def _map(f, arr, na_mask=False, na_value=np.nan):
if isinstance(arr, Series):
arr = arr.values
if not isinstance(arr, np.ndarray):
arr = np.asarray(arr, dtype=object)
if na_mask:
mask = isnull(arr)
try:
result = lib.map_infer_mask(arr, f, mask.view(np.uint8))
except (TypeError, AttributeError):
def g(x):
try:
return f(x)
except (TypeError, AttributeError):
return na_value
return _map(g, arr)
if na_value is not np.nan:
np.putmask(result, mask, na_value)
if result.dtype == object:
result = lib.maybe_convert_objects(result)
return result
else:
return lib.map_infer(arr, f)
def _map(f, arr, na_mask=False, na_value=np.nan, dtype=object):
from pandas.core.series import Series
if not len(arr):
return np.ndarray(0, dtype=dtype)
if isinstance(arr, Series):
arr = arr.values
if not isinstance(arr, np.ndarray):
arr = np.asarray(arr, dtype=object)
if na_mask:
mask = isnull(arr)
try:
result = lib.map_infer_mask(arr, f, mask.view(np.uint8))
except (TypeError, AttributeError):
def g(x):
try:
return f(x)
except (TypeError, AttributeError):
return na_value
return _map(g, arr, dtype=dtype)
if na_value is not np.nan:
np.putmask(result, mask, na_value)
if result.dtype == object:
result = lib.maybe_convert_objects(result)
return result
else:
return lib.map_infer(arr, f)
