Returns result csc_matrix, csr_matrix, bsr_matrix, dia_matrix or coo_matrix. And it is a great sanity check. array ([[1, 0, 2, 0, 3], [0, 4, 0, 5, 0]])) print (x) < 2 x5 sparse matrix of type '' with 5 stored elements in Compressed Sparse Row format > One of the most common things that you might want to do is to make a conditional selection from the matrix … python scipy sparse-matrix  Share. SciPy has a module, scipy.sparse that provides functions to deal with sparse data. For fast row slicing, faster matrix vector products. These examples are extracted from open source projects. Also known as the ‘ijv’ or ‘triplet’ format. When you work with sparse matrix data structure with SciPy in Python, sometimes you might want to visualize the sparse matrix. CSR - Compressed Sparse Row. There are 7 data structures for storing sparse matrices in SciPy: bsr_matrix: Block Sparse Row matrix; coo_matrix: COOrdinate format matrix Let’s say that you have a sparse matrix: import numpy as np from scipy.sparse import x = csr_matrix (np. Parameters file str or file-like object. Davide Fiocco. Many linear algebra NumPy and SciPy functions that operate on NumPy arrays can transparently operate on SciPy sparse arrays. SciPy 2-D sparse matrix package for numeric data is scipy.sparse. scipy.sparse.coo_matrix¶ class scipy.sparse.coo_matrix (arg1, shape = None, dtype = None, copy = False) [source] ¶ A sparse matrix in COOrdinate format.