with pytest.raises(ValueError, match="pie plot doesn't allow negative values"): 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 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 drawn 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 drawn 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() # secondary -> 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 drawn 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 drawn 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 drawn 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.parametrize( "input_logy, expected_scale", [(True, "log"), ("sym", "symlog")] ) def test_secondary_logy(self, input_logy, expected_scale): # GH 25545 s1 = Series(np.random.randn(30)) s2 = Series(np.random.randn(30)) # GH 24980 ax1 = s1.plot(logy=input_logy) ax2 = s2.plot(secondary_y=True, logy=input_logy) assert ax1.get_yscale() == expected_scale assert ax2.get_yscale() == expected_scale def test_plot_fails_with_dupe_color_and_style(self): x = Series(np.random.randn(2)) _, ax = self.plt.subplots() msg = ( "Cannot pass 'style' string with a color symbol and 'color' keyword " "argument. Please use one or the other or pass 'style' without a color " "symbol" ) with pytest.raises(ValueError, match=msg): x.plot(style="k--", color="k", ax=ax) @td.skip_if_no_scipy def test_kde_kwargs(self): 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=0.5, ind=sample_points) _check_plot_works(self.ts.plot.density, bw_method=0.5, ind=sample_points) _, ax = self.plt.subplots() ax = self.ts.plot.kde(logy=True, bw_method=0.5, ind=sample_points, ax=ax) self._check_ax_scales(ax, yaxis="log") self._check_text_labels(ax.yaxis.get_label(), "Density") @td.skip_if_no_scipy def test_kde_missing_vals(self): 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_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_kind_both_ways(self): s = Series(range(3)) kinds = ( plotting.PlotAccessor._common_kinds + plotting.PlotAccessor._series_kinds ) for kind in kinds: _, ax = self.plt.subplots() s.plot(kind=kind, ax=ax) self.plt.close() _, ax = self.plt.subplots() getattr(s.plot, kind)() self.plt.close() def test_invalid_plot_data(self): s = Series(list("abcd")) _, ax = self.plt.subplots() for kind in plotting.PlotAccessor._common_kinds: msg = "no numeric data to plot" with pytest.raises(TypeError, match=msg): s.plot(kind=kind, ax=ax) def test_valid_object_plot(self): s = Series(range(10), dtype=object) for kind in plotting.PlotAccessor._common_kinds: _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.PlotAccessor._common_kinds: msg = "no numeric data to plot" with pytest.raises(TypeError, match=msg): s.plot(kind=kind, ax=ax) def test_invalid_kind(self): s = Series([1, 2]) with pytest.raises(ValueError, match="invalid_kind is not a valid plot kind"): s.plot(kind="invalid_kind") 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 = np.random.randn(index.size) s = Series(values, index=index) _check_plot_works(s.plot) def test_errorbar_asymmetrical(self): # GH9536 s = Series(np.arange(10), name="x") err = np.random.rand(2, 10) ax = s.plot(yerr=err, xerr=err) result = np.vstack([i.vertices[:, 1] for i in ax.collections[1].get_paths()]) expected = (err.T * np.array([-1, 1])) + s.to_numpy().reshape(-1, 1) tm.assert_numpy_array_equal(result, expected) msg = ( "Asymmetrical error bars should be provided " f"with the shape \\(2, {len(s)}\\)" ) with pytest.raises(ValueError, match=msg): s.plot(yerr=np.random.rand(2, 11)) tm.close() def test_errorbar_plot(self): s = Series(np.arange(10), name="x") s_err = np.random.randn(10) d_err = DataFrame(np.random.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(np.random.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 tm.external_error_raised(ValueError): s.plot(yerr=np.arange(11)) s_err = ["zzz"] * 10 with tm.external_error_raised(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) 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.PlotAccessor._series_kinds + plotting.PlotAccessor._common_kinds, ) def test_standard_colors(self): from pandas.plotting._matplotlib.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 def test_standard_colors_all(self): import matplotlib.colors as colors from pandas.plotting._matplotlib.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=[f"P{i:02d}" for i in range(10)]) _, ax = self.plt.subplots() ax = s.plot(xticks=[0, 3, 5, 9], ax=ax) exp = [f"P{i:02d}" for i in [0, 3, 5, 9]] self._check_text_labels(ax.get_xticklabels(), exp) def test_xtick_barPlot(self): # GH28172 s = Series(range(10), index=[f"P{i:02d}" for i in range(10)]) ax = s.plot.bar(xticks=range(0, 11, 2)) exp = np.array(list(range(0, 11, 2))) tm.assert_numpy_array_equal(exp, ax.get_xticks()) 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(reason="GH#24426") def test_plot_accessor_updates_on_inplace(self): ser = Series([1, 2, 3, 4]) _, ax = self.plt.subplots() ax = ser.plot(ax=ax) before = ax.xaxis.get_ticklocs() ser.drop([0, 1], inplace=True) _, ax = self.plt.subplots() after = ax.xaxis.get_ticklocs() tm.assert_numpy_array_equal(before, after) @pytest.mark.parametrize("kind", ["line", "area"]) def test_plot_xlim_for_series(self, kind): # test if xlim is also correctly plotted in Series for line and area # GH 27686 s = Series([2, 3]) _, ax = self.plt.subplots() s.plot(kind=kind, ax=ax) xlims = ax.get_xlim() assert xlims[0] < 0 assert xlims[1] > 1 def test_plot_no_rows(self): # GH 27758 df = Series(dtype=int) assert df.empty ax = df.plot() assert len(ax.get_lines()) == 1 line = ax.get_lines()[0] assert len(line.get_xdata()) == 0 assert len(line.get_ydata()) == 0 def test_plot_no_numeric_data(self): df = Series(["a", "b", "c"]) with pytest.raises(TypeError, match="no numeric data to plot"): df.plot() @pytest.mark.parametrize( "data, index", [ ([1, 2, 3, 4], [3, 2, 1, 0]), ([10, 50, 20, 30], [1910, 1920, 1980, 1950]), ], ) def test_plot_order(self, data, index): # GH38865 Verify plot order of a Series ser = Series(data=data, index=index) ax = ser.plot(kind="bar") expected = ser.tolist() result = [ patch.get_bbox().ymax for patch in sorted(ax.patches, key=lambda patch: patch.get_bbox().xmax) ] assert expected == result def test_style_single_ok(self): s = Series([1, 2]) ax = s.plot(style="s", color="C3") assert ax.lines[0].get_color() == "C3" @pytest.mark.parametrize( "index_name, old_label, new_label", [(None, "", "new"), ("old", "old", "new"), (None, "", "")], ) @pytest.mark.parametrize("kind", ["line", "area", "bar"]) def test_xlabel_ylabel_series(self, kind, index_name, old_label, new_label): # GH 9093 ser = Series([1, 2, 3, 4]) ser.index.name = index_name # default is the ylabel is not shown and xlabel is index name ax = ser.plot(kind=kind) assert ax.get_ylabel() == "" assert ax.get_xlabel() == old_label # old xlabel will be overridden and assigned ylabel will be used as ylabel ax = ser.plot(kind=kind, ylabel=new_label, xlabel=new_label) assert ax.get_ylabel() == new_label assert ax.get_xlabel() == new_label @pytest.mark.parametrize( "index", [ pd.timedelta_range(start=0, periods=2, freq="D"), [pd.Timedelta(days=1), pd.Timedelta(days=2)], ], ) def test_timedelta_index(self, index): # GH37454 xlims = (3, 1) ax = Series([1, 2], index=index).plot(xlim=(xlims)) assert ax.get_xlim() == (3, 1)