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ENH/BUG: boxplot now supports layout #7035

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2 changes: 2 additions & 0 deletions doc/source/release.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -332,6 +332,7 @@ Improvements to existing features
- Arrays of strings can be wrapped to a specified width (``str.wrap``) (:issue:`6999`)
- ``GroupBy.count()`` is now implemented in Cython and is much faster for large
numbers of groups (:issue:`7016`).
- ``boxplot`` now supports ``layout`` keyword (:issue:`6769`)

.. _release.bug_fixes-0.14.0:

Expand Down Expand Up @@ -485,6 +486,7 @@ Bug Fixes
- Bug in cache coherence with chained indexing and slicing; add ``_is_view`` property to ``NDFrame`` to correctly predict
views; mark ``is_copy`` on ``xs` only if its an actual copy (and not a view) (:issue:`7084`)
- Bug in DatetimeIndex creation from string ndarray with ``dayfirst=True`` (:issue:`5917`)
- Bug in ``boxplot`` and ``hist`` draws unnecessary axes (:issue:`6769`)

pandas 0.13.1
-------------
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2 changes: 2 additions & 0 deletions doc/source/v0.14.0.txt
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Original file line number Diff line number Diff line change
Expand Up @@ -390,6 +390,8 @@ Plotting
positional argument ``frame`` instead of ``data``. A ``FutureWarning`` is
raised if the old ``data`` argument is used by name. (:issue:`6956`)

- ``boxplot`` now supports ``layout`` keyword (:issue:`6769`)

.. _whatsnew_0140.prior_deprecations:

Prior Version Deprecations/Changes
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148 changes: 117 additions & 31 deletions pandas/tests/test_graphics.py
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Expand Up @@ -13,6 +13,7 @@
from pandas.compat import range, lrange, StringIO, lmap, lzip, u, zip
import pandas.util.testing as tm
from pandas.util.testing import ensure_clean
import pandas.core.common as com
from pandas.core.config import set_option


Expand Down Expand Up @@ -1837,6 +1838,19 @@ def test_errorbar_scatter(self):

@tm.mplskip
class TestDataFrameGroupByPlots(tm.TestCase):

def setUp(self):
n = 100
with tm.RNGContext(42):
gender = tm.choice(['Male', 'Female'], size=n)
classroom = tm.choice(['A', 'B', 'C'], size=n)

self.hist_df = DataFrame({'gender': gender,
'classroom': classroom,
'height': random.normal(66, 4, size=n),
'weight': random.normal(161, 32, size=n),
'category': random.randint(4, size=n)})

def tearDown(self):
tm.close()

Expand Down Expand Up @@ -1924,39 +1938,117 @@ def test_grouped_hist(self):
with tm.assertRaises(AttributeError):
plotting.grouped_hist(df.A, by=df.C, foo='bar')

def _check_axes_shape(self, axes, axes_num=None, layout=None, figsize=(8.0, 6.0)):
"""
Check expected number of axes is drawn in expected layout

Parameters
----------
axes : matplotlib Axes object, or its list-like
axes_num : number
expected number of axes. Unnecessary axes should be set to invisible.
layout : tuple
expected layout
figsize : tuple
expected figsize. default is matplotlib default
"""
visible_axes = self._flatten_visible(axes)

if axes_num is not None:
self.assertEqual(len(visible_axes), axes_num)
for ax in visible_axes:
# check something drawn on visible axes
self.assert_(len(ax.get_children()) > 0)

if layout is not None:
if isinstance(axes, list):
self.assertEqual((len(axes), ), layout)
elif isinstance(axes, np.ndarray):
self.assertEqual(axes.shape, layout)
else:
# in case of AxesSubplot
self.assertEqual((1, ), layout)

self.assert_numpy_array_equal(np.round(visible_axes[0].figure.get_size_inches()),
np.array(figsize))

def _flatten_visible(self, axes):
axes = plotting._flatten(axes)
axes = [ax for ax in axes if ax.get_visible()]
return axes

@slow
def test_grouped_hist_layout(self):
def test_grouped_box_layout(self):
import matplotlib.pyplot as plt
n = 100
gender = tm.choice(['Male', 'Female'], size=n)
df = DataFrame({'gender': gender,
'height': random.normal(66, 4, size=n),
'weight': random.normal(161, 32, size=n),
'category': random.randint(4, size=n)})
self.assertRaises(ValueError, df.hist, column='weight', by=df.gender,
df = self.hist_df

self.assertRaises(ValueError, df.boxplot, column=['weight', 'height'], by=df.gender,
layout=(1, 1))
self.assertRaises(ValueError, df.boxplot, column=['height', 'weight', 'category'],
layout=(2, 1))

box = _check_plot_works(df.groupby('gender').boxplot, column='height')
self._check_axes_shape(plt.gcf().axes, axes_num=2)

box = _check_plot_works(df.groupby('category').boxplot, column='height')
self._check_axes_shape(plt.gcf().axes, axes_num=4)

# GH 6769
box = _check_plot_works(df.groupby('classroom').boxplot, column='height')
self._check_axes_shape(plt.gcf().axes, axes_num=3)

box = df.boxplot(column=['height', 'weight', 'category'], by='gender')
self._check_axes_shape(plt.gcf().axes, axes_num=3)

box = df.groupby('classroom').boxplot(column=['height', 'weight', 'category'])
self._check_axes_shape(plt.gcf().axes, axes_num=3)

box = _check_plot_works(df.groupby('category').boxplot, column='height', layout=(3, 2))
self._check_axes_shape(plt.gcf().axes, axes_num=4)

box = df.boxplot(column=['height', 'weight', 'category'], by='gender', layout=(4, 1))
self._check_axes_shape(plt.gcf().axes, axes_num=3)

box = df.groupby('classroom').boxplot(column=['height', 'weight', 'category'], layout=(1, 4))
self._check_axes_shape(plt.gcf().axes, axes_num=3)

@slow
def test_grouped_hist_layout(self):

df = self.hist_df
self.assertRaises(ValueError, df.hist, column='weight', by=df.gender,
layout=(1,))
layout=(1, 1))
self.assertRaises(ValueError, df.hist, column='height', by=df.category,
layout=(1, 3))
self.assertRaises(ValueError, df.hist, column='height', by=df.category,
layout=(2, 1))
self.assertEqual(df.hist(column='height', by=df.gender,
layout=(2, 1)).shape, (2,))
tm.close()
self.assertEqual(df.hist(column='height', by=df.category,
layout=(4, 1)).shape, (4,))
tm.close()
self.assertEqual(df.hist(column='height', by=df.category,
layout=(4, 2)).shape, (4, 2))

axes = _check_plot_works(df.hist, column='height', by=df.gender, layout=(2, 1))
self._check_axes_shape(axes, axes_num=2, layout=(2, ), figsize=(10, 5))

axes = _check_plot_works(df.hist, column='height', by=df.category, layout=(4, 1))
self._check_axes_shape(axes, axes_num=4, layout=(4, ), figsize=(10, 5))

axes = _check_plot_works(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))

# GH 6769
axes = _check_plot_works(df.hist, column='height', by='classroom', layout=(2, 2))
self._check_axes_shape(axes, axes_num=3, layout=(2, 2), figsize=(10, 5))

# without column
axes = _check_plot_works(df.hist, by='classroom')
self._check_axes_shape(axes, axes_num=3, layout=(2, 2), figsize=(10, 5))

axes = _check_plot_works(df.hist, by='gender', layout=(3, 5))
self._check_axes_shape(axes, axes_num=2, layout=(3, 5), figsize=(10, 5))

axes = _check_plot_works(df.hist, column=['height', 'weight', 'category'])
self._check_axes_shape(axes, axes_num=3, layout=(2, 2), figsize=(10, 5))

@slow
def test_axis_share_x(self):
df = self.hist_df
# GH4089
n = 100
df = DataFrame({'gender': tm.choice(['Male', 'Female'], size=n),
'height': random.normal(66, 4, size=n),
'weight': random.normal(161, 32, size=n)})
ax1, ax2 = df.hist(column='height', by=df.gender, sharex=True)

# share x
Expand All @@ -1969,10 +2061,7 @@ def test_axis_share_x(self):

@slow
def test_axis_share_y(self):
n = 100
df = DataFrame({'gender': tm.choice(['Male', 'Female'], size=n),
'height': random.normal(66, 4, size=n),
'weight': random.normal(161, 32, size=n)})
df = self.hist_df
ax1, ax2 = df.hist(column='height', by=df.gender, sharey=True)

# share y
Expand All @@ -1985,10 +2074,7 @@ def test_axis_share_y(self):

@slow
def test_axis_share_xy(self):
n = 100
df = DataFrame({'gender': tm.choice(['Male', 'Female'], size=n),
'height': random.normal(66, 4, size=n),
'weight': random.normal(161, 32, size=n)})
df = self.hist_df
ax1, ax2 = df.hist(column='height', by=df.gender, sharex=True,
sharey=True)

Expand Down
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