def _isna_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 = libmissing.isnaobj_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):
result = obj._constructor(result, index=obj.index, name=obj.name, copy=False)
return result
def _get_dtype_cmp_class(dtype):
if is_numeric_dtype(dtype) or is_bool_dtype(dtype):
return "numeric"
if is_string_like_dtype(dtype) or is_categorical_dtype(dtype):
return "string"
if is_datetime64_any_dtype(dtype):
return "datetime"
return "other"
def _isna_string_dtype(values: np.ndarray, dtype: np.dtype, old: bool) -> np.ndarray:
# 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)
if old:
vec = libmissing.isnaobj_old(values.ravel())
else:
vec = libmissing.isnaobj(values.ravel())
result[...] = vec.reshape(shape)
return result
def _isna_ndarraylike(obj):
is_extension = is_extension_array_dtype(obj)
if not is_extension:
# Avoid accessing `.values` on things like
# PeriodIndex, which may be expensive.
values = getattr(obj, "_values", obj)
else:
values = obj
dtype = values.dtype
if is_extension:
if isinstance(obj, (ABCIndexClass, ABCSeries)):
values = obj._values
else:
values = obj
result = values.isna()
elif isinstance(obj, ABCDatetimeArray):
return obj.isna()
elif is_string_dtype(dtype):
# Working around NumPy ticket 1542
shape = values.shape
if is_string_like_dtype(dtype):
# object array of strings
result = np.zeros(values.shape, dtype=bool)
else:
# object array of non-strings
result = np.empty(shape, dtype=bool)
vec = libmissing.isnaobj(values.ravel())
result[...] = vec.reshape(shape)
elif needs_i8_conversion(dtype):
# this is the NaT pattern
result = values.view("i8") == iNaT
else:
result = np.isnan(values)
# box
if isinstance(obj, ABCSeries):
result = obj._constructor(result,
index=obj.index,
name=obj.name,
copy=False)
return result
def test_is_string_like_dtype():
assert not com.is_string_like_dtype(object)
assert not com.is_string_like_dtype(pd.Series([1, 2]))
assert com.is_string_like_dtype(str)
assert com.is_string_like_dtype(np.array(['a', 'b']))
def test_is_string_like_dtype():
assert not com.is_string_like_dtype(object)
assert not com.is_string_like_dtype(pd.Series([1, 2]))
assert com.is_string_like_dtype(str)
assert com.is_string_like_dtype(np.array(['a', 'b']))
