How to Work With Sparse Data

SciPy - Interview Questions

SciPy has a module, scipy.sparse that provides functions to deal with sparse data. There are two types of sparse matrices that we use :

CSC : Compressed Sparse Column. For efficient arithmetic, fast column slicing.

CSR : Compressed Sparse Row. For fast row slicing, faster matrix vector products

CSR Matrix : We can create CSR matrix by passing an arrray into function scipy.sparse.csr_matrix().

Create a CSR matrix from an array :

import numpy as np
from scipy.sparse import csr_matrix
arr = np.array([0, 0, 0, 0, 0, 1, 1, 0, 2])
print(csr_matrix(arr))

Output :

(0, 5) 1
(0, 6) 1
(0, 8) 2