本文整理匯總了Python中pandas.core.frame.DataFrame._get_numeric_data方法的典型用法代碼示例。如果您正苦於以下問題：Python DataFrame._get_numeric_data方法的具體用法？Python DataFrame._get_numeric_data怎麽用？Python DataFrame._get_numeric_data使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類pandas.core.frame.DataFrame的用法示例。
在下文中一共展示了DataFrame._get_numeric_data方法的1個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: boxplot
# 需要導入模塊: from pandas.core.frame import DataFrame [as 別名]
# 或者: from pandas.core.frame.DataFrame import _get_numeric_data [as 別名]
def boxplot(data, column=None, by=None, ax=None, fontsize=None,
rot=0, grid=True, figsize=None):
"""
Make a box plot from DataFrame column optionally grouped b ysome columns or
other inputs
Parameters
----------
data : DataFrame or Series
column : column name or list of names, or vector
Can be any valid input to groupby
by : string or sequence
Column in the DataFrame to group by
fontsize : int or string
Returns
-------
ax : matplotlib.axes.AxesSubplot
"""
from pandas import Series, DataFrame
if isinstance(data, Series):
data = DataFrame({'x' : data})
column = 'x'
def plot_group(grouped, ax):
keys, values = zip(*grouped)
keys = [_stringify(x) for x in keys]
ax.boxplot(values)
ax.set_xticklabels(keys, rotation=rot, fontsize=fontsize)
if column == None:
columns = None
else:
if isinstance(column, (list, tuple)):
columns = column
else:
columns = [column]
if by is not None:
if not isinstance(by, (list, tuple)):
by = [by]
fig, axes = _grouped_plot_by_column(plot_group, data, columns=columns,
by=by, grid=grid, figsize=figsize)
# Return axes in multiplot case, maybe revisit later # 985
ret = axes
else:
if ax is None:
ax = _gca()
fig = ax.get_figure()
data = data._get_numeric_data()
if columns:
cols = columns
else:
cols = data.columns
keys = [_stringify(x) for x in cols]
# Return boxplot dict in single plot case
bp = ax.boxplot(list(data[cols].values.T))
ax.set_xticklabels(keys, rotation=rot, fontsize=fontsize)
ax.grid(grid)
ret = bp
fig.subplots_adjust(bottom=0.15, top=0.9, left=0.1, right=0.9, wspace=0.2)
return ret