Introduction | Getting into NumPy Basics
Getting into NumPy Basics

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Getting into NumPy Basics

# Introduction

## What is NumPy?

`NumPy` is a library for the Python programming language, designed for handling large, multi-dimensional arrays and matrices of numerical data. It plays a crucial role in scientific computing within Python and finds extensive use across various fields, including machine learning, data science, and scientific computing.

The library offers a vast array of functions and tools specifically for managing large volumes of numerical data. Among these capabilities are functions for executing mathematical operations on arrays, including computations of the mean, median, standard deviation, and beyond.

Additionally, `NumPy` equips users with numerous utilities for array manipulation, such as sorting, reshaping, and indexing, enhancing its indispensability in numerical and scientific computation.

One of the key advantages of `NumPy` is its capability for fast, efficient computations on large data arrays. This efficiency is due to the underlying optimized C and Fortran code, allowing `NumPy` to execute computations much faster than if using pure Python code.

Everything was clear?

## What is NumPy?

`NumPy` is a library for the Python programming language, designed for handling large, multi-dimensional arrays and matrices of numerical data. It plays a crucial role in scientific computing within Python and finds extensive use across various fields, including machine learning, data science, and scientific computing.

The library offers a vast array of functions and tools specifically for managing large volumes of numerical data. Among these capabilities are functions for executing mathematical operations on arrays, including computations of the mean, median, standard deviation, and beyond.

Additionally, `NumPy` equips users with numerous utilities for array manipulation, such as sorting, reshaping, and indexing, enhancing its indispensability in numerical and scientific computation.

One of the key advantages of `NumPy` is its capability for fast, efficient computations on large data arrays. This efficiency is due to the underlying optimized C and Fortran code, allowing `NumPy` to execute computations much faster than if using pure Python code.

Section 1. Chapter 1
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