This has confused me for a while, but we apparently (sometimes?) allow a fill_value whose dtype is not the same as sp_values.dtype

In [20]: a = pd.SparseArray([1, 2, 3], fill_value=1.0) In [21]: a Out[21]: [1.0, 2, 3] Fill: 1.0 IntIndex Indices: array([1, 2], dtype=int32) In [22]: a.sp_values.dtype Out[22]: dtype('int64')

This can lead to confusing behavior when doing operations.

I suspect a primary motivation was supporting sparse integer values with NaN for a fill value. We should investigate what's tested, part of the API, and useful to users.