本文整理汇总了Python中pandas.plotting._core.grouped_hist方法的典型用法代码示例。如果您正苦于以下问题：Python _core.grouped_hist方法的具体用法？Python _core.grouped_hist怎么用？Python _core.grouped_hist使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类pandas.plotting._core的用法示例。
在下文中一共展示了_core.grouped_hist方法的2个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: test_grouped_hist_legacy
# 需要导入模块: from pandas.plotting import _core [as 别名]
# 或者: from pandas.plotting._core import grouped_hist [as 别名]
def test_grouped_hist_legacy(self):
from matplotlib.patches import Rectangle
df = DataFrame(randn(500, 2), columns=['A', 'B'])
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
if _mpl_ge_2_2_0():
kwargs = {"density": True}
else:
kwargs = {"normed": True}
axes = grouped_hist(df.A, by=df.C, cumulative=True,
bins=4, xlabelsize=xf, xrot=xrot,
ylabelsize=yf, yrot=yrot, **kwargs)
# 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')
with tm.assert_produces_warning(FutureWarning):
df.hist(by='C', figsize='default') 示例2: test_grouped_hist_legacy
# 需要导入模块: from pandas.plotting import _core [as 别名]
# 或者: from pandas.plotting._core import grouped_hist [as 别名]
def test_grouped_hist_legacy(self):
from matplotlib.patches import Rectangle
df = DataFrame(randn(500, 2), columns=['A', 'B'])
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, normed=True, cumulative=True,
bins=4, xlabelsize=xf, xrot=xrot,
ylabelsize=yf, yrot=yrot)
# 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')
with tm.assert_produces_warning(FutureWarning):
df.hist(by='C', figsize='default')