本文整理汇总了Python中pandas._libs.lib.memory_usage_of_objects方法的典型用法代码示例。如果您正苦于以下问题：Python lib.memory_usage_of_objects方法的具体用法？Python lib.memory_usage_of_objects怎么用？Python lib.memory_usage_of_objects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._libs.lib的用法示例。
在下文中一共展示了lib.memory_usage_of_objects方法的4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: memory_usage
# 需要导入模块: from pandas._libs import lib [as 别名]
# 或者: from pandas._libs.lib import memory_usage_of_objects [as 别名]
def memory_usage(self, deep=False):
"""
Memory usage of the values
Parameters
----------
deep : bool
Introspect the data deeply, interrogate
`object` dtypes for system-level memory consumption
Returns
-------
bytes used
See Also
--------
numpy.ndarray.nbytes
Notes
-----
Memory usage does not include memory consumed by elements that
are not components of the array if deep=False or if used on PyPy
"""
if hasattr(self.array, 'memory_usage'):
return self.array.memory_usage(deep=deep)
v = self.array.nbytes
if deep and is_object_dtype(self) and not PYPY:
v += lib.memory_usage_of_objects(self.array)
return v 示例2: memory_usage
# 需要导入模块: from pandas._libs import lib [as 别名]
# 或者: from pandas._libs.lib import memory_usage_of_objects [as 别名]
def memory_usage(self, deep=False):
values = self.sp_values
v = values.nbytes
if deep and is_object_dtype(self) and not PYPY:
v += lib.memory_usage_of_objects(values)
return v 示例3: memory_usage
# 需要导入模块: from pandas._libs import lib [as 别名]
# 或者: from pandas._libs.lib import memory_usage_of_objects [as 别名]
def memory_usage(self, deep=False):
"""
Memory usage of the values
Parameters
----------
deep : bool
Introspect the data deeply, interrogate
`object` dtypes for system-level memory consumption
Returns
-------
bytes used
Notes
-----
Memory usage does not include memory consumed by elements that
are not components of the array if deep=False or if used on PyPy
See Also
--------
numpy.ndarray.nbytes
"""
if hasattr(self.values, 'memory_usage'):
return self.values.memory_usage(deep=deep)
v = self.values.nbytes
if deep and is_object_dtype(self) and not PYPY:
v += lib.memory_usage_of_objects(self.values)
return v 示例4: memory_usage
# 需要导入模块: from pandas._libs import lib [as 别名]
# 或者: from pandas._libs.lib import memory_usage_of_objects [as 别名]
def memory_usage(self, deep=False):
"""
Memory usage of my values
Parameters
----------
deep : bool
Introspect the data deeply, interrogate
`object` dtypes for system-level memory consumption
Returns
-------
bytes used
Notes
-----
Memory usage does not include memory consumed by elements that
are not components of the array if deep=False or if used on PyPy
See Also
--------
numpy.ndarray.nbytes
"""
if hasattr(self.values, 'memory_usage'):
return self.values.memory_usage(deep=deep)
v = self.values.nbytes
if deep and is_object_dtype(self) and not PYPY:
v += lib.memory_usage_of_objects(self.values)
return v