Sindbad~EG File Manager
""" Test cases for Series.plot """
from datetime import datetime
from itertools import chain
import numpy as np
import pytest
from pandas.compat import is_platform_linux
from pandas.compat.numpy import np_version_gte1p24
import pandas.util._test_decorators as td
import pandas as pd
from pandas import (
DataFrame,
Series,
date_range,
period_range,
plotting,
)
import pandas._testing as tm
from pandas.tests.plotting.common import (
_check_ax_scales,
_check_axes_shape,
_check_colors,
_check_grid_settings,
_check_has_errorbars,
_check_legend_labels,
_check_plot_works,
_check_text_labels,
_check_ticks_props,
_unpack_cycler,
get_y_axis,
)
mpl = pytest.importorskip("matplotlib")
plt = pytest.importorskip("matplotlib.pyplot")
@pytest.fixture
def ts():
return Series(
np.arange(10, dtype=np.float64),
index=date_range("2020-01-01", periods=10),
name="ts",
)
@pytest.fixture
def series():
return Series(
range(20), dtype=np.float64, name="series", index=[f"i_{i}" for i in range(20)]
)
class TestSeriesPlots:
@pytest.mark.slow
@pytest.mark.parametrize("kwargs", [{"label": "foo"}, {"use_index": False}])
def test_plot(self, ts, kwargs):
_check_plot_works(ts.plot, **kwargs)
@pytest.mark.slow
def test_plot_tick_props(self, ts):
axes = _check_plot_works(ts.plot, rot=0)
_check_ticks_props(axes, xrot=0)
@pytest.mark.slow
@pytest.mark.parametrize(
"scale, exp_scale",
[
[{"logy": True}, {"yaxis": "log"}],
[{"logx": True}, {"xaxis": "log"}],
[{"loglog": True}, {"xaxis": "log", "yaxis": "log"}],
],
)
def test_plot_scales(self, ts, scale, exp_scale):
ax = _check_plot_works(ts.plot, style=".", **scale)
_check_ax_scales(ax, **exp_scale)
@pytest.mark.slow
def test_plot_ts_bar(self, ts):
_check_plot_works(ts[:10].plot.bar)
@pytest.mark.slow
def test_plot_ts_area_stacked(self, ts):
_check_plot_works(ts.plot.area, stacked=False)
def test_plot_iseries(self):
ser = Series(range(5), period_range("2020-01-01", periods=5))
_check_plot_works(ser.plot)
@pytest.mark.parametrize(
"kind",
[
"line",
"bar",
"barh",
pytest.param("kde", marks=td.skip_if_no("scipy")),
"hist",
"box",
],
)
def test_plot_series_kinds(self, series, kind):
_check_plot_works(series[:5].plot, kind=kind)
def test_plot_series_barh(self, series):
_check_plot_works(series[:10].plot.barh)
def test_plot_series_bar_ax(self):
ax = _check_plot_works(
Series(np.random.default_rng(2).standard_normal(10)).plot.bar, color="black"
)
_check_colors([ax.patches[0]], facecolors=["black"])
@pytest.mark.parametrize("kwargs", [{}, {"layout": (-1, 1)}, {"layout": (1, -1)}])
def test_plot_6951(self, ts, kwargs):
# GH 6951
ax = _check_plot_works(ts.plot, subplots=True, **kwargs)
_check_axes_shape(ax, axes_num=1, layout=(1, 1))
def test_plot_figsize_and_title(self, series):
# figsize and title
_, ax = mpl.pyplot.subplots()
ax = series.plot(title="Test", figsize=(16, 8), ax=ax)
_check_text_labels(ax.title, "Test")
_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 = mpl.pyplot.rcParams[key]
_, ax = mpl.pyplot.subplots()
Series([1, 2, 3]).plot(ax=ax)
assert colors == mpl.pyplot.rcParams[key]
@pytest.mark.parametrize("kwargs", [{}, {"secondary_y": True}])
def test_ts_line_lim(self, ts, kwargs):
_, ax = mpl.pyplot.subplots()
ax = ts.plot(ax=ax, **kwargs)
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, ts):
_, ax = mpl.pyplot.subplots()
ax = 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]
_check_ticks_props(ax, xrot=0)
def test_ts_area_lim_xcompat(self, ts):
# GH 7471
_, ax = mpl.pyplot.subplots()
ax = 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]
_check_ticks_props(ax, xrot=30)
def test_ts_tz_area_lim_xcompat(self, ts):
tz_ts = ts.copy()
tz_ts.index = tz_ts.tz_localize("GMT").tz_convert("CET")
_, ax = mpl.pyplot.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]
_check_ticks_props(ax, xrot=0)
def test_ts_tz_area_lim_xcompat_secondary_y(self, ts):
tz_ts = ts.copy()
tz_ts.index = tz_ts.tz_localize("GMT").tz_convert("CET")
_, ax = mpl.pyplot.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]
_check_ticks_props(ax, xrot=0)
def test_area_sharey_dont_overwrite(self, ts):
# GH37942
fig, (ax1, ax2) = mpl.pyplot.subplots(1, 2, sharey=True)
abs(ts).plot(ax=ax1, kind="area")
abs(ts).plot(ax=ax2, kind="area")
assert get_y_axis(ax1).joined(ax1, ax2)
assert get_y_axis(ax2).joined(ax1, ax2)
plt.close(fig)
def test_label(self):
s = Series([1, 2])
_, ax = mpl.pyplot.subplots()
ax = s.plot(label="LABEL", legend=True, ax=ax)
_check_legend_labels(ax, labels=["LABEL"])
mpl.pyplot.close("all")
def test_label_none(self):
s = Series([1, 2])
_, ax = mpl.pyplot.subplots()
ax = s.plot(legend=True, ax=ax)
_check_legend_labels(ax, labels=[""])
mpl.pyplot.close("all")
def test_label_ser_name(self):
s = Series([1, 2], name="NAME")
_, ax = mpl.pyplot.subplots()
ax = s.plot(legend=True, ax=ax)
_check_legend_labels(ax, labels=["NAME"])
mpl.pyplot.close("all")
def test_label_ser_name_override(self):
s = Series([1, 2], name="NAME")
# override the default
_, ax = mpl.pyplot.subplots()
ax = s.plot(legend=True, label="LABEL", ax=ax)
_check_legend_labels(ax, labels=["LABEL"])
mpl.pyplot.close("all")
def test_label_ser_name_override_dont_draw(self):
s = Series([1, 2], name="NAME")
# Add lebel info, but don't draw
_, ax = mpl.pyplot.subplots()
ax = s.plot(legend=False, label="LABEL", ax=ax)
assert ax.get_legend() is None # Hasn't been drawn
ax.legend() # draw it
_check_legend_labels(ax, labels=["LABEL"])
mpl.pyplot.close("all")
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)
@pytest.mark.parametrize("index", [None, date_range("2020-01-01", periods=4)])
def test_line_area_nan_series(self, index):
values = [1, 2, np.nan, 3]
d = Series(values, index=index)
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 = mpl.pyplot.subplots()
ax = s.plot(use_index=False, ax=ax)
label = ax.get_xlabel()
assert label == ""
def test_line_use_index_false_diff_var(self):
s = Series([1, 2, 3], index=["a", "b", "c"])
s.index.name = "The Index"
_, ax = mpl.pyplot.subplots()
ax2 = s.plot.bar(use_index=False, ax=ax)
label2 = ax2.get_xlabel()
assert label2 == ""
@pytest.mark.xfail(
np_version_gte1p24 and is_platform_linux(),
reason="Weird rounding problems",
strict=False,
)
@pytest.mark.parametrize("axis, meth", [("yaxis", "bar"), ("xaxis", "barh")])
def test_bar_log(self, axis, meth):
expected = np.array([1e-1, 1e0, 1e1, 1e2, 1e3, 1e4])
_, ax = mpl.pyplot.subplots()
ax = getattr(Series([200, 500]).plot, meth)(log=True, ax=ax)
tm.assert_numpy_array_equal(getattr(ax, axis).get_ticklocs(), expected)
@pytest.mark.xfail(
np_version_gte1p24 and is_platform_linux(),
reason="Weird rounding problems",
strict=False,
)
@pytest.mark.parametrize(
"axis, kind, res_meth",
[["yaxis", "bar", "get_ylim"], ["xaxis", "barh", "get_xlim"]],
)
def test_bar_log_kind_bar(self, axis, kind, res_meth):
# GH 9905
expected = np.array([1e-5, 1e-4, 1e-3, 1e-2, 1e-1, 1e0, 1e1])
_, ax = mpl.pyplot.subplots()
ax = Series([0.1, 0.01, 0.001]).plot(log=True, kind=kind, ax=ax)
ymin = 0.0007943282347242822
ymax = 0.12589254117941673
res = getattr(ax, res_meth)()
tm.assert_almost_equal(res[0], ymin)
tm.assert_almost_equal(res[1], ymax)
tm.assert_numpy_array_equal(getattr(ax, axis).get_ticklocs(), expected)
def test_bar_ignore_index(self):
df = Series([1, 2, 3, 4], index=["a", "b", "c", "d"])
_, ax = mpl.pyplot.subplots()
ax = df.plot.bar(use_index=False, ax=ax)
_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_default(self):
df = DataFrame(np.random.default_rng(2).standard_normal((5, 5)))
# Default rot 0
_, ax = mpl.pyplot.subplots()
axes = df.plot(ax=ax)
_check_ticks_props(axes, xrot=0)
def test_rotation_30(self):
df = DataFrame(np.random.default_rng(2).standard_normal((5, 5)))
_, ax = mpl.pyplot.subplots()
axes = df.plot(rot=30, ax=ax)
_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.default_rng(2).standard_normal(len(rng)), rng)
_, ax = mpl.pyplot.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]
_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 = mpl.pyplot.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.default_rng(2).integers(1, 5),
index=["a", "b", "c", "d", "e"],
name="YLABEL",
)
ax = _check_plot_works(series.plot.pie)
_check_text_labels(ax.texts, series.index)
assert ax.get_ylabel() == "YLABEL"
def test_pie_series_no_label(self):
series = Series(
np.random.default_rng(2).integers(1, 5),
index=["a", "b", "c", "d", "e"],
name="YLABEL",
)
ax = _check_plot_works(series.plot.pie, labels=None)
_check_text_labels(ax.texts, [""] * 5)
def test_pie_series_less_colors_than_elements(self):
series = Series(
np.random.default_rng(2).integers(1, 5),
index=["a", "b", "c", "d", "e"],
name="YLABEL",
)
color_args = ["r", "g", "b"]
ax = _check_plot_works(series.plot.pie, colors=color_args)
color_expected = ["r", "g", "b", "r", "g"]
_check_colors(ax.patches, facecolors=color_expected)
def test_pie_series_labels_and_colors(self):
series = Series(
np.random.default_rng(2).integers(1, 5),
index=["a", "b", "c", "d", "e"],
name="YLABEL",
)
# 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)
_check_text_labels(ax.texts, labels)
_check_colors(ax.patches, facecolors=color_args)
def test_pie_series_autopct_and_fontsize(self):
series = Series(
np.random.default_rng(2).integers(1, 5),
index=["a", "b", "c", "d", "e"],
name="YLABEL",
)
color_args = ["r", "g", "b", "c", "m"]
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)))
_check_text_labels(ax.texts, expected_texts)
for t in ax.texts:
assert t.get_fontsize() == 7
def test_pie_series_negative_raises(self):
# 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()
def test_pie_series_nan(self):
# includes nan
series = Series([1, 2, np.nan, 4], index=["a", "b", "c", "d"], name="YLABEL")
ax = _check_plot_works(series.plot.pie)
_check_text_labels(ax.texts, ["a", "b", "", "d"])
def test_pie_nan(self):
s = Series([1, np.nan, 1, 1])
_, ax = mpl.pyplot.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.default_rng(2).standard_normal((30, 3)), columns=list("abc")
)
s = Series(np.random.default_rng(2).standard_normal(30), name="x")
# primary -> secondary (without passing ax)
_, ax = mpl.pyplot.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
_check_legend_labels(ax, labels=["a", "b", "c", "x (right)"])
assert ax.get_yaxis().get_visible()
assert ax.right_ax.get_yaxis().get_visible()
def test_df_series_secondary_legend_with_axes(self):
# GH 9779
df = DataFrame(
np.random.default_rng(2).standard_normal((30, 3)), columns=list("abc")
)
s = Series(np.random.default_rng(2).standard_normal(30), name="x")
# primary -> secondary (with passing ax)
_, ax = mpl.pyplot.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
_check_legend_labels(ax, labels=["a", "b", "c", "x (right)"])
assert ax.get_yaxis().get_visible()
assert ax.right_ax.get_yaxis().get_visible()
def test_df_series_secondary_legend_both(self):
# GH 9779
df = DataFrame(
np.random.default_rng(2).standard_normal((30, 3)), columns=list("abc")
)
s = Series(np.random.default_rng(2).standard_normal(30), name="x")
# secondary -> secondary (without passing ax)
_, ax = mpl.pyplot.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)"]
_check_legend_labels(ax.left_ax, labels=expected)
assert not ax.left_ax.get_yaxis().get_visible()
assert ax.get_yaxis().get_visible()
def test_df_series_secondary_legend_both_with_axis(self):
# GH 9779
df = DataFrame(
np.random.default_rng(2).standard_normal((30, 3)), columns=list("abc")
)
s = Series(np.random.default_rng(2).standard_normal(30), name="x")
# secondary -> secondary (with passing ax)
_, ax = mpl.pyplot.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)"]
_check_legend_labels(ax.left_ax, expected)
assert not ax.left_ax.get_yaxis().get_visible()
assert ax.get_yaxis().get_visible()
def test_df_series_secondary_legend_both_with_axis_2(self):
# GH 9779
df = DataFrame(
np.random.default_rng(2).standard_normal((30, 3)), columns=list("abc")
)
s = Series(np.random.default_rng(2).standard_normal(30), name="x")
# secondary -> secondary (with passing ax)
_, ax = mpl.pyplot.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)"]
_check_legend_labels(ax.left_ax, expected)
assert not ax.left_ax.get_yaxis().get_visible()
assert ax.get_yaxis().get_visible()
@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.default_rng(2).standard_normal(100))
s2 = Series(np.random.default_rng(2).standard_normal(100))
# 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.default_rng(2).standard_normal(2))
_, ax = mpl.pyplot.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)
@pytest.mark.parametrize(
"bw_method, ind",
[
["scott", 20],
[None, 20],
[None, np.int_(20)],
[0.5, np.linspace(-100, 100, 20)],
],
)
def test_kde_kwargs(self, ts, bw_method, ind):
pytest.importorskip("scipy")
_check_plot_works(ts.plot.kde, bw_method=bw_method, ind=ind)
def test_density_kwargs(self, ts):
pytest.importorskip("scipy")
sample_points = np.linspace(-100, 100, 20)
_check_plot_works(ts.plot.density, bw_method=0.5, ind=sample_points)
def test_kde_kwargs_check_axes(self, ts):
pytest.importorskip("scipy")
_, ax = mpl.pyplot.subplots()
sample_points = np.linspace(-100, 100, 20)
ax = ts.plot.kde(logy=True, bw_method=0.5, ind=sample_points, ax=ax)
_check_ax_scales(ax, yaxis="log")
_check_text_labels(ax.yaxis.get_label(), "Density")
def test_kde_missing_vals(self):
pytest.importorskip("scipy")
s = Series(np.random.default_rng(2).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.xfail(reason="Api changed in 3.6.0")
def test_boxplot_series(self, ts):
_, ax = mpl.pyplot.subplots()
ax = ts.plot.box(logy=True, ax=ax)
_check_ax_scales(ax, yaxis="log")
xlabels = ax.get_xticklabels()
_check_text_labels(xlabels, [ts.name])
ylabels = ax.get_yticklabels()
_check_text_labels(ylabels, [""] * len(ylabels))
@pytest.mark.parametrize(
"kind",
plotting.PlotAccessor._common_kinds + plotting.PlotAccessor._series_kinds,
)
def test_kind_kwarg(self, kind):
pytest.importorskip("scipy")
s = Series(range(3))
_, ax = mpl.pyplot.subplots()
s.plot(kind=kind, ax=ax)
mpl.pyplot.close()
@pytest.mark.parametrize(
"kind",
plotting.PlotAccessor._common_kinds + plotting.PlotAccessor._series_kinds,
)
def test_kind_attr(self, kind):
pytest.importorskip("scipy")
s = Series(range(3))
_, ax = mpl.pyplot.subplots()
getattr(s.plot, kind)()
mpl.pyplot.close()
@pytest.mark.parametrize("kind", plotting.PlotAccessor._common_kinds)
def test_invalid_plot_data(self, kind):
s = Series(list("abcd"))
_, ax = mpl.pyplot.subplots()
msg = "no numeric data to plot"
with pytest.raises(TypeError, match=msg):
s.plot(kind=kind, ax=ax)
@pytest.mark.parametrize("kind", plotting.PlotAccessor._common_kinds)
def test_valid_object_plot(self, kind):
pytest.importorskip("scipy")
s = Series(range(10), dtype=object)
_check_plot_works(s.plot, kind=kind)
@pytest.mark.parametrize("kind", plotting.PlotAccessor._common_kinds)
def test_partially_invalid_plot_data(self, kind):
s = Series(["a", "b", 1.0, 2])
_, ax = mpl.pyplot.subplots()
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.default_rng(2).standard_normal(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.default_rng(2).random((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.default_rng(2).random((2, 11)))
@pytest.mark.slow
@pytest.mark.parametrize("kind", ["line", "bar"])
@pytest.mark.parametrize(
"yerr",
[
Series(np.abs(np.random.default_rng(2).standard_normal(10))),
np.abs(np.random.default_rng(2).standard_normal(10)),
list(np.abs(np.random.default_rng(2).standard_normal(10))),
DataFrame(
np.abs(np.random.default_rng(2).standard_normal((10, 2))),
columns=["x", "y"],
),
],
)
def test_errorbar_plot(self, kind, yerr):
s = Series(np.arange(10), name="x")
ax = _check_plot_works(s.plot, yerr=yerr, kind=kind)
_check_has_errorbars(ax, xerr=0, yerr=1)
@pytest.mark.slow
def test_errorbar_plot_yerr_0(self):
s = Series(np.arange(10), name="x")
s_err = np.abs(np.random.default_rng(2).standard_normal(10))
ax = _check_plot_works(s.plot, xerr=s_err)
_check_has_errorbars(ax, xerr=1, yerr=0)
@pytest.mark.slow
@pytest.mark.parametrize(
"yerr",
[
Series(np.abs(np.random.default_rng(2).standard_normal(12))),
DataFrame(
np.abs(np.random.default_rng(2).standard_normal((12, 2))),
columns=["x", "y"],
),
],
)
def test_errorbar_plot_ts(self, yerr):
# test time series plotting
ix = date_range("1/1/2000", "1/1/2001", freq="ME")
ts = Series(np.arange(12), index=ix, name="x")
yerr.index = ix
ax = _check_plot_works(ts.plot, yerr=yerr)
_check_has_errorbars(ax, xerr=0, yerr=1)
@pytest.mark.slow
def test_errorbar_plot_invalid_yerr_shape(self):
s = Series(np.arange(10), name="x")
# check incorrect lengths and types
with tm.external_error_raised(ValueError):
s.plot(yerr=np.arange(11))
@pytest.mark.slow
def test_errorbar_plot_invalid_yerr(self):
s = Series(np.arange(10), name="x")
s_err = ["zzz"] * 10
with tm.external_error_raised(TypeError):
s.plot(yerr=s_err)
@pytest.mark.slow
def test_table_true(self, series):
_check_plot_works(series.plot, table=True)
@pytest.mark.slow
def test_table_self(self, series):
_check_plot_works(series.plot, table=series)
@pytest.mark.slow
def test_series_grid_settings(self):
# Make sure plot defaults to rcParams['axes.grid'] setting, GH 9792
pytest.importorskip("scipy")
_check_grid_settings(
Series([1, 2, 3]),
plotting.PlotAccessor._series_kinds + plotting.PlotAccessor._common_kinds,
)
@pytest.mark.parametrize("c", ["r", "red", "green", "#FF0000"])
def test_standard_colors(self, c):
from pandas.plotting._matplotlib.style import get_standard_colors
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):
from matplotlib import 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 = mpl.pyplot.subplots()
ax = Series(np.arange(12) + 1).plot(color="green", ax=ax)
_check_colors(ax.get_lines(), linecolors=["green"])
def test_time_series_plot_color_kwargs(self):
# #1890
_, ax = mpl.pyplot.subplots()
ax = Series(np.arange(12) + 1, index=date_range("1/1/2000", periods=12)).plot(
color="green", ax=ax
)
_check_colors(ax.get_lines(), linecolors=["green"])
def test_time_series_plot_color_with_empty_kwargs(self):
import matplotlib as mpl
def_colors = _unpack_cycler(mpl.rcParams)
index = date_range("1/1/2000", periods=12)
s = Series(np.arange(1, 13), index=index)
ncolors = 3
_, ax = mpl.pyplot.subplots()
for i in range(ncolors):
ax = s.plot(ax=ax)
_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 = mpl.pyplot.subplots()
ax = s.plot(xticks=[0, 3, 5, 9], ax=ax)
exp = [f"P{i:02d}" for i in [0, 3, 5, 9]]
_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, see also "
"github.com/pandas-dev/pandas/commit/"
"ef1bd69fa42bbed5d09dd17f08c44fc8bfc2b685#r61470674"
)
def test_plot_accessor_updates_on_inplace(self):
ser = Series([1, 2, 3, 4])
_, ax = mpl.pyplot.subplots()
ax = ser.plot(ax=ax)
before = ax.xaxis.get_ticklocs()
ser.drop([0, 1], inplace=True)
_, ax = mpl.pyplot.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 = mpl.pyplot.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", "barh", "hist"])
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 (reverse for barh)
ax = ser.plot(kind=kind)
if kind == "barh":
assert ax.get_xlabel() == ""
assert ax.get_ylabel() == old_label
elif kind == "hist":
assert ax.get_xlabel() == ""
assert ax.get_ylabel() == "Frequency"
else:
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)
def test_series_none_color(self):
# GH51953
series = Series([1, 2, 3])
ax = series.plot(color=None)
expected = _unpack_cycler(mpl.pyplot.rcParams)[:1]
_check_colors(ax.get_lines(), linecolors=expected)
@pytest.mark.slow
def test_plot_no_warning(self, ts):
# GH 55138
# TODO(3.0): this can be removed once Period[B] deprecation is enforced
with tm.assert_produces_warning(False):
_ = ts.plot()
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