What is NumPy?
According to Wikipedia -
NumPy is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays.

Install NumPy a) If you already have Anaconda installed in your PC, then NumPy might be pre-installed in it or simply install it by running -
conda install numpy
b) If you have pip installed in your PC, then run -
python -m pip install — user numpy

Import the Library
import numpy as np
You can also give other name instead of np.

Create Arrays and change elements of array
a) 1D Array
arr1 = np.array([1,2,3,4,5,6])
b) Higher Dimension Array
arr2 = np.array([[1,2,3],[4,5,6]])
c) Change an element of Array
arr1[1] = 22 # [1,22,3,4,5,6]
arr2[1][1] = 56 # [[1,2,3],[4,56,6]]
d) Create a matrix/array with all its elements zero
arr3 = np.zeros(3) # creates an array of 3 elements
arr4 = np.zeros((2,3)) # creates a matrix of 2 rows and 3 columns
e) Create an Identity Matrix
arr5 = np.eye(4) #creates a 4X4 identity matrix
f) Creates a matrix/array with all its elements one
arr6 = np.ones((3,4)) # creates an array of 3 rows and 4 columns
g) Creates a evenly spaced numbers over a specified interval
arr7 = np.linspace(start = 0, stop = 5, num = 10, endpoint = True)# creates an array of 10 elements with evenly spaced numbers from 0 to 5 (including 5).

Array of Random Numbers
np.random.rand(5) # creates an array of 5 random numbers from 0 to 1
np.random.randn(5,5) # creates a 5X5 matrix of random numbers from -1 to # 1
np.random.randint(1,100) # returns a number between 1 and 100
np.random.randint(1,100,10) # returns an array of 10 numbers between 1 and 100
arr = np.arange(25) # returns an array of 25 elements from 0 to 25 (exclusive)

Indexing
arr[8] # returns element at 8th index
arr[1:5] # returns elements of 1st to 5th (excluding) index
arr2d[0][0] # returns element at 0th row and 0th column
arr2d[:2,1:]

Operations
arr-arr
arr+5
arr*arr
1/arr # ensure that none of the elements has value zero
np.sqrt(arr)
np.exp(arr)
np.sin(arr)
np.log(arr)

Other functions
arr.max() # returns maximum element of array
arr.min() # returns minimum element of array
arr.argmax() # returns index of maximum element
arr.argmin() # returns index of minimum element
arr.shape() # returns the shape of array
arr.dtype() # returns the type of array
arr1 = arr.copy() # initialises a copy of arr array to arr1