Forgive me if this is off topic; I haven't been following this closely and I haven't used scipy.sparse. But there are some very reasonable cases where you might want to fill sparse data with a value other than 0:
* The sparseness is missing data, and 0 is not the same as NA * Better compression: figure out which value is most common in the data and make that the default that gets filled. E.g. how many fingers a person has. Neal On Tue, Aug 27, 2019 at 3:46 PM Rok Mihevc <rok.mih...@gmail.com> wrote: > > On Tue, Aug 27, 2019 at 11:05 PM Wes McKinney <wesmck...@gmail.com> wrote: > > > I don't think this has been discussed. I think the SparseTensor > > discussions have been intended to reach compatibility with "sparse > > matrix" projects like scipy.sparse. pandas's "SparseArray" objects are > > a distinct thing -- I don't know many examples of sparse matrices with > > fill values other than 0 > > > The reason for implementing fill_value would be the case where user wants > another value to be '0' and it's practical for the SparseTensor object to > keep that value for them. I am not sure how common would such a case be and > since scipy.sparse is time tested I'd agree with compatibility as the > current goal.
