398 lines
16 KiB
Python
398 lines
16 KiB
Python
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# coding: utf-8
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import pytest
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import itertools
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import string
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from distutils.version import LooseVersion
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from pandas import Series, DataFrame, MultiIndex
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from pandas.compat import range, lzip
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import pandas.util.testing as tm
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import pandas.util._test_decorators as td
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import numpy as np
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from numpy import random
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import pandas.plotting as plotting
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from pandas.tests.plotting.common import (TestPlotBase, _check_plot_works)
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""" Test cases for .boxplot method """
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def _skip_if_mpl_14_or_dev_boxplot():
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# GH 8382
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# Boxplot failures on 1.4 and 1.4.1
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# Don't need try / except since that's done at class level
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import matplotlib
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if LooseVersion(matplotlib.__version__) >= LooseVersion('1.4'):
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pytest.skip("Matplotlib Regression in 1.4 and current dev.")
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@td.skip_if_no_mpl
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class TestDataFramePlots(TestPlotBase):
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@pytest.mark.slow
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def test_boxplot_legacy1(self):
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df = DataFrame(np.random.randn(6, 4),
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index=list(string.ascii_letters[:6]),
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columns=['one', 'two', 'three', 'four'])
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df['indic'] = ['foo', 'bar'] * 3
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df['indic2'] = ['foo', 'bar', 'foo'] * 2
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_check_plot_works(df.boxplot, return_type='dict')
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_check_plot_works(df.boxplot, column=[
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'one', 'two'], return_type='dict')
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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(df.boxplot, column=['one', 'two'],
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by='indic')
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_check_plot_works(df.boxplot, column='one', by=['indic', 'indic2'])
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with tm.assert_produces_warning(UserWarning):
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_check_plot_works(df.boxplot, by='indic')
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with tm.assert_produces_warning(UserWarning):
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_check_plot_works(df.boxplot, by=['indic', 'indic2'])
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_check_plot_works(plotting._core.boxplot, data=df['one'],
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return_type='dict')
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_check_plot_works(df.boxplot, notch=1, return_type='dict')
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with tm.assert_produces_warning(UserWarning):
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_check_plot_works(df.boxplot, by='indic', notch=1)
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@pytest.mark.slow
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def test_boxplot_legacy2(self):
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df = DataFrame(np.random.rand(10, 2), columns=['Col1', 'Col2'])
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df['X'] = Series(['A', 'A', 'A', 'A', 'A', 'B', 'B', 'B', 'B', 'B'])
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df['Y'] = Series(['A'] * 10)
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with tm.assert_produces_warning(UserWarning):
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_check_plot_works(df.boxplot, by='X')
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# When ax is supplied and required number of axes is 1,
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# passed ax should be used:
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fig, ax = self.plt.subplots()
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axes = df.boxplot('Col1', by='X', ax=ax)
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ax_axes = ax.axes if self.mpl_ge_1_5_0 else ax.get_axes()
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assert ax_axes is axes
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fig, ax = self.plt.subplots()
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axes = df.groupby('Y').boxplot(ax=ax, return_type='axes')
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ax_axes = ax.axes if self.mpl_ge_1_5_0 else ax.get_axes()
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assert ax_axes is axes['A']
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# Multiple columns with an ax argument should use same figure
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fig, ax = self.plt.subplots()
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with tm.assert_produces_warning(UserWarning):
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axes = df.boxplot(column=['Col1', 'Col2'],
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by='X', ax=ax, return_type='axes')
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assert axes['Col1'].get_figure() is fig
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# When by is None, check that all relevant lines are present in the
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# dict
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fig, ax = self.plt.subplots()
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d = df.boxplot(ax=ax, return_type='dict')
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lines = list(itertools.chain.from_iterable(d.values()))
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assert len(ax.get_lines()) == len(lines)
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@pytest.mark.slow
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def test_boxplot_return_type_none(self):
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# GH 12216; return_type=None & by=None -> axes
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result = self.hist_df.boxplot()
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assert isinstance(result, self.plt.Axes)
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@pytest.mark.slow
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def test_boxplot_return_type_legacy(self):
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# API change in https://github.com/pandas-dev/pandas/pull/7096
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import matplotlib as mpl # noqa
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df = DataFrame(np.random.randn(6, 4),
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index=list(string.ascii_letters[:6]),
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columns=['one', 'two', 'three', 'four'])
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with pytest.raises(ValueError):
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df.boxplot(return_type='NOTATYPE')
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result = df.boxplot()
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self._check_box_return_type(result, 'axes')
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with tm.assert_produces_warning(False):
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result = df.boxplot(return_type='dict')
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self._check_box_return_type(result, 'dict')
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with tm.assert_produces_warning(False):
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result = df.boxplot(return_type='axes')
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self._check_box_return_type(result, 'axes')
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with tm.assert_produces_warning(False):
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result = df.boxplot(return_type='both')
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self._check_box_return_type(result, 'both')
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@pytest.mark.slow
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def test_boxplot_axis_limits(self):
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def _check_ax_limits(col, ax):
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y_min, y_max = ax.get_ylim()
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assert y_min <= col.min()
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assert y_max >= col.max()
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df = self.hist_df.copy()
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df['age'] = np.random.randint(1, 20, df.shape[0])
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# One full row
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height_ax, weight_ax = df.boxplot(['height', 'weight'], by='category')
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_check_ax_limits(df['height'], height_ax)
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_check_ax_limits(df['weight'], weight_ax)
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assert weight_ax._sharey == height_ax
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# Two rows, one partial
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p = df.boxplot(['height', 'weight', 'age'], by='category')
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height_ax, weight_ax, age_ax = p[0, 0], p[0, 1], p[1, 0]
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dummy_ax = p[1, 1]
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_check_ax_limits(df['height'], height_ax)
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_check_ax_limits(df['weight'], weight_ax)
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_check_ax_limits(df['age'], age_ax)
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assert weight_ax._sharey == height_ax
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assert age_ax._sharey == height_ax
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assert dummy_ax._sharey is None
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@pytest.mark.slow
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def test_boxplot_empty_column(self):
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_skip_if_mpl_14_or_dev_boxplot()
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df = DataFrame(np.random.randn(20, 4))
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df.loc[:, 0] = np.nan
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_check_plot_works(df.boxplot, return_type='axes')
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@pytest.mark.slow
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def test_figsize(self):
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df = DataFrame(np.random.rand(10, 5),
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columns=['A', 'B', 'C', 'D', 'E'])
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result = df.boxplot(return_type='axes', figsize=(12, 8))
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assert result.figure.bbox_inches.width == 12
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assert result.figure.bbox_inches.height == 8
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def test_fontsize(self):
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df = DataFrame({"a": [1, 2, 3, 4, 5, 6]})
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self._check_ticks_props(df.boxplot("a", fontsize=16),
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xlabelsize=16, ylabelsize=16)
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@td.skip_if_no_mpl
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class TestDataFrameGroupByPlots(TestPlotBase):
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@pytest.mark.slow
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def test_boxplot_legacy1(self):
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grouped = self.hist_df.groupby(by='gender')
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with tm.assert_produces_warning(UserWarning):
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axes = _check_plot_works(grouped.boxplot, return_type='axes')
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self._check_axes_shape(list(axes.values), axes_num=2, layout=(1, 2))
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axes = _check_plot_works(grouped.boxplot, subplots=False,
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return_type='axes')
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self._check_axes_shape(axes, axes_num=1, layout=(1, 1))
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@pytest.mark.slow
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def test_boxplot_legacy2(self):
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tuples = lzip(string.ascii_letters[:10], range(10))
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df = DataFrame(np.random.rand(10, 3),
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index=MultiIndex.from_tuples(tuples))
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grouped = df.groupby(level=1)
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with tm.assert_produces_warning(UserWarning):
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axes = _check_plot_works(grouped.boxplot, return_type='axes')
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self._check_axes_shape(list(axes.values), axes_num=10, layout=(4, 3))
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axes = _check_plot_works(grouped.boxplot, subplots=False,
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return_type='axes')
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self._check_axes_shape(axes, axes_num=1, layout=(1, 1))
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@pytest.mark.slow
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def test_boxplot_legacy3(self):
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tuples = lzip(string.ascii_letters[:10], range(10))
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df = DataFrame(np.random.rand(10, 3),
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index=MultiIndex.from_tuples(tuples))
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grouped = df.unstack(level=1).groupby(level=0, axis=1)
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with tm.assert_produces_warning(UserWarning):
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axes = _check_plot_works(grouped.boxplot, return_type='axes')
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self._check_axes_shape(list(axes.values), axes_num=3, layout=(2, 2))
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axes = _check_plot_works(grouped.boxplot, subplots=False,
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return_type='axes')
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self._check_axes_shape(axes, axes_num=1, layout=(1, 1))
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@pytest.mark.slow
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def test_grouped_plot_fignums(self):
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n = 10
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weight = Series(np.random.normal(166, 20, size=n))
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height = Series(np.random.normal(60, 10, size=n))
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with tm.RNGContext(42):
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gender = np.random.choice(['male', 'female'], size=n)
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df = DataFrame({'height': height, 'weight': weight, 'gender': gender})
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gb = df.groupby('gender')
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res = gb.plot()
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assert len(self.plt.get_fignums()) == 2
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assert len(res) == 2
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tm.close()
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res = gb.boxplot(return_type='axes')
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assert len(self.plt.get_fignums()) == 1
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assert len(res) == 2
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tm.close()
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# now works with GH 5610 as gender is excluded
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res = df.groupby('gender').hist()
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tm.close()
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@pytest.mark.slow
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def test_grouped_box_return_type(self):
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df = self.hist_df
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# old style: return_type=None
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result = df.boxplot(by='gender')
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assert isinstance(result, np.ndarray)
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self._check_box_return_type(
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result, None,
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expected_keys=['height', 'weight', 'category'])
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# now for groupby
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result = df.groupby('gender').boxplot(return_type='dict')
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self._check_box_return_type(
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result, 'dict', expected_keys=['Male', 'Female'])
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columns2 = 'X B C D A G Y N Q O'.split()
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df2 = DataFrame(random.randn(50, 10), columns=columns2)
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categories2 = 'A B C D E F G H I J'.split()
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df2['category'] = categories2 * 5
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for t in ['dict', 'axes', 'both']:
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returned = df.groupby('classroom').boxplot(return_type=t)
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self._check_box_return_type(
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returned, t, expected_keys=['A', 'B', 'C'])
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returned = df.boxplot(by='classroom', return_type=t)
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self._check_box_return_type(
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returned, t,
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expected_keys=['height', 'weight', 'category'])
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returned = df2.groupby('category').boxplot(return_type=t)
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self._check_box_return_type(returned, t, expected_keys=categories2)
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returned = df2.boxplot(by='category', return_type=t)
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self._check_box_return_type(returned, t, expected_keys=columns2)
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@pytest.mark.slow
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def test_grouped_box_layout(self):
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df = self.hist_df
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pytest.raises(ValueError, df.boxplot, column=['weight', 'height'],
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by=df.gender, layout=(1, 1))
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pytest.raises(ValueError, df.boxplot,
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column=['height', 'weight', 'category'],
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layout=(2, 1), return_type='dict')
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pytest.raises(ValueError, df.boxplot, column=['weight', 'height'],
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by=df.gender, layout=(-1, -1))
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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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box = _check_plot_works(df.groupby('gender').boxplot,
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column='height', return_type='dict')
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self._check_axes_shape(self.plt.gcf().axes, axes_num=2, layout=(1, 2))
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with tm.assert_produces_warning(UserWarning):
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box = _check_plot_works(df.groupby('category').boxplot,
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column='height',
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return_type='dict')
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self._check_axes_shape(self.plt.gcf().axes, axes_num=4, layout=(2, 2))
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# GH 6769
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with tm.assert_produces_warning(UserWarning):
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box = _check_plot_works(df.groupby('classroom').boxplot,
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column='height', return_type='dict')
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self._check_axes_shape(self.plt.gcf().axes, axes_num=3, layout=(2, 2))
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# GH 5897
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axes = df.boxplot(column=['height', 'weight', 'category'], by='gender',
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return_type='axes')
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self._check_axes_shape(self.plt.gcf().axes, axes_num=3, layout=(2, 2))
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for ax in [axes['height']]:
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self._check_visible(ax.get_xticklabels(), visible=False)
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self._check_visible([ax.xaxis.get_label()], visible=False)
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for ax in [axes['weight'], axes['category']]:
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self._check_visible(ax.get_xticklabels())
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self._check_visible([ax.xaxis.get_label()])
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box = df.groupby('classroom').boxplot(
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column=['height', 'weight', 'category'], return_type='dict')
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self._check_axes_shape(self.plt.gcf().axes, axes_num=3, layout=(2, 2))
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with tm.assert_produces_warning(UserWarning):
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box = _check_plot_works(df.groupby('category').boxplot,
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column='height',
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layout=(3, 2), return_type='dict')
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self._check_axes_shape(self.plt.gcf().axes, axes_num=4, layout=(3, 2))
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||
|
|
with tm.assert_produces_warning(UserWarning):
|
||
|
|
box = _check_plot_works(df.groupby('category').boxplot,
|
||
|
|
column='height',
|
||
|
|
layout=(3, -1), return_type='dict')
|
||
|
|
self._check_axes_shape(self.plt.gcf().axes, axes_num=4, layout=(3, 2))
|
||
|
|
|
||
|
|
box = df.boxplot(column=['height', 'weight', 'category'], by='gender',
|
||
|
|
layout=(4, 1))
|
||
|
|
self._check_axes_shape(self.plt.gcf().axes, axes_num=3, layout=(4, 1))
|
||
|
|
|
||
|
|
box = df.boxplot(column=['height', 'weight', 'category'], by='gender',
|
||
|
|
layout=(-1, 1))
|
||
|
|
self._check_axes_shape(self.plt.gcf().axes, axes_num=3, layout=(3, 1))
|
||
|
|
|
||
|
|
box = df.groupby('classroom').boxplot(
|
||
|
|
column=['height', 'weight', 'category'], layout=(1, 4),
|
||
|
|
return_type='dict')
|
||
|
|
self._check_axes_shape(self.plt.gcf().axes, axes_num=3, layout=(1, 4))
|
||
|
|
|
||
|
|
box = df.groupby('classroom').boxplot( # noqa
|
||
|
|
column=['height', 'weight', 'category'], layout=(1, -1),
|
||
|
|
return_type='dict')
|
||
|
|
self._check_axes_shape(self.plt.gcf().axes, axes_num=3, layout=(1, 3))
|
||
|
|
|
||
|
|
@pytest.mark.slow
|
||
|
|
def test_grouped_box_multiple_axes(self):
|
||
|
|
# GH 6970, GH 7069
|
||
|
|
df = self.hist_df
|
||
|
|
|
||
|
|
# check warning to ignore sharex / sharey
|
||
|
|
# this check should be done in the first function which
|
||
|
|
# passes multiple axes to plot, hist or boxplot
|
||
|
|
# location should be changed if other test is added
|
||
|
|
# which has earlier alphabetical order
|
||
|
|
with tm.assert_produces_warning(UserWarning):
|
||
|
|
fig, axes = self.plt.subplots(2, 2)
|
||
|
|
df.groupby('category').boxplot(
|
||
|
|
column='height', return_type='axes', ax=axes)
|
||
|
|
self._check_axes_shape(self.plt.gcf().axes,
|
||
|
|
axes_num=4, layout=(2, 2))
|
||
|
|
|
||
|
|
fig, axes = self.plt.subplots(2, 3)
|
||
|
|
with tm.assert_produces_warning(UserWarning):
|
||
|
|
returned = df.boxplot(column=['height', 'weight', 'category'],
|
||
|
|
by='gender', return_type='axes', ax=axes[0])
|
||
|
|
returned = np.array(list(returned.values))
|
||
|
|
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
|
||
|
|
|
||
|
|
# draw on second row
|
||
|
|
with tm.assert_produces_warning(UserWarning):
|
||
|
|
returned = df.groupby('classroom').boxplot(
|
||
|
|
column=['height', 'weight', 'category'],
|
||
|
|
return_type='axes', ax=axes[1])
|
||
|
|
returned = np.array(list(returned.values))
|
||
|
|
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
|
||
|
|
with tm.assert_produces_warning(UserWarning):
|
||
|
|
axes = df.groupby('classroom').boxplot(ax=axes)
|
||
|
|
|
||
|
|
def test_fontsize(self):
|
||
|
|
df = DataFrame({"a": [1, 2, 3, 4, 5, 6], "b": [0, 0, 0, 1, 1, 1]})
|
||
|
|
self._check_ticks_props(df.boxplot("a", by="b", fontsize=16),
|
||
|
|
xlabelsize=16, ylabelsize=16)
|