def _isnull_ndarraylike_old(obj): values = getattr(obj, 'values', obj) dtype = values.dtype if is_string_dtype(dtype): # Working around NumPy ticket 1542 shape = values.shape if is_string_like_dtype(dtype): result = np.zeros(values.shape, dtype=bool) else: result = np.empty(shape, dtype=bool) vec = lib.isnullobj_old(values.ravel()) result[:] = vec.reshape(shape) elif dtype in _DATELIKE_DTYPES: # this is the NaT pattern result = values.view('i8') == iNaT else: result = ~np.isfinite(values) # box if isinstance(obj, ABCSeries): from pandas import Series result = Series(result, index=obj.index, name=obj.name, copy=False) return result
def _isnull_ndarraylike_old(obj): values = getattr(obj, 'values', obj) dtype = values.dtype if is_string_dtype(dtype): # Working around NumPy ticket 1542 shape = values.shape if is_string_like_dtype(dtype): result = np.zeros(values.shape, dtype=bool) else: result = np.empty(shape, dtype=bool) vec = lib.isnullobj_old(values.ravel()) result[:] = vec.reshape(shape) elif is_datetime64_dtype(dtype): # this is the NaT pattern result = values.view('i8') == iNaT else: result = ~np.isfinite(values) # box if isinstance(obj, ABCSeries): from pandas import Series result = Series(result, index=obj.index, name=obj.name, copy=False) return result
def _isnull_ndarraylike_old(obj): from pandas import Series values = np.asarray(obj) if values.dtype.kind in ('O', 'S', 'U'): # Working around NumPy ticket 1542 shape = values.shape if values.dtype.kind in ('S', 'U'): result = np.zeros(values.shape, dtype=bool) else: result = np.empty(shape, dtype=bool) vec = lib.isnullobj_old(values.ravel()) result[:] = vec.reshape(shape) if isinstance(obj, Series): result = Series(result, index=obj.index, copy=False) elif values.dtype == np.dtype('M8[ns]'): # this is the NaT pattern result = values.view('i8') == tslib.iNaT else: result = -np.isfinite(obj) return result