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
def memory_usage(self, deep=False):
"""
Memory usage of the values.
Parameters
----------
deep : bool, default False
Introspect the data deeply, interrogate
`object` dtypes for system-level memory consumption.
Returns
-------
bytes used
See Also
--------
numpy.ndarray.nbytes : Total bytes consumed by the elements of the
array.
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"):
# error: "ExtensionArray" has no attribute "memory_usage"
return self.array.memory_usage(
deep=deep) # type: ignore[attr-defined]
v = self.array.nbytes
if deep and is_object_dtype(self) and not PYPY:
v += lib.memory_usage_of_objects(self._values)
return v
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
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
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
def memory_usage(self, deep: bool = False) -> int:
result = self._ndarray.nbytes
if deep:
return result + lib.memory_usage_of_objects(self._ndarray)
return result
