I think you can use pandas or numpy to do this. I think if you;re using scipy then you should have numpy already installed (and you're probably using it now).

As an example:

# save numpy array as csv file
from numpy import asarray
from numpy import savetxt
# define data
data = asarray([[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]])
# save to csv file
savetxt('data.csv', data, delimiter=',')

Reference documentation: https://numpy.org/doc/stable/reference/generated/numpy.savetxt.html

There is a function in SciPy to convert sparse matrices and it is called todense:

import pandas as pd
from scipy.sparse.csr_matrix import todense

df = pd.DataFrame(data=todense(your_sparse_matrix_here))
df.to_csv('your_dense_matrix_name_here.csv', index=False)

Note that you may need large memory for this conversion depending on matrix dimensions.