pandas.SparseArray.astype

SparseArray.astype(dtype=None, copy=True) [source]

Change the dtype of a SparseArray.

The output will always be a SparseArray. To convert to a dense ndarray with a certain dtype, use numpy.asarray().

Parameters:	dtype : np.dtype or ExtensionDtype For SparseDtype, this changes the dtype of self.sp_values and the self.fill_value. For other dtypes, this only changes the dtype of self.sp_values. copy : bool, default True Whether to ensure a copy is made, even if not necessary.
Returns:	SparseArray

Examples

>>> arr = SparseArray([0, 0, 1, 2])
>>> arr
[0, 0, 1, 2]
Fill: 0
IntIndex
Indices: array([2, 3], dtype=int32)

>>> arr.astype(np.dtype('int32'))
[0, 0, 1, 2]
Fill: 0
IntIndex
Indices: array([2, 3], dtype=int32)

Using a NumPy dtype with a different kind (e.g. float) will coerce just self.sp_values.

>>> arr.astype(np.dtype('float64'))
... # doctest: +NORMALIZE_WHITESPACE
[0, 0, 1.0, 2.0]
Fill: 0
IntIndex
Indices: array([2, 3], dtype=int32)

Use a SparseDtype if you wish to be change the fill value as well.

>>> arr.astype(SparseDtype("float64", fill_value=np.nan))
... # doctest: +NORMALIZE_WHITESPACE
[nan, nan, 1.0, 2.0]
Fill: nan
IntIndex
Indices: array([2, 3], dtype=int32)