def _isnull_old(obj):
'''
Detect missing values. Treat None, NaN, INF, -INF as null.
Parameters
----------
arr: ndarray or object value
Returns
-------
boolean ndarray or boolean
'''
if lib.isscalar(obj):
return lib.checknull_old(obj)
from pandas.core.generic import PandasObject
if isinstance(obj, np.ndarray):
return _isnull_ndarraylike_old(obj)
elif isinstance(obj, PandasObject):
# TODO: optimize for DataFrame, etc.
return obj.apply(_isnull_old)
elif isinstance(obj, list) or hasattr(obj, '__array__'):
return _isnull_ndarraylike_old(obj)
else:
return obj is None
def _isnull_old(obj):
'''
Detect missing values. Treat None, NaN, INF, -INF as null.
Parameters
----------
arr: ndarray or object value
Returns
-------
boolean ndarray or boolean
'''
if lib.isscalar(obj):
return lib.checknull_old(obj)
from pandas.core.generic import PandasObject
if isinstance(obj, np.ndarray):
return _isnull_ndarraylike_old(obj)
elif isinstance(obj, PandasObject):
# TODO: optimize for DataFrame, etc.
return obj.apply(_isnull_old)
elif isinstance(obj, list) or hasattr(obj, '__array__'):
return _isnull_ndarraylike_old(obj)
else:
return obj is None
def isnull_old(obj):
'''
Replacement for numpy.isnan / -numpy.isfinite which is suitable
for use on object arrays. Treat None, NaN, INF, -INF as null.
Parameters
----------
arr: ndarray or object value
Returns
-------
boolean ndarray or boolean
'''
if lib.isscalar(obj):
return lib.checknull_old(obj)
from pandas.core.generic import PandasObject
if isinstance(obj, np.ndarray):
return _isnull_ndarraylike_old(obj)
elif isinstance(obj, PandasObject):
# TODO: optimize for DataFrame, etc.
return obj.apply(isnull_old)
elif isinstance(obj, list) or hasattr(obj, '__array__'):
return _isnull_ndarraylike_old(obj)
else:
return obj is None
def isnull_old(obj):
"""
Replacement for numpy.isnan / -numpy.isfinite which is suitable
for use on object arrays. Treat None, NaN, INF, -INF as null.
Parameters
----------
arr: ndarray or object value
Returns
-------
boolean ndarray or boolean
"""
if lib.isscalar(obj):
return lib.checknull_old(obj)
from pandas.core.generic import PandasObject
if isinstance(obj, np.ndarray):
return _isnull_ndarraylike_old(obj)
elif isinstance(obj, PandasObject):
# TODO: optimize for DataFrame, etc.
return obj.apply(isnull_old)
elif isinstance(obj, list) or hasattr(obj, "__array__"):
return _isnull_ndarraylike_old(obj)
else:
return obj is None
def _isnull_old(obj):
"""Detect missing values. Treat None, NaN, INF, -INF as null.
Parameters
----------
arr: ndarray or object value
Returns
-------
boolean ndarray or boolean
"""
if is_scalar(obj):
return lib.checknull_old(obj)
# hack (for now) because MI registers as ndarray
elif isinstance(obj, ABCMultiIndex):
raise NotImplementedError("isnull is not defined for MultiIndex")
elif isinstance(obj, (ABCSeries, np.ndarray, ABCIndexClass)):
return _isnull_ndarraylike_old(obj)
elif isinstance(obj, ABCGeneric):
return obj._constructor(obj._data.isnull(func=_isnull_old))
elif isinstance(obj, list) or hasattr(obj, '__array__'):
return _isnull_ndarraylike_old(np.asarray(obj))
else:
return obj is None
def _isnull_old(obj):
"""Detect missing values. Treat None, NaN, INF, -INF as null.
Parameters
----------
arr: ndarray or object value
Returns
-------
boolean ndarray or boolean
"""
if is_scalar(obj):
return lib.checknull_old(obj)
# hack (for now) because MI registers as ndarray
elif isinstance(obj, ABCMultiIndex):
raise NotImplementedError("isnull is not defined for MultiIndex")
elif isinstance(obj, (ABCSeries, np.ndarray, ABCIndexClass)):
return _isnull_ndarraylike_old(obj)
elif isinstance(obj, ABCGeneric):
return obj._constructor(obj._data.isnull(func=_isnull_old))
elif isinstance(obj, list) or hasattr(obj, '__array__'):
return _isnull_ndarraylike_old(np.asarray(obj))
else:
return obj is None
