本文整理汇总了Python中pandas.core.series.Series.hist方法的典型用法代码示例。如果您正苦于以下问题：Python Series.hist方法的具体用法？Python Series.hist怎么用？Python Series.hist使用的例子？那么, 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.core.series.Series的用法示例。
在下文中一共展示了Series.hist方法的6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: hist
# 需要导入模块: from pandas.core.series import Series [as 别名]
# 或者: from pandas.core.series.Series import hist [as 别名]
def hist(self, bins=10, **kwds):
"""
Histogram.
Parameters
----------
bins : integer, default 10
Number of histogram bins to be used
`**kwds` : optional
Additional keyword arguments are documented in
:meth:`pandas.Series.plot`.
Returns
-------
axes : :class:`matplotlib.axes.Axes` or numpy.ndarray of them
"""
return self(kind='hist', bins=bins, **kwds) 示例2: hist
# 需要导入模块: from pandas.core.series import Series [as 别名]
# 或者: from pandas.core.series.Series import hist [as 别名]
def hist(self, bins=10, **kwds):
"""
Histogram
Parameters
----------
bins: integer, default 10
Number of histogram bins to be used
`**kwds` : optional
Additional keyword arguments are documented in
:meth:`pandas.Series.plot`.
Returns
-------
axes : :class:`matplotlib.axes.Axes` or numpy.ndarray of them
"""
return self(kind='hist', bins=bins, **kwds) 示例3: _args_adjust
# 需要导入模块: from pandas.core.series import Series [as 别名]
# 或者: from pandas.core.series.Series import hist [as 别名]
def _args_adjust(self):
if is_integer(self.bins):
# create common bin edge
values = (self.data._convert(datetime=True)._get_numeric_data())
values = np.ravel(values)
values = values[~isna(values)]
hist, self.bins = np.histogram(
values, bins=self.bins,
range=self.kwds.get('range', None),
weights=self.kwds.get('weights', None))
if is_list_like(self.bottom):
self.bottom = np.array(self.bottom) 示例4: _plot
# 需要导入模块: from pandas.core.series import Series [as 别名]
# 或者: from pandas.core.series.Series import hist [as 别名]
def _plot(cls, ax, y, style=None, bins=None, bottom=0, column_num=0,
stacking_id=None, **kwds):
if column_num == 0:
cls._initialize_stacker(ax, stacking_id, len(bins) - 1)
y = y[~isna(y)]
base = np.zeros(len(bins) - 1)
bottom = bottom + \
cls._get_stacked_values(ax, stacking_id, base, kwds['label'])
# ignore style
n, bins, patches = ax.hist(y, bins=bins, bottom=bottom, **kwds)
cls._update_stacker(ax, stacking_id, n)
return patches 示例5: grouped_hist
# 需要导入模块: from pandas.core.series import Series [as 别名]
# 或者: from pandas.core.series.Series import hist [as 别名]
def grouped_hist(data, column=None, by=None, ax=None, bins=50, figsize=None,
layout=None, sharex=False, sharey=False, rot=90, grid=True,
xlabelsize=None, xrot=None, ylabelsize=None, yrot=None,
**kwargs):
"""
Grouped histogram
Parameters
----------
data : Series/DataFrame
column : object, optional
by : object, optional
ax : axes, optional
bins : int, default 50
figsize : tuple, optional
layout : optional
sharex : boolean, default False
sharey : boolean, default False
rot : int, default 90
grid : bool, default True
kwargs : dict, keyword arguments passed to matplotlib.Axes.hist
Returns
-------
axes : collection of Matplotlib Axes
"""
_raise_if_no_mpl()
_converter._WARN = False
def plot_group(group, ax):
ax.hist(group.dropna().values, bins=bins, **kwargs)
xrot = xrot or rot
fig, axes = _grouped_plot(plot_group, data, column=column,
by=by, sharex=sharex, sharey=sharey, ax=ax,
figsize=figsize, layout=layout, rot=rot)
_set_ticks_props(axes, xlabelsize=xlabelsize, xrot=xrot,
ylabelsize=ylabelsize, yrot=yrot)
fig.subplots_adjust(bottom=0.15, top=0.9, left=0.1, right=0.9,
hspace=0.5, wspace=0.3)
return axes 示例6: grouped_hist
# 需要导入模块: from pandas.core.series import Series [as 别名]
# 或者: from pandas.core.series.Series import hist [as 别名]
def grouped_hist(data, column=None, by=None, ax=None, bins=50, figsize=None,
layout=None, sharex=False, sharey=False, rot=90, grid=True,
xlabelsize=None, xrot=None, ylabelsize=None, yrot=None,
**kwargs):
"""
Grouped histogram
Parameters
----------
data: Series/DataFrame
column: object, optional
by: object, optional
ax: axes, optional
bins: int, default 50
figsize: tuple, optional
layout: optional
sharex: boolean, default False
sharey: boolean, default False
rot: int, default 90
grid: bool, default True
kwargs: dict, keyword arguments passed to matplotlib.Axes.hist
Returns
-------
axes: collection of Matplotlib Axes
"""
_raise_if_no_mpl()
_converter._WARN = False
def plot_group(group, ax):
ax.hist(group.dropna().values, bins=bins, **kwargs)
xrot = xrot or rot
fig, axes = _grouped_plot(plot_group, data, column=column,
by=by, sharex=sharex, sharey=sharey, ax=ax,
figsize=figsize, layout=layout, rot=rot)
_set_ticks_props(axes, xlabelsize=xlabelsize, xrot=xrot,
ylabelsize=ylabelsize, yrot=yrot)
fig.subplots_adjust(bottom=0.15, top=0.9, left=0.1, right=0.9,
hspace=0.5, wspace=0.3)
return axes