NumPy Introduction

What is NumPy?

NumPy is a Python library used for handling arrays.

It also has functions that work in the fields of linear algebra, Fourier transforms, and matrices.

NumPy was created by Travis Oliphant in 2005. It is an open-source project that you can use freely.

NumPy refers to Numerical Python.

Why use NumPy?

In Python, we have lists that meet the array function, but they are slow to process.

NumPy aims to provide an array object that is 50 times faster than traditional Python lists.

The array objects in NumPy are called ndarray, which provides many support functions to make it easy to use ndarray Very easy.

Arrays are very commonly used in data science because speed and resources are very important.

Data Science:A branch of computer science that studies how to store, use, and analyze data to extract information from it.

Why is NumPy faster than lists?

Unlike lists, NumPy arrays are stored in a continuous position in memory, so processes can access and manipulate them very efficiently.

This behavior is called the locality of reference in computer science.

This is the main reason why NumPy is faster than lists. It is also optimized to work with the latest CPU architectures.

What language is NumPy written in?

NumPy is a Python library, part of which is written in Python, but most of the parts that require fast computation are written in C or C++.

Where is the NumPy codebase?

The source code of NumPy is located in this github repository:https://github.com/numpy/numpy

github: Allows many people to work on the same codebase.