The formula C=numpy.add(A, B) adds the two matrices A and B and stores the result in C. • To subtract matrix B from matrix A, enter C=numpy.subtract(A, B). The result is stored in C. • C=numpy.divide(A, B): Split matrix A into two equal parts and store the result in C. • C stands for numpy. multiply(A, B): Multiply matrices A and B, then store the result in matrices C. • C=numpy.sum(A): Calculate the sum of each element in the matrix A, then store the result in c R. • C=numpy.sum(A, axis = 0): Create a vector C by adding the columns of the matrix A. • C=numpy.sum(A, axis = 1): Summarize matrix A row-by-row and store the result in the vector C. Create Python code that demonstrates the use of these techniques in a sample matrix.

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Array

The simplest way to start thinking about an array is as a collection, or a set of elements. In programming, these elements may be constants, variables, functions and pointers.