def astype(self, dtype: AstypeArg, copy: bool = True) -> ArrayLike:
dtype = pandas_dtype(dtype)
if is_dtype_equal(dtype, self.dtype):
if copy:
return self.copy()
return self
# if we are astyping to another nullable masked dtype, we can fastpath
if isinstance(dtype, BaseMaskedDtype):
# TODO deal with NaNs for FloatingArray case
data = self._data.astype(dtype.numpy_dtype, copy=copy)
# mask is copied depending on whether the data was copied, and
# not directly depending on the `copy` keyword
mask = self._mask if data is self._data else self._mask.copy()
cls = dtype.construct_array_type()
return cls(data, mask, copy=False)
if isinstance(dtype, ExtensionDtype):
eacls = dtype.construct_array_type()
return eacls._from_sequence(self, dtype=dtype, copy=copy)
na_value: float | np.datetime64 | lib.NoDefault
# coerce
if is_float_dtype(dtype):
# In astype, we consider dtype=float to also mean na_value=np.nan
na_value = np.nan
elif is_datetime64_dtype(dtype):
na_value = np.datetime64("NaT")
else:
na_value = lib.no_default
# to_numpy will also raise, but we get somewhat nicer exception messages here
if is_integer_dtype(dtype) and self._hasna:
raise ValueError("cannot convert NA to integer")
if is_bool_dtype(dtype) and self._hasna:
# careful: astype_nansafe converts np.nan to True
raise ValueError("cannot convert float NaN to bool")
data = self.to_numpy(dtype=dtype, na_value=na_value, copy=copy)
if self.dtype.kind == "f":
# TODO: make this consistent between IntegerArray/FloatingArray,
# see test_astype_str
return astype_nansafe(data, dtype, copy=False)
return data
def astype(self, dtype: AstypeArg, copy: bool = True) -> ArrayLike:
dtype = pandas_dtype(dtype)
if is_dtype_equal(dtype, self.dtype):
if copy:
return self.copy()
return self
# if we are astyping to another nullable masked dtype, we can fastpath
if isinstance(dtype, BaseMaskedDtype):
# TODO deal with NaNs for FloatingArray case
data = self._data.astype(dtype.numpy_dtype, copy=copy)
# mask is copied depending on whether the data was copied, and
# not directly depending on the `copy` keyword
mask = self._mask if data is self._data else self._mask.copy()
cls = dtype.construct_array_type()
return cls(data, mask, copy=False)
if isinstance(dtype, ExtensionDtype):
eacls = dtype.construct_array_type()
return eacls._from_sequence(self, dtype=dtype, copy=copy)
raise NotImplementedError("subclass must implement astype to np.dtype")
