Python has solidified its place as one of the most versatile and powerful programming languages in the world, thanks to its simplicity, readability, and extensive support for various fields such as data science, web development, machine learning, and automation. For anyone embarking on a journey into the world of programming, Python offers a gateway that is both accessible and highly functional. This book, Python Programming: General-Purpose Libraries; NumPy, Pandas, Matplotlib, Seaborn, Requests, os & sys, is designed to be a comprehensive guide to mastering Python's essential general-purpose libraries. These libraries are crucial tools for anyone looking to perform data analysis, visualization, or automation. By the end of this book, you will have gained the foundational skills required to leverage these libraries to their full potential in real-world projects. In the first part of the book, we will delve into NumPy, the cornerstone of numerical computing in Python. With its array objects and mathematical functions, NumPy allows us to efficiently manipulate large datasets and perform complex mathematical operations. We will explore NumPy's capabilities and how it serves as the backbone for other scientific libraries. Next, we will tackle Pandas, an indispensable library for data manipulation and analysis. Pandas provides powerful tools for working with structured data, including Series and DataFrames, which allow you to clean, filter, and analyze data in ways that are both intuitive and efficient. The goal is to provide you with a deep understanding of how to handle data in various formats such as CSV, Excel, and SQL databases. Matplotlib and Seaborn will introduce you to the art of data visualization. While Matplotlib allows you to create a wide array of static, animated, and interactive visualizations, Seaborn enhances Matplotlib's capabilities with a simpler syntax and aesthetically pleasing statistical graphics. By the end of this section, you'll have a solid grasp of how to represent complex data visually and communicate insights through charts, graphs, and plots. Requests is the library that simplifies working with HTTP requests in Python, allowing you to interact with web APIs, download files, and retrieve data from the web. Understanding how to use this library effectively is key to working with external data sources, making it a vital tool in web scraping, web services, and automation projects. Finally, we will cover os and sys, two libraries th