scipy sparse matrix: remove the rows whose all elements are zero

Question

I have a sparse matrix which is transformed from sklearn tfidfVectorier. I believe that some rows are all-zero rows. I want to remove them. However, as far as I know, the existi

Answer 1

Slicing + getnnz() does the trick:

M = M[M.getnnz(1)>0]

Works directly on csr_array. You can also remove all 0 columns without changing formats:

M = M[:,M.getnnz(0)>0]

However if you want to remove both you need

M = M[M.getnnz(1)>0][:,M.getnnz(0)>0] #GOOD

I am not sure why but

M = M[M.getnnz(1)>0, M.getnnz(0)>0] #BAD

does not work.