I have created a CSR matrix using *scipy.sparse.csr_matrix* and the elements in the matrix are either 0 or 1. The matrix is very sparse and big. Is there any way to count how many matrix elements have value 1?

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There are several ways to count number of 1's in your CSR matrix, but the quickest way is to use **__getattr__**

Example:

>>> X.toarray()

array([[0, 1, 0, 0, 1],

[1, 0, 0, 0, 0],

[0, 0, 1, 1, 1],

[1, 0, 0, 1, 0],

[0, 0, 0, 0, 1],

[0, 1, 1, 1, 0],

[1, 0, 0, 0, 0]], dtype=int8)

>>> print(X.__getattr__)

<bound method spmatrix.__getattr__ of <7x5 sparse matrix of type '<class 'numpy.int8'>'

with 13 stored elementsin Compressed Sparse Row format>>

Another approach: You can convert the matrix to COOrdinate format using** tocoo() **function and then check the length.

>>> X_1 = (X == 1)

>>> X_1

<7x5 sparse matrix of type '<class 'numpy.bool_'>'

with 13 stored elements in Compressed Sparse Row format>

>>> co=X_1.tocoo()

>>> co

<7x5 sparse matrix of type '<class 'numpy.bool_'>'

with 13 stored elements in COOrdinate format>

>>> m=set(zip(co.row,co.col))

>>> len(m)

13