#### Here are two approaches to convert Pandas DataFrame to a **NumPy** **array**: (1) First approach: df.to_numpy() (2) Second approach: df.values Note that the recommended approach is df.to_numpy(). Steps to Convert Pandas DataFrame to a **NumPy** **Array** Step 1: Create a DataFrame. To start with a simple example, let's create a DataFrame with 3 columns. A dense **matrix** stored in a **NumPy array** can be converted into a sparse **matrix** using the CSR representation by calling the csr_**matrix**() function. In the example below, we define a 3 x 6 sparse **matrix** as a dense **array**, convert it to a CSR sparse representation, and then convert it back to a dense **array** by calling the todense() function. The bsr sparse **matrix** representation has the following structure: data: a K Ã— R Ã— C **matrix**, where K is the number of blocks, and R and C are dimensions of each block. indices: length K **array**.

**NumPy**

**matrix**multiplication can be done by the following three methods. multiply(): element-wise

**matrix**multiplication. matmul():

**matrix**product of two

**arrays**. dot(): dot product of two

**arrays**. 1.

**NumPy**

**Matrix**Multiplication Element Wise. If you want element-wise

**matrix**multiplication, you can use multiply() function. Parameters. indices (

**array**_like) - Initial data for the tensor.Can be a list, tuple,

**NumPy**ndarray, scalar, and other types.Will be cast to a torch.LongTensor internally. The indices are the coordinates of the non-zero values in the

**matrix**, and thus should be two-dimensional where the first dimension is the number of tensor dimensions and the second dimension is the number of. To create a

**coo**_

**matrix**we need 3 one-dimensional

**numpy arrays**. The first

**array**represents the row indices, the second

**array**represents column indices and the third

**array**represents non-zero data in the element. The row and column indices specify the location of non-zero element and the data

**array**specifies the actual non-zero data in it.