NumPy

• It's a popular library of Python.
• Its abbreviation is Numerical Python.
• The purpose of the NumPy library is to do scientific computation and apply them to Python applications.
• It is fast because it is written in C and Python.
• In Python, there are no built-in array capabilities.
• NumPy can be used over lists.

NumPy Features

• A durable N-dimensional array.
• Tools to manipulate and work with the array.
• Perform mathematical and logical operations on the array.
• Powerful predefined functions.

NumPy vs List

• NumPy arrays consume less memory.
• Operations complete quickly in NumPy.
• NumPy arrays have a fixed type, which saves time on type checking during execution.

Applications of NumPy

• It can be used for mathematical operations.
• For backend code, NumPy is important because Pandas and NumPy work well together.
• Helps in plotting while using the Matplotlib library.
• An important part of machine learning and data science algorithms.

import numpy as np

# simple code 

a = np.array([1,2,3])

#We can do anything add, sum, division, mean, median, etc.
np.sum([3,2])
np.subtract([1,2])