643 lines
22 KiB
Python
643 lines
22 KiB
Python
""" Test cases for .hist method """
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import numpy as np
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import pytest
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import pandas.util._test_decorators as td
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from pandas import DataFrame, Index, Series, to_datetime
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import pandas._testing as tm
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from pandas.tests.plotting.common import TestPlotBase, _check_plot_works
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pytestmark = pytest.mark.slow
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@td.skip_if_no_mpl
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class TestSeriesPlots(TestPlotBase):
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def setup_method(self, method):
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TestPlotBase.setup_method(self, method)
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import matplotlib as mpl
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mpl.rcdefaults()
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self.ts = tm.makeTimeSeries()
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self.ts.name = "ts"
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def test_hist_legacy(self):
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_check_plot_works(self.ts.hist)
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_check_plot_works(self.ts.hist, grid=False)
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_check_plot_works(self.ts.hist, figsize=(8, 10))
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# _check_plot_works adds an ax so catch warning. see GH #13188
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with tm.assert_produces_warning(UserWarning):
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_check_plot_works(self.ts.hist, by=self.ts.index.month)
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with tm.assert_produces_warning(UserWarning):
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_check_plot_works(self.ts.hist, by=self.ts.index.month, bins=5)
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fig, ax = self.plt.subplots(1, 1)
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_check_plot_works(self.ts.hist, ax=ax)
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_check_plot_works(self.ts.hist, ax=ax, figure=fig)
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_check_plot_works(self.ts.hist, figure=fig)
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tm.close()
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fig, (ax1, ax2) = self.plt.subplots(1, 2)
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_check_plot_works(self.ts.hist, figure=fig, ax=ax1)
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_check_plot_works(self.ts.hist, figure=fig, ax=ax2)
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with pytest.raises(ValueError):
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self.ts.hist(by=self.ts.index, figure=fig)
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def test_hist_bins_legacy(self):
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df = DataFrame(np.random.randn(10, 2))
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ax = df.hist(bins=2)[0][0]
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assert len(ax.patches) == 2
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def test_hist_layout(self):
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df = self.hist_df
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with pytest.raises(ValueError):
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df.height.hist(layout=(1, 1))
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with pytest.raises(ValueError):
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df.height.hist(layout=[1, 1])
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def test_hist_layout_with_by(self):
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df = self.hist_df
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# _check_plot_works adds an `ax` kwarg to the method call
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# so we get a warning about an axis being cleared, even
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# though we don't explicing pass one, see GH #13188
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with tm.assert_produces_warning(UserWarning):
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axes = _check_plot_works(df.height.hist, by=df.gender, layout=(2, 1))
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self._check_axes_shape(axes, axes_num=2, layout=(2, 1))
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with tm.assert_produces_warning(UserWarning):
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axes = _check_plot_works(df.height.hist, by=df.gender, layout=(3, -1))
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self._check_axes_shape(axes, axes_num=2, layout=(3, 1))
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with tm.assert_produces_warning(UserWarning):
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axes = _check_plot_works(df.height.hist, by=df.category, layout=(4, 1))
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self._check_axes_shape(axes, axes_num=4, layout=(4, 1))
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with tm.assert_produces_warning(UserWarning):
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axes = _check_plot_works(df.height.hist, by=df.category, layout=(2, -1))
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self._check_axes_shape(axes, axes_num=4, layout=(2, 2))
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with tm.assert_produces_warning(UserWarning):
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axes = _check_plot_works(df.height.hist, by=df.category, layout=(3, -1))
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self._check_axes_shape(axes, axes_num=4, layout=(3, 2))
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with tm.assert_produces_warning(UserWarning):
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axes = _check_plot_works(df.height.hist, by=df.category, layout=(-1, 4))
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self._check_axes_shape(axes, axes_num=4, layout=(1, 4))
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with tm.assert_produces_warning(UserWarning):
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axes = _check_plot_works(df.height.hist, by=df.classroom, layout=(2, 2))
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self._check_axes_shape(axes, axes_num=3, layout=(2, 2))
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axes = df.height.hist(by=df.category, layout=(4, 2), figsize=(12, 7))
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self._check_axes_shape(axes, axes_num=4, layout=(4, 2), figsize=(12, 7))
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def test_hist_no_overlap(self):
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from matplotlib.pyplot import gcf, subplot
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x = Series(np.random.randn(2))
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y = Series(np.random.randn(2))
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subplot(121)
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x.hist()
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subplot(122)
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y.hist()
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fig = gcf()
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axes = fig.axes
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assert len(axes) == 2
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def test_hist_by_no_extra_plots(self):
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df = self.hist_df
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axes = df.height.hist(by=df.gender) # noqa
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assert len(self.plt.get_fignums()) == 1
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def test_plot_fails_when_ax_differs_from_figure(self):
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from pylab import figure
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fig1 = figure()
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fig2 = figure()
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ax1 = fig1.add_subplot(111)
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with pytest.raises(AssertionError):
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self.ts.hist(ax=ax1, figure=fig2)
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@pytest.mark.parametrize(
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"histtype, expected",
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[
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("bar", True),
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("barstacked", True),
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("step", False),
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("stepfilled", True),
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],
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)
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def test_histtype_argument(self, histtype, expected):
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# GH23992 Verify functioning of histtype argument
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ser = Series(np.random.randint(1, 10))
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ax = ser.hist(histtype=histtype)
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self._check_patches_all_filled(ax, filled=expected)
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@pytest.mark.parametrize(
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"by, expected_axes_num, expected_layout", [(None, 1, (1, 1)), ("b", 2, (1, 2))]
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)
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def test_hist_with_legend(self, by, expected_axes_num, expected_layout):
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# GH 6279 - Series histogram can have a legend
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index = 15 * ["1"] + 15 * ["2"]
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s = Series(np.random.randn(30), index=index, name="a")
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s.index.name = "b"
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# Use default_axes=True when plotting method generate subplots itself
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axes = _check_plot_works(s.hist, default_axes=True, legend=True, by=by)
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self._check_axes_shape(axes, axes_num=expected_axes_num, layout=expected_layout)
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self._check_legend_labels(axes, "a")
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@pytest.mark.parametrize("by", [None, "b"])
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def test_hist_with_legend_raises(self, by):
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# GH 6279 - Series histogram with legend and label raises
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index = 15 * ["1"] + 15 * ["2"]
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s = Series(np.random.randn(30), index=index, name="a")
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s.index.name = "b"
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with pytest.raises(ValueError, match="Cannot use both legend and label"):
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s.hist(legend=True, by=by, label="c")
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@td.skip_if_no_mpl
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class TestDataFramePlots(TestPlotBase):
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def test_hist_df_legacy(self):
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from matplotlib.patches import Rectangle
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with tm.assert_produces_warning(UserWarning):
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_check_plot_works(self.hist_df.hist)
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# make sure layout is handled
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df = DataFrame(np.random.randn(100, 2))
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df[2] = to_datetime(
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np.random.randint(
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self.start_date_to_int64,
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self.end_date_to_int64,
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size=100,
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dtype=np.int64,
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)
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)
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with tm.assert_produces_warning(UserWarning):
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axes = _check_plot_works(df.hist, grid=False)
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self._check_axes_shape(axes, axes_num=3, layout=(2, 2))
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assert not axes[1, 1].get_visible()
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_check_plot_works(df[[2]].hist)
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df = DataFrame(np.random.randn(100, 1))
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_check_plot_works(df.hist)
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# make sure layout is handled
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df = DataFrame(np.random.randn(100, 5))
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df[5] = to_datetime(
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np.random.randint(
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self.start_date_to_int64,
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self.end_date_to_int64,
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size=100,
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dtype=np.int64,
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)
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)
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with tm.assert_produces_warning(UserWarning):
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axes = _check_plot_works(df.hist, layout=(4, 2))
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self._check_axes_shape(axes, axes_num=6, layout=(4, 2))
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# make sure sharex, sharey is handled
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with tm.assert_produces_warning(UserWarning):
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_check_plot_works(df.hist, sharex=True, sharey=True)
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# handle figsize arg
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with tm.assert_produces_warning(UserWarning):
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_check_plot_works(df.hist, figsize=(8, 10))
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# check bins argument
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with tm.assert_produces_warning(UserWarning):
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_check_plot_works(df.hist, bins=5)
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# make sure xlabelsize and xrot are handled
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ser = df[0]
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xf, yf = 20, 18
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xrot, yrot = 30, 40
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axes = ser.hist(xlabelsize=xf, xrot=xrot, ylabelsize=yf, yrot=yrot)
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self._check_ticks_props(
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axes, xlabelsize=xf, xrot=xrot, ylabelsize=yf, yrot=yrot
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)
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xf, yf = 20, 18
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xrot, yrot = 30, 40
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axes = df.hist(xlabelsize=xf, xrot=xrot, ylabelsize=yf, yrot=yrot)
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self._check_ticks_props(
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axes, xlabelsize=xf, xrot=xrot, ylabelsize=yf, yrot=yrot
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)
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tm.close()
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ax = ser.hist(cumulative=True, bins=4, density=True)
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# height of last bin (index 5) must be 1.0
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rects = [x for x in ax.get_children() if isinstance(x, Rectangle)]
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tm.assert_almost_equal(rects[-1].get_height(), 1.0)
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tm.close()
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ax = ser.hist(log=True)
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# scale of y must be 'log'
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self._check_ax_scales(ax, yaxis="log")
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tm.close()
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# propagate attr exception from matplotlib.Axes.hist
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with pytest.raises(AttributeError):
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ser.hist(foo="bar")
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def test_hist_non_numerical_or_datetime_raises(self):
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# gh-10444, GH32590
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df = DataFrame(
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{
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"a": np.random.rand(10),
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"b": np.random.randint(0, 10, 10),
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"c": to_datetime(
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np.random.randint(
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1582800000000000000, 1583500000000000000, 10, dtype=np.int64
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)
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),
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"d": to_datetime(
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np.random.randint(
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1582800000000000000, 1583500000000000000, 10, dtype=np.int64
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),
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utc=True,
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),
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}
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)
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df_o = df.astype(object)
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msg = "hist method requires numerical or datetime columns, nothing to plot."
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with pytest.raises(ValueError, match=msg):
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df_o.hist()
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def test_hist_layout(self):
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df = DataFrame(np.random.randn(100, 2))
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df[2] = to_datetime(
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np.random.randint(
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self.start_date_to_int64,
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self.end_date_to_int64,
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size=100,
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dtype=np.int64,
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)
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)
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layout_to_expected_size = (
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{"layout": None, "expected_size": (2, 2)}, # default is 2x2
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{"layout": (2, 2), "expected_size": (2, 2)},
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{"layout": (4, 1), "expected_size": (4, 1)},
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{"layout": (1, 4), "expected_size": (1, 4)},
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{"layout": (3, 3), "expected_size": (3, 3)},
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{"layout": (-1, 4), "expected_size": (1, 4)},
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{"layout": (4, -1), "expected_size": (4, 1)},
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{"layout": (-1, 2), "expected_size": (2, 2)},
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{"layout": (2, -1), "expected_size": (2, 2)},
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)
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for layout_test in layout_to_expected_size:
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axes = df.hist(layout=layout_test["layout"])
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expected = layout_test["expected_size"]
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self._check_axes_shape(axes, axes_num=3, layout=expected)
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# layout too small for all 4 plots
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with pytest.raises(ValueError):
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df.hist(layout=(1, 1))
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# invalid format for layout
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with pytest.raises(ValueError):
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df.hist(layout=(1,))
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with pytest.raises(ValueError):
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df.hist(layout=(-1, -1))
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# GH 9351
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def test_tight_layout(self):
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df = DataFrame(np.random.randn(100, 2))
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df[2] = to_datetime(
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np.random.randint(
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self.start_date_to_int64,
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self.end_date_to_int64,
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size=100,
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dtype=np.int64,
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)
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)
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# Use default_axes=True when plotting method generate subplots itself
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_check_plot_works(df.hist, default_axes=True)
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self.plt.tight_layout()
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tm.close()
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def test_hist_subplot_xrot(self):
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# GH 30288
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df = DataFrame(
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{
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"length": [1.5, 0.5, 1.2, 0.9, 3],
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"animal": ["pig", "rabbit", "pig", "pig", "rabbit"],
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}
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)
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# Use default_axes=True when plotting method generate subplots itself
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axes = _check_plot_works(
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df.hist,
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default_axes=True,
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filterwarnings="always",
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column="length",
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by="animal",
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bins=5,
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xrot=0,
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)
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self._check_ticks_props(axes, xrot=0)
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@pytest.mark.parametrize(
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"column, expected",
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[
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(None, ["width", "length", "height"]),
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(["length", "width", "height"], ["length", "width", "height"]),
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],
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)
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def test_hist_column_order_unchanged(self, column, expected):
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# GH29235
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df = DataFrame(
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{
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"width": [0.7, 0.2, 0.15, 0.2, 1.1],
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"length": [1.5, 0.5, 1.2, 0.9, 3],
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"height": [3, 0.5, 3.4, 2, 1],
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},
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index=["pig", "rabbit", "duck", "chicken", "horse"],
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)
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# Use default_axes=True when plotting method generate subplots itself
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axes = _check_plot_works(
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df.hist,
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default_axes=True,
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column=column,
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layout=(1, 3),
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)
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result = [axes[0, i].get_title() for i in range(3)]
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assert result == expected
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@pytest.mark.parametrize(
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"histtype, expected",
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[
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("bar", True),
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("barstacked", True),
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("step", False),
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("stepfilled", True),
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],
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)
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def test_histtype_argument(self, histtype, expected):
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# GH23992 Verify functioning of histtype argument
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df = DataFrame(np.random.randint(1, 10, size=(100, 2)), columns=["a", "b"])
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ax = df.hist(histtype=histtype)
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self._check_patches_all_filled(ax, filled=expected)
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@pytest.mark.parametrize("by", [None, "c"])
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@pytest.mark.parametrize("column", [None, "b"])
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def test_hist_with_legend(self, by, column):
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# GH 6279 - DataFrame histogram can have a legend
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expected_axes_num = 1 if by is None and column is not None else 2
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expected_layout = (1, expected_axes_num)
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expected_labels = column or ["a", "b"]
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if by is not None:
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expected_labels = [expected_labels] * 2
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index = Index(15 * ["1"] + 15 * ["2"], name="c")
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df = DataFrame(np.random.randn(30, 2), index=index, columns=["a", "b"])
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# Use default_axes=True when plotting method generate subplots itself
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axes = _check_plot_works(
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df.hist,
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default_axes=True,
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legend=True,
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by=by,
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column=column,
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)
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self._check_axes_shape(axes, axes_num=expected_axes_num, layout=expected_layout)
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if by is None and column is None:
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axes = axes[0]
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for expected_label, ax in zip(expected_labels, axes):
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self._check_legend_labels(ax, expected_label)
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@pytest.mark.parametrize("by", [None, "c"])
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@pytest.mark.parametrize("column", [None, "b"])
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def test_hist_with_legend_raises(self, by, column):
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# GH 6279 - DataFrame histogram with legend and label raises
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index = Index(15 * ["1"] + 15 * ["2"], name="c")
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df = DataFrame(np.random.randn(30, 2), index=index, columns=["a", "b"])
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with pytest.raises(ValueError, match="Cannot use both legend and label"):
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df.hist(legend=True, by=by, column=column, label="d")
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@td.skip_if_no_mpl
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class TestDataFrameGroupByPlots(TestPlotBase):
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def test_grouped_hist_legacy(self):
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from matplotlib.patches import Rectangle
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from pandas.plotting._matplotlib.hist import _grouped_hist
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df = DataFrame(np.random.randn(500, 1), columns=["A"])
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df["B"] = to_datetime(
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np.random.randint(
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self.start_date_to_int64,
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self.end_date_to_int64,
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size=500,
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dtype=np.int64,
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)
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)
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df["C"] = np.random.randint(0, 4, 500)
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df["D"] = ["X"] * 500
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axes = _grouped_hist(df.A, by=df.C)
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self._check_axes_shape(axes, axes_num=4, layout=(2, 2))
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tm.close()
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axes = df.hist(by=df.C)
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self._check_axes_shape(axes, axes_num=4, layout=(2, 2))
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tm.close()
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# group by a key with single value
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axes = df.hist(by="D", rot=30)
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self._check_axes_shape(axes, axes_num=1, layout=(1, 1))
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self._check_ticks_props(axes, xrot=30)
|
|
|
|
tm.close()
|
|
# make sure kwargs to hist are handled
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|
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 pytest.raises(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))
|
|
with tm.RNGContext(42):
|
|
gender_int = np.random.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()
|
|
|
|
def test_grouped_hist_layout(self):
|
|
df = self.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):
|
|
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):
|
|
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):
|
|
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):
|
|
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):
|
|
# GH 6970, GH 7069
|
|
df = self.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
|
|
|
|
with pytest.raises(ValueError):
|
|
fig, axes = self.plt.subplots(2, 3)
|
|
# pass different number of axes from required
|
|
axes = df.hist(column="height", ax=axes)
|
|
|
|
def test_axis_share_x(self):
|
|
df = self.hist_df
|
|
# GH4089
|
|
ax1, ax2 = df.hist(column="height", by=df.gender, sharex=True)
|
|
|
|
# share x
|
|
assert ax1._shared_x_axes.joined(ax1, ax2)
|
|
assert ax2._shared_x_axes.joined(ax1, ax2)
|
|
|
|
# don't share y
|
|
assert not ax1._shared_y_axes.joined(ax1, ax2)
|
|
assert not ax2._shared_y_axes.joined(ax1, ax2)
|
|
|
|
def test_axis_share_y(self):
|
|
df = self.hist_df
|
|
ax1, ax2 = df.hist(column="height", by=df.gender, sharey=True)
|
|
|
|
# share y
|
|
assert ax1._shared_y_axes.joined(ax1, ax2)
|
|
assert ax2._shared_y_axes.joined(ax1, ax2)
|
|
|
|
# don't share x
|
|
assert not ax1._shared_x_axes.joined(ax1, ax2)
|
|
assert not ax2._shared_x_axes.joined(ax1, ax2)
|
|
|
|
def test_axis_share_xy(self):
|
|
df = self.hist_df
|
|
ax1, ax2 = df.hist(column="height", by=df.gender, sharex=True, sharey=True)
|
|
|
|
# share both x and y
|
|
assert ax1._shared_x_axes.joined(ax1, ax2)
|
|
assert ax2._shared_x_axes.joined(ax1, ax2)
|
|
|
|
assert ax1._shared_y_axes.joined(ax1, ax2)
|
|
assert ax2._shared_y_axes.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)
|