801 lines
29 KiB
Python
801 lines
29 KiB
Python
|
""" Test cases for .hist method """
|
||
|
|
import re
|
||
|
|
|
||
|
|
import numpy as np
|
||
|
|
import pytest
|
||
|
|
|
||
|
|
import pandas.util._test_decorators as td
|
||
|
|
|
||
|
|
from pandas import (
|
||
|
|
DataFrame,
|
||
|
|
Index,
|
||
|
|
Series,
|
||
|
|
to_datetime,
|
||
|
|
)
|
||
|
|
import pandas._testing as tm
|
||
|
|
from pandas.tests.plotting.common import (
|
||
|
|
TestPlotBase,
|
||
|
|
_check_plot_works,
|
||
|
|
)
|
||
|
|
|
||
|
|
|
||
|
|
@pytest.fixture
|
||
|
|
def ts():
|
||
|
|
return tm.makeTimeSeries(name="ts")
|
||
|
|
|
||
|
|
|
||
|
|
@td.skip_if_no_mpl
|
||
|
|
class TestSeriesPlots(TestPlotBase):
|
||
|
|
def test_hist_legacy(self, ts):
|
||
|
|
_check_plot_works(ts.hist)
|
||
|
|
_check_plot_works(ts.hist, grid=False)
|
||
|
|
_check_plot_works(ts.hist, figsize=(8, 10))
|
||
|
|
# _check_plot_works adds an ax so catch warning. see GH #13188
|
||
|
|
with tm.assert_produces_warning(UserWarning, check_stacklevel=False):
|
||
|
|
_check_plot_works(ts.hist, by=ts.index.month)
|
||
|
|
with tm.assert_produces_warning(UserWarning, check_stacklevel=False):
|
||
|
|
_check_plot_works(ts.hist, by=ts.index.month, bins=5)
|
||
|
|
|
||
|
|
fig, ax = self.plt.subplots(1, 1)
|
||
|
|
_check_plot_works(ts.hist, ax=ax, default_axes=True)
|
||
|
|
_check_plot_works(ts.hist, ax=ax, figure=fig, default_axes=True)
|
||
|
|
_check_plot_works(ts.hist, figure=fig, default_axes=True)
|
||
|
|
tm.close()
|
||
|
|
|
||
|
|
fig, (ax1, ax2) = self.plt.subplots(1, 2)
|
||
|
|
_check_plot_works(ts.hist, figure=fig, ax=ax1, default_axes=True)
|
||
|
|
_check_plot_works(ts.hist, figure=fig, ax=ax2, default_axes=True)
|
||
|
|
|
||
|
|
msg = (
|
||
|
|
"Cannot pass 'figure' when using the 'by' argument, since a new 'Figure' "
|
||
|
|
"instance will be created"
|
||
|
|
)
|
||
|
|
with pytest.raises(ValueError, match=msg):
|
||
|
|
ts.hist(by=ts.index, figure=fig)
|
||
|
|
|
||
|
|
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
|
||
|
|
|
||
|
|
def test_hist_layout(self, hist_df):
|
||
|
|
df = hist_df
|
||
|
|
msg = "The 'layout' keyword is not supported when 'by' is None"
|
||
|
|
with pytest.raises(ValueError, match=msg):
|
||
|
|
df.height.hist(layout=(1, 1))
|
||
|
|
|
||
|
|
with pytest.raises(ValueError, match=msg):
|
||
|
|
df.height.hist(layout=[1, 1])
|
||
|
|
|
||
|
|
@pytest.mark.slow
|
||
|
|
def test_hist_layout_with_by(self, hist_df):
|
||
|
|
df = hist_df
|
||
|
|
|
||
|
|
# _check_plot_works adds an `ax` kwarg to the method call
|
||
|
|
# so we get a warning about an axis being cleared, even
|
||
|
|
# though we don't explicing pass one, see GH #13188
|
||
|
|
with tm.assert_produces_warning(UserWarning, check_stacklevel=False):
|
||
|
|
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, check_stacklevel=False):
|
||
|
|
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, check_stacklevel=False):
|
||
|
|
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, check_stacklevel=False):
|
||
|
|
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, check_stacklevel=False):
|
||
|
|
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, check_stacklevel=False):
|
||
|
|
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, check_stacklevel=False):
|
||
|
|
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))
|
||
|
|
|
||
|
|
def test_hist_no_overlap(self):
|
||
|
|
from matplotlib.pyplot import (
|
||
|
|
gcf,
|
||
|
|
subplot,
|
||
|
|
)
|
||
|
|
|
||
|
|
x = Series(np.random.randn(2))
|
||
|
|
y = Series(np.random.randn(2))
|
||
|
|
subplot(121)
|
||
|
|
x.hist()
|
||
|
|
subplot(122)
|
||
|
|
y.hist()
|
||
|
|
fig = gcf()
|
||
|
|
axes = fig.axes
|
||
|
|
assert len(axes) == 2
|
||
|
|
|
||
|
|
def test_hist_by_no_extra_plots(self, hist_df):
|
||
|
|
df = hist_df
|
||
|
|
axes = df.height.hist(by=df.gender) # noqa
|
||
|
|
assert len(self.plt.get_fignums()) == 1
|
||
|
|
|
||
|
|
def test_plot_fails_when_ax_differs_from_figure(self, ts):
|
||
|
|
from pylab import figure
|
||
|
|
|
||
|
|
fig1 = figure()
|
||
|
|
fig2 = figure()
|
||
|
|
ax1 = fig1.add_subplot(111)
|
||
|
|
msg = "passed axis not bound to passed figure"
|
||
|
|
with pytest.raises(AssertionError, match=msg):
|
||
|
|
ts.hist(ax=ax1, figure=fig2)
|
||
|
|
|
||
|
|
@pytest.mark.parametrize(
|
||
|
|
"histtype, expected",
|
||
|
|
[
|
||
|
|
("bar", True),
|
||
|
|
("barstacked", True),
|
||
|
|
("step", False),
|
||
|
|
("stepfilled", True),
|
||
|
|
],
|
||
|
|
)
|
||
|
|
def test_histtype_argument(self, histtype, expected):
|
||
|
|
# GH23992 Verify functioning of histtype argument
|
||
|
|
ser = Series(np.random.randint(1, 10))
|
||
|
|
ax = ser.hist(histtype=histtype)
|
||
|
|
self._check_patches_all_filled(ax, filled=expected)
|
||
|
|
|
||
|
|
@pytest.mark.parametrize(
|
||
|
|
"by, expected_axes_num, expected_layout", [(None, 1, (1, 1)), ("b", 2, (1, 2))]
|
||
|
|
)
|
||
|
|
def test_hist_with_legend(self, by, expected_axes_num, expected_layout):
|
||
|
|
# GH 6279 - Series histogram can have a legend
|
||
|
|
index = 15 * ["1"] + 15 * ["2"]
|
||
|
|
s = Series(np.random.randn(30), index=index, name="a")
|
||
|
|
s.index.name = "b"
|
||
|
|
|
||
|
|
# Use default_axes=True when plotting method generate subplots itself
|
||
|
|
axes = _check_plot_works(s.hist, default_axes=True, legend=True, by=by)
|
||
|
|
self._check_axes_shape(axes, axes_num=expected_axes_num, layout=expected_layout)
|
||
|
|
self._check_legend_labels(axes, "a")
|
||
|
|
|
||
|
|
@pytest.mark.parametrize("by", [None, "b"])
|
||
|
|
def test_hist_with_legend_raises(self, by):
|
||
|
|
# GH 6279 - Series histogram with legend and label raises
|
||
|
|
index = 15 * ["1"] + 15 * ["2"]
|
||
|
|
s = Series(np.random.randn(30), index=index, name="a")
|
||
|
|
s.index.name = "b"
|
||
|
|
|
||
|
|
with pytest.raises(ValueError, match="Cannot use both legend and label"):
|
||
|
|
s.hist(legend=True, by=by, label="c")
|
||
|
|
|
||
|
|
def test_hist_kwargs(self, ts):
|
||
|
|
_, ax = self.plt.subplots()
|
||
|
|
ax = 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 = ts.plot.hist(orientation="horizontal", ax=ax)
|
||
|
|
self._check_text_labels(ax.xaxis.get_label(), "Frequency")
|
||
|
|
tm.close()
|
||
|
|
|
||
|
|
_, ax = self.plt.subplots()
|
||
|
|
ax = ts.plot.hist(align="left", stacked=True, ax=ax)
|
||
|
|
tm.close()
|
||
|
|
|
||
|
|
@pytest.mark.xfail(reason="Api changed in 3.6.0")
|
||
|
|
@td.skip_if_no_scipy
|
||
|
|
def test_hist_kde(self, ts):
|
||
|
|
_, ax = self.plt.subplots()
|
||
|
|
ax = 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))
|
||
|
|
|
||
|
|
_check_plot_works(ts.plot.kde)
|
||
|
|
_check_plot_works(ts.plot.density)
|
||
|
|
_, ax = self.plt.subplots()
|
||
|
|
ax = 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))
|
||
|
|
|
||
|
|
@td.skip_if_no_scipy
|
||
|
|
def test_hist_kde_color(self, ts):
|
||
|
|
_, ax = self.plt.subplots()
|
||
|
|
ax = 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)
|
||
|
|
|
||
|
|
_, ax = self.plt.subplots()
|
||
|
|
ax = 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"])
|
||
|
|
|
||
|
|
|
||
|
|
@td.skip_if_no_mpl
|
||
|
|
class TestDataFramePlots(TestPlotBase):
|
||
|
|
@pytest.mark.slow
|
||
|
|
def test_hist_df_legacy(self, hist_df):
|
||
|
|
from matplotlib.patches import Rectangle
|
||
|
|
|
||
|
|
with tm.assert_produces_warning(UserWarning, check_stacklevel=False):
|
||
|
|
_check_plot_works(hist_df.hist)
|
||
|
|
|
||
|
|
# make sure layout is handled
|
||
|
|
df = DataFrame(np.random.randn(100, 2))
|
||
|
|
df[2] = to_datetime(
|
||
|
|
np.random.randint(
|
||
|
|
812419200000000000,
|
||
|
|
819331200000000000,
|
||
|
|
size=100,
|
||
|
|
dtype=np.int64,
|
||
|
|
)
|
||
|
|
)
|
||
|
|
with tm.assert_produces_warning(UserWarning, check_stacklevel=False):
|
||
|
|
axes = _check_plot_works(df.hist, grid=False)
|
||
|
|
self._check_axes_shape(axes, axes_num=3, layout=(2, 2))
|
||
|
|
assert not axes[1, 1].get_visible()
|
||
|
|
|
||
|
|
_check_plot_works(df[[2]].hist)
|
||
|
|
df = DataFrame(np.random.randn(100, 1))
|
||
|
|
_check_plot_works(df.hist)
|
||
|
|
|
||
|
|
# make sure layout is handled
|
||
|
|
df = DataFrame(np.random.randn(100, 5))
|
||
|
|
df[5] = to_datetime(
|
||
|
|
np.random.randint(
|
||
|
|
812419200000000000,
|
||
|
|
819331200000000000,
|
||
|
|
size=100,
|
||
|
|
dtype=np.int64,
|
||
|
|
)
|
||
|
|
)
|
||
|
|
with tm.assert_produces_warning(UserWarning, check_stacklevel=False):
|
||
|
|
axes = _check_plot_works(df.hist, layout=(4, 2))
|
||
|
|
self._check_axes_shape(axes, axes_num=6, layout=(4, 2))
|
||
|
|
|
||
|
|
# make sure sharex, sharey is handled
|
||
|
|
with tm.assert_produces_warning(UserWarning, check_stacklevel=False):
|
||
|
|
_check_plot_works(df.hist, sharex=True, sharey=True)
|
||
|
|
|
||
|
|
# handle figsize arg
|
||
|
|
with tm.assert_produces_warning(UserWarning, check_stacklevel=False):
|
||
|
|
_check_plot_works(df.hist, figsize=(8, 10))
|
||
|
|
|
||
|
|
# check bins argument
|
||
|
|
with tm.assert_produces_warning(UserWarning, check_stacklevel=False):
|
||
|
|
_check_plot_works(df.hist, bins=5)
|
||
|
|
|
||
|
|
# make sure xlabelsize and xrot are handled
|
||
|
|
ser = df[0]
|
||
|
|
xf, yf = 20, 18
|
||
|
|
xrot, yrot = 30, 40
|
||
|
|
axes = ser.hist(xlabelsize=xf, xrot=xrot, ylabelsize=yf, yrot=yrot)
|
||
|
|
self._check_ticks_props(
|
||
|
|
axes, xlabelsize=xf, xrot=xrot, ylabelsize=yf, yrot=yrot
|
||
|
|
)
|
||
|
|
|
||
|
|
xf, yf = 20, 18
|
||
|
|
xrot, yrot = 30, 40
|
||
|
|
axes = df.hist(xlabelsize=xf, xrot=xrot, ylabelsize=yf, yrot=yrot)
|
||
|
|
self._check_ticks_props(
|
||
|
|
axes, xlabelsize=xf, xrot=xrot, ylabelsize=yf, yrot=yrot
|
||
|
|
)
|
||
|
|
|
||
|
|
tm.close()
|
||
|
|
|
||
|
|
ax = ser.hist(cumulative=True, bins=4, density=True)
|
||
|
|
# height of last bin (index 5) must be 1.0
|
||
|
|
rects = [x for x in ax.get_children() if isinstance(x, Rectangle)]
|
||
|
|
tm.assert_almost_equal(rects[-1].get_height(), 1.0)
|
||
|
|
|
||
|
|
tm.close()
|
||
|
|
ax = ser.hist(log=True)
|
||
|
|
# scale of y must be 'log'
|
||
|
|
self._check_ax_scales(ax, yaxis="log")
|
||
|
|
|
||
|
|
tm.close()
|
||
|
|
|
||
|
|
# propagate attr exception from matplotlib.Axes.hist
|
||
|
|
with tm.external_error_raised(AttributeError):
|
||
|
|
ser.hist(foo="bar")
|
||
|
|
|
||
|
|
def test_hist_non_numerical_or_datetime_raises(self):
|
||
|
|
# gh-10444, GH32590
|
||
|
|
df = DataFrame(
|
||
|
|
{
|
||
|
|
"a": np.random.rand(10),
|
||
|
|
"b": np.random.randint(0, 10, 10),
|
||
|
|
"c": to_datetime(
|
||
|
|
np.random.randint(
|
||
|
|
1582800000000000000, 1583500000000000000, 10, dtype=np.int64
|
||
|
|
)
|
||
|
|
),
|
||
|
|
"d": to_datetime(
|
||
|
|
np.random.randint(
|
||
|
|
1582800000000000000, 1583500000000000000, 10, dtype=np.int64
|
||
|
|
),
|
||
|
|
utc=True,
|
||
|
|
),
|
||
|
|
}
|
||
|
|
)
|
||
|
|
df_o = df.astype(object)
|
||
|
|
|
||
|
|
msg = "hist method requires numerical or datetime columns, nothing to plot."
|
||
|
|
with pytest.raises(ValueError, match=msg):
|
||
|
|
df_o.hist()
|
||
|
|
|
||
|
|
def test_hist_layout(self):
|
||
|
|
df = DataFrame(np.random.randn(100, 2))
|
||
|
|
df[2] = to_datetime(
|
||
|
|
np.random.randint(
|
||
|
|
812419200000000000,
|
||
|
|
819331200000000000,
|
||
|
|
size=100,
|
||
|
|
dtype=np.int64,
|
||
|
|
)
|
||
|
|
)
|
||
|
|
|
||
|
|
layout_to_expected_size = (
|
||
|
|
{"layout": None, "expected_size": (2, 2)}, # default is 2x2
|
||
|
|
{"layout": (2, 2), "expected_size": (2, 2)},
|
||
|
|
{"layout": (4, 1), "expected_size": (4, 1)},
|
||
|
|
{"layout": (1, 4), "expected_size": (1, 4)},
|
||
|
|
{"layout": (3, 3), "expected_size": (3, 3)},
|
||
|
|
{"layout": (-1, 4), "expected_size": (1, 4)},
|
||
|
|
{"layout": (4, -1), "expected_size": (4, 1)},
|
||
|
|
{"layout": (-1, 2), "expected_size": (2, 2)},
|
||
|
|
{"layout": (2, -1), "expected_size": (2, 2)},
|
||
|
|
)
|
||
|
|
|
||
|
|
for layout_test in layout_to_expected_size:
|
||
|
|
axes = df.hist(layout=layout_test["layout"])
|
||
|
|
expected = layout_test["expected_size"]
|
||
|
|
self._check_axes_shape(axes, axes_num=3, layout=expected)
|
||
|
|
|
||
|
|
# layout too small for all 4 plots
|
||
|
|
msg = "Layout of 1x1 must be larger than required size 3"
|
||
|
|
with pytest.raises(ValueError, match=msg):
|
||
|
|
df.hist(layout=(1, 1))
|
||
|
|
|
||
|
|
# invalid format for layout
|
||
|
|
msg = re.escape("Layout must be a tuple of (rows, columns)")
|
||
|
|
with pytest.raises(ValueError, match=msg):
|
||
|
|
df.hist(layout=(1,))
|
||
|
|
msg = "At least one dimension of layout must be positive"
|
||
|
|
with pytest.raises(ValueError, match=msg):
|
||
|
|
df.hist(layout=(-1, -1))
|
||
|
|
|
||
|
|
# GH 9351
|
||
|
|
def test_tight_layout(self):
|
||
|
|
df = DataFrame(np.random.randn(100, 2))
|
||
|
|
df[2] = to_datetime(
|
||
|
|
np.random.randint(
|
||
|
|
812419200000000000,
|
||
|
|
819331200000000000,
|
||
|
|
size=100,
|
||
|
|
dtype=np.int64,
|
||
|
|
)
|
||
|
|
)
|
||
|
|
# Use default_axes=True when plotting method generate subplots itself
|
||
|
|
_check_plot_works(df.hist, default_axes=True)
|
||
|
|
self.plt.tight_layout()
|
||
|
|
|
||
|
|
tm.close()
|
||
|
|
|
||
|
|
def test_hist_subplot_xrot(self):
|
||
|
|
# GH 30288
|
||
|
|
df = DataFrame(
|
||
|
|
{
|
||
|
|
"length": [1.5, 0.5, 1.2, 0.9, 3],
|
||
|
|
"animal": ["pig", "rabbit", "pig", "pig", "rabbit"],
|
||
|
|
}
|
||
|
|
)
|
||
|
|
# Use default_axes=True when plotting method generate subplots itself
|
||
|
|
axes = _check_plot_works(
|
||
|
|
df.hist,
|
||
|
|
default_axes=True,
|
||
|
|
column="length",
|
||
|
|
by="animal",
|
||
|
|
bins=5,
|
||
|
|
xrot=0,
|
||
|
|
)
|
||
|
|
self._check_ticks_props(axes, xrot=0)
|
||
|
|
|
||
|
|
@pytest.mark.parametrize(
|
||
|
|
"column, expected",
|
||
|
|
[
|
||
|
|
(None, ["width", "length", "height"]),
|
||
|
|
(["length", "width", "height"], ["length", "width", "height"]),
|
||
|
|
],
|
||
|
|
)
|
||
|
|
def test_hist_column_order_unchanged(self, column, expected):
|
||
|
|
# GH29235
|
||
|
|
|
||
|
|
df = DataFrame(
|
||
|
|
{
|
||
|
|
"width": [0.7, 0.2, 0.15, 0.2, 1.1],
|
||
|
|
"length": [1.5, 0.5, 1.2, 0.9, 3],
|
||
|
|
"height": [3, 0.5, 3.4, 2, 1],
|
||
|
|
},
|
||
|
|
index=["pig", "rabbit", "duck", "chicken", "horse"],
|
||
|
|
)
|
||
|
|
|
||
|
|
# Use default_axes=True when plotting method generate subplots itself
|
||
|
|
axes = _check_plot_works(
|
||
|
|
df.hist,
|
||
|
|
default_axes=True,
|
||
|
|
column=column,
|
||
|
|
layout=(1, 3),
|
||
|
|
)
|
||
|
|
result = [axes[0, i].get_title() for i in range(3)]
|
||
|
|
assert result == expected
|
||
|
|
|
||
|
|
@pytest.mark.parametrize(
|
||
|
|
"histtype, expected",
|
||
|
|
[
|
||
|
|
("bar", True),
|
||
|
|
("barstacked", True),
|
||
|
|
("step", False),
|
||
|
|
("stepfilled", True),
|
||
|
|
],
|
||
|
|
)
|
||
|
|
def test_histtype_argument(self, histtype, expected):
|
||
|
|
# GH23992 Verify functioning of histtype argument
|
||
|
|
df = DataFrame(np.random.randint(1, 10, size=(100, 2)), columns=["a", "b"])
|
||
|
|
ax = df.hist(histtype=histtype)
|
||
|
|
self._check_patches_all_filled(ax, filled=expected)
|
||
|
|
|
||
|
|
@pytest.mark.parametrize("by", [None, "c"])
|
||
|
|
@pytest.mark.parametrize("column", [None, "b"])
|
||
|
|
def test_hist_with_legend(self, by, column):
|
||
|
|
# GH 6279 - DataFrame histogram can have a legend
|
||
|
|
expected_axes_num = 1 if by is None and column is not None else 2
|
||
|
|
expected_layout = (1, expected_axes_num)
|
||
|
|
expected_labels = column or ["a", "b"]
|
||
|
|
if by is not None:
|
||
|
|
expected_labels = [expected_labels] * 2
|
||
|
|
|
||
|
|
index = Index(15 * ["1"] + 15 * ["2"], name="c")
|
||
|
|
df = DataFrame(np.random.randn(30, 2), index=index, columns=["a", "b"])
|
||
|
|
|
||
|
|
# Use default_axes=True when plotting method generate subplots itself
|
||
|
|
axes = _check_plot_works(
|
||
|
|
df.hist,
|
||
|
|
default_axes=True,
|
||
|
|
legend=True,
|
||
|
|
by=by,
|
||
|
|
column=column,
|
||
|
|
)
|
||
|
|
|
||
|
|
self._check_axes_shape(axes, axes_num=expected_axes_num, layout=expected_layout)
|
||
|
|
if by is None and column is None:
|
||
|
|
axes = axes[0]
|
||
|
|
for expected_label, ax in zip(expected_labels, axes):
|
||
|
|
self._check_legend_labels(ax, expected_label)
|
||
|
|
|
||
|
|
@pytest.mark.parametrize("by", [None, "c"])
|
||
|
|
@pytest.mark.parametrize("column", [None, "b"])
|
||
|
|
def test_hist_with_legend_raises(self, by, column):
|
||
|
|
# GH 6279 - DataFrame histogram with legend and label raises
|
||
|
|
index = Index(15 * ["1"] + 15 * ["2"], name="c")
|
||
|
|
df = DataFrame(np.random.randn(30, 2), index=index, columns=["a", "b"])
|
||
|
|
|
||
|
|
with pytest.raises(ValueError, match="Cannot use both legend and label"):
|
||
|
|
df.hist(legend=True, by=by, column=column, label="d")
|
||
|
|
|
||
|
|
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_hist_df_with_nonnumerics(self):
|
||
|
|
# GH 9853
|
||
|
|
df = DataFrame(
|
||
|
|
np.random.RandomState(42).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
|
||
|
|
|
||
|
|
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 drawn 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()
|
||
|
|
|
||
|
|
@td.skip_if_no_mpl
|
||
|
|
def test_hist_with_nans_and_weights(self):
|
||
|
|
# GH 48884
|
||
|
|
df = DataFrame(
|
||
|
|
[[np.nan, 0.2, 0.3], [0.4, np.nan, np.nan], [0.7, 0.8, 0.9]],
|
||
|
|
columns=list("abc"),
|
||
|
|
)
|
||
|
|
weights = np.array([0.25, 0.3, 0.45])
|
||
|
|
no_nan_df = DataFrame([[0.4, 0.2, 0.3], [0.7, 0.8, 0.9]], columns=list("abc"))
|
||
|
|
no_nan_weights = np.array([[0.3, 0.25, 0.25], [0.45, 0.45, 0.45]])
|
||
|
|
|
||
|
|
from matplotlib.patches import Rectangle
|
||
|
|
|
||
|
|
_, ax0 = self.plt.subplots()
|
||
|
|
df.plot.hist(ax=ax0, weights=weights)
|
||
|
|
rects = [x for x in ax0.get_children() if isinstance(x, Rectangle)]
|
||
|
|
heights = [rect.get_height() for rect in rects]
|
||
|
|
_, ax1 = self.plt.subplots()
|
||
|
|
no_nan_df.plot.hist(ax=ax1, weights=no_nan_weights)
|
||
|
|
no_nan_rects = [x for x in ax1.get_children() if isinstance(x, Rectangle)]
|
||
|
|
no_nan_heights = [rect.get_height() for rect in no_nan_rects]
|
||
|
|
assert all(h0 == h1 for h0, h1 in zip(heights, no_nan_heights))
|
||
|
|
|
||
|
|
idxerror_weights = np.array([[0.3, 0.25], [0.45, 0.45]])
|
||
|
|
|
||
|
|
msg = "weights must have the same shape as data, or be a single column"
|
||
|
|
with pytest.raises(ValueError, match=msg):
|
||
|
|
_, ax2 = self.plt.subplots()
|
||
|
|
no_nan_df.plot.hist(ax=ax2, weights=idxerror_weights)
|
||
|
|
|
||
|
|
|
||
|
|
@td.skip_if_no_mpl
|
||
|
|
class TestDataFrameGroupByPlots(TestPlotBase):
|
||
|
|
def test_grouped_hist_legacy(self):
|
||
|
|
from matplotlib.patches import Rectangle
|
||
|
|
|
||
|
|
from pandas.plotting._matplotlib.hist import _grouped_hist
|
||
|
|
|
||
|
|
df = DataFrame(np.random.randn(500, 1), columns=["A"])
|
||
|
|
df["B"] = to_datetime(
|
||
|
|
np.random.randint(
|
||
|
|
812419200000000000,
|
||
|
|
819331200000000000,
|
||
|
|
size=500,
|
||
|
|
dtype=np.int64,
|
||
|
|
)
|
||
|
|
)
|
||
|
|
df["C"] = np.random.randint(0, 4, 500)
|
||
|
|
df["D"] = ["X"] * 500
|
||
|
|
|
||
|
|
axes = _grouped_hist(df.A, by=df.C)
|
||
|
|
self._check_axes_shape(axes, axes_num=4, layout=(2, 2))
|
||
|
|
|
||
|
|
tm.close()
|
||
|
|
axes = df.hist(by=df.C)
|
||
|
|
self._check_axes_shape(axes, axes_num=4, layout=(2, 2))
|
||
|
|
|
||
|
|
tm.close()
|
||
|
|
# group by a key with single value
|
||
|
|
axes = df.hist(by="D", rot=30)
|
||
|
|
self._check_axes_shape(axes, axes_num=1, layout=(1, 1))
|
||
|
|
self._check_ticks_props(axes, xrot=30)
|
||
|
|
|
||
|
|
tm.close()
|
||
|
|
# make sure kwargs to hist are handled
|
||
|
|
xf, yf = 20, 18
|
||
|
|
xrot, yrot = 30, 40
|
||
|
|
|
||
|
|
axes = _grouped_hist(
|
||
|
|
df.A,
|
||
|
|
by=df.C,
|
||
|
|
cumulative=True,
|
||
|
|
bins=4,
|
||
|
|
xlabelsize=xf,
|
||
|
|
xrot=xrot,
|
||
|
|
ylabelsize=yf,
|
||
|
|
yrot=yrot,
|
||
|
|
density=True,
|
||
|
|
)
|
||
|
|
# height of last bin (index 5) must be 1.0
|
||
|
|
for ax in axes.ravel():
|
||
|
|
rects = [x for x in ax.get_children() if isinstance(x, Rectangle)]
|
||
|
|
height = rects[-1].get_height()
|
||
|
|
tm.assert_almost_equal(height, 1.0)
|
||
|
|
self._check_ticks_props(
|
||
|
|
axes, xlabelsize=xf, xrot=xrot, ylabelsize=yf, yrot=yrot
|
||
|
|
)
|
||
|
|
|
||
|
|
tm.close()
|
||
|
|
axes = _grouped_hist(df.A, by=df.C, log=True)
|
||
|
|
# scale of y must be 'log'
|
||
|
|
self._check_ax_scales(axes, yaxis="log")
|
||
|
|
|
||
|
|
tm.close()
|
||
|
|
# propagate attr exception from matplotlib.Axes.hist
|
||
|
|
with tm.external_error_raised(AttributeError):
|
||
|
|
_grouped_hist(df.A, by=df.C, foo="bar")
|
||
|
|
|
||
|
|
msg = "Specify figure size by tuple instead"
|
||
|
|
with pytest.raises(ValueError, match=msg):
|
||
|
|
df.hist(by="C", figsize="default")
|
||
|
|
|
||
|
|
def test_grouped_hist_legacy2(self):
|
||
|
|
n = 10
|
||
|
|
weight = Series(np.random.normal(166, 20, size=n))
|
||
|
|
height = Series(np.random.normal(60, 10, size=n))
|
||
|
|
gender_int = np.random.RandomState(42).choice([0, 1], size=n)
|
||
|
|
df_int = DataFrame({"height": height, "weight": weight, "gender": gender_int})
|
||
|
|
gb = df_int.groupby("gender")
|
||
|
|
axes = gb.hist()
|
||
|
|
assert len(axes) == 2
|
||
|
|
assert len(self.plt.get_fignums()) == 2
|
||
|
|
tm.close()
|
||
|
|
|
||
|
|
@pytest.mark.slow
|
||
|
|
def test_grouped_hist_layout(self, hist_df):
|
||
|
|
df = hist_df
|
||
|
|
msg = "Layout of 1x1 must be larger than required size 2"
|
||
|
|
with pytest.raises(ValueError, match=msg):
|
||
|
|
df.hist(column="weight", by=df.gender, layout=(1, 1))
|
||
|
|
|
||
|
|
msg = "Layout of 1x3 must be larger than required size 4"
|
||
|
|
with pytest.raises(ValueError, match=msg):
|
||
|
|
df.hist(column="height", by=df.category, layout=(1, 3))
|
||
|
|
|
||
|
|
msg = "At least one dimension of layout must be positive"
|
||
|
|
with pytest.raises(ValueError, match=msg):
|
||
|
|
df.hist(column="height", by=df.category, layout=(-1, -1))
|
||
|
|
|
||
|
|
with tm.assert_produces_warning(UserWarning, check_stacklevel=False):
|
||
|
|
axes = _check_plot_works(
|
||
|
|
df.hist, column="height", by=df.gender, layout=(2, 1)
|
||
|
|
)
|
||
|
|
self._check_axes_shape(axes, axes_num=2, layout=(2, 1))
|
||
|
|
|
||
|
|
with tm.assert_produces_warning(UserWarning, check_stacklevel=False):
|
||
|
|
axes = _check_plot_works(
|
||
|
|
df.hist, column="height", by=df.gender, layout=(2, -1)
|
||
|
|
)
|
||
|
|
self._check_axes_shape(axes, axes_num=2, layout=(2, 1))
|
||
|
|
|
||
|
|
axes = df.hist(column="height", by=df.category, layout=(4, 1))
|
||
|
|
self._check_axes_shape(axes, axes_num=4, layout=(4, 1))
|
||
|
|
|
||
|
|
axes = df.hist(column="height", by=df.category, layout=(-1, 1))
|
||
|
|
self._check_axes_shape(axes, axes_num=4, layout=(4, 1))
|
||
|
|
|
||
|
|
axes = df.hist(column="height", by=df.category, layout=(4, 2), figsize=(12, 8))
|
||
|
|
self._check_axes_shape(axes, axes_num=4, layout=(4, 2), figsize=(12, 8))
|
||
|
|
tm.close()
|
||
|
|
|
||
|
|
# GH 6769
|
||
|
|
with tm.assert_produces_warning(UserWarning, check_stacklevel=False):
|
||
|
|
axes = _check_plot_works(
|
||
|
|
df.hist, column="height", by="classroom", layout=(2, 2)
|
||
|
|
)
|
||
|
|
self._check_axes_shape(axes, axes_num=3, layout=(2, 2))
|
||
|
|
|
||
|
|
# without column
|
||
|
|
with tm.assert_produces_warning(UserWarning, check_stacklevel=False):
|
||
|
|
axes = _check_plot_works(df.hist, by="classroom")
|
||
|
|
self._check_axes_shape(axes, axes_num=3, layout=(2, 2))
|
||
|
|
|
||
|
|
axes = df.hist(by="gender", layout=(3, 5))
|
||
|
|
self._check_axes_shape(axes, axes_num=2, layout=(3, 5))
|
||
|
|
|
||
|
|
axes = df.hist(column=["height", "weight", "category"])
|
||
|
|
self._check_axes_shape(axes, axes_num=3, layout=(2, 2))
|
||
|
|
|
||
|
|
def test_grouped_hist_multiple_axes(self, hist_df):
|
||
|
|
# GH 6970, GH 7069
|
||
|
|
df = hist_df
|
||
|
|
|
||
|
|
fig, axes = self.plt.subplots(2, 3)
|
||
|
|
returned = df.hist(column=["height", "weight", "category"], ax=axes[0])
|
||
|
|
self._check_axes_shape(returned, axes_num=3, layout=(1, 3))
|
||
|
|
tm.assert_numpy_array_equal(returned, axes[0])
|
||
|
|
assert returned[0].figure is fig
|
||
|
|
returned = df.hist(by="classroom", ax=axes[1])
|
||
|
|
self._check_axes_shape(returned, axes_num=3, layout=(1, 3))
|
||
|
|
tm.assert_numpy_array_equal(returned, axes[1])
|
||
|
|
assert returned[0].figure is fig
|
||
|
|
|
||
|
|
fig, axes = self.plt.subplots(2, 3)
|
||
|
|
# pass different number of axes from required
|
||
|
|
msg = "The number of passed axes must be 1, the same as the output plot"
|
||
|
|
with pytest.raises(ValueError, match=msg):
|
||
|
|
axes = df.hist(column="height", ax=axes)
|
||
|
|
|
||
|
|
def test_axis_share_x(self, hist_df):
|
||
|
|
df = hist_df
|
||
|
|
# GH4089
|
||
|
|
ax1, ax2 = df.hist(column="height", by=df.gender, sharex=True)
|
||
|
|
|
||
|
|
# share x
|
||
|
|
assert self.get_x_axis(ax1).joined(ax1, ax2)
|
||
|
|
assert self.get_x_axis(ax2).joined(ax1, ax2)
|
||
|
|
|
||
|
|
# don't share y
|
||
|
|
assert not self.get_y_axis(ax1).joined(ax1, ax2)
|
||
|
|
assert not self.get_y_axis(ax2).joined(ax1, ax2)
|
||
|
|
|
||
|
|
def test_axis_share_y(self, hist_df):
|
||
|
|
df = hist_df
|
||
|
|
ax1, ax2 = df.hist(column="height", by=df.gender, sharey=True)
|
||
|
|
|
||
|
|
# share y
|
||
|
|
assert self.get_y_axis(ax1).joined(ax1, ax2)
|
||
|
|
assert self.get_y_axis(ax2).joined(ax1, ax2)
|
||
|
|
|
||
|
|
# don't share x
|
||
|
|
assert not self.get_x_axis(ax1).joined(ax1, ax2)
|
||
|
|
assert not self.get_x_axis(ax2).joined(ax1, ax2)
|
||
|
|
|
||
|
|
def test_axis_share_xy(self, hist_df):
|
||
|
|
df = hist_df
|
||
|
|
ax1, ax2 = df.hist(column="height", by=df.gender, sharex=True, sharey=True)
|
||
|
|
|
||
|
|
# share both x and y
|
||
|
|
assert self.get_x_axis(ax1).joined(ax1, ax2)
|
||
|
|
assert self.get_x_axis(ax2).joined(ax1, ax2)
|
||
|
|
|
||
|
|
assert self.get_y_axis(ax1).joined(ax1, ax2)
|
||
|
|
assert self.get_y_axis(ax2).joined(ax1, ax2)
|
||
|
|
|
||
|
|
@pytest.mark.parametrize(
|
||
|
|
"histtype, expected",
|
||
|
|
[
|
||
|
|
("bar", True),
|
||
|
|
("barstacked", True),
|
||
|
|
("step", False),
|
||
|
|
("stepfilled", True),
|
||
|
|
],
|
||
|
|
)
|
||
|
|
def test_histtype_argument(self, histtype, expected):
|
||
|
|
# GH23992 Verify functioning of histtype argument
|
||
|
|
df = DataFrame(np.random.randint(1, 10, size=(100, 2)), columns=["a", "b"])
|
||
|
|
ax = df.hist(by="a", histtype=histtype)
|
||
|
|
self._check_patches_all_filled(ax, filled=expected)
|