# Sparse Matrices

In this lesson, we will learn about different sparse matrices in Python and the conversion between sparse and dense matrices.

## We'll cover the following

# Sparse matrices in Python #

The procedure we have used so far to construct the matrix for a is not very efficient. A full matrix is created, which consists mostly of zeros with non-zero values only appearing on diagonals. There are more efficient routines that store what are called **sparse matrices**. In a sparse matrix, only the value and location of non-zero values in a matrix are stored. Functionality for sparse matrices is available in the `scipy`

submodule `sparse`

.

We will import the

`scipy.sparse`

submodule as`sp`

.

```
import scipy.sparse as sp
```

# Dense to sparse #

When we create a sparse matrix, we have to choose which format it should be stored in. There are many ways to store a sparse matrix. Two most commonly used are:

*compressed sparse column*using the`csc_matrix(A)`

method.*compressed sparse row*using the`csr_matrix(A)`

method.

The following matrix is an example of this:

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