# Matrix manipulation in Python

We can easily perform matrix manipulation in Python using the Numpy library. NumPy is a Python package. It stands for 'Numerical Python'. It is a library consisting of multidimensional array objects and a collection of routines for processing of array. Using NumPy, mathematical and logical operations on arrays can be performed.

## Install and Import Numpy

To install Numpy, use pip −

pip install numpy


Import Numpy −

import numpy


## Add, Subtract, Divide and Multiply matrices

We will use the following Numpy methods for matrix manipulations −

• numpy.subtract() − Subtract two matrices

• numpy.divide() − Divide two matrices

• numpy.multiply() − Multiply two matrices

Let us now see the code −

### Example

import numpy as np

# Two matrices
mx1 = np.array([[5, 10], [15, 20]])
mx2 = np.array([[25, 30], [35, 40]])

print("Matrix1 =\n",mx1)
print("\nMatrix2 =\n",mx2)

print ("\nAddition of two matrices: ")

# The subtract() is used to subtract matrices
print ("\nSubtraction of two matrices: ")
print (np.subtract(mx1,mx2))

# The divide() is used to divide matrices
print ("\nMatrix Division: ")
print (np.divide(mx1,mx2))

# The multiply()is used to multiply matrices
print ("\nMultiplication of two matrices: ")
print (np.multiply(mx1,mx2))


### Output

Matrix1 =
[[ 5 10]
[15 20]]

Matrix2 =
[[25 30]
[35 40]]

[[30 40]
[50 60]]

Subtraction of two matrices:
[[-20 -20]
[-20 -20]]

Matrix Division:
[[0.2 0.33333333]
[0.42857143 0.5 ]]

Multiplication of two matrices:
[[125 300]
[525 800]]


## Summation of matrix elements

The sum() method is used to find the summation −

### Example

import numpy as np

# A matrix
mx = np.array([[5, 10], [15, 20]])

print("Matrix =\n",mx)

print ("\nThe summation of elements=")
print (np.sum(mx))

print ("\nThe column wise summation=")
print (np.sum(mx,axis=0))

print ("\nThe row wise summation=")
print (np.sum(mx,axis=1))


### Output

Matrix =
[[ 5 10]
[15 20]]

The summation of elements=
50

The column wise summation=
[20 30]

The row wise summation=
[15 35]


## Transpose a Matrix

The .T property is used to find the Transpose of a Matrix −

### Example

import numpy as np

# A matrix
mx = np.array([[5, 10], [15, 20]])

print("Matrix =\n",mx)

print ("\nThe Transpose =")
print (mx.T)


### Output

Matrix =
[[ 5 10]
[15 20]]

The Transpose =
[[ 5 15]
[10 20]]