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Python is a general-purpose programming language that is popular with data scientists. It is free, as are a number of open-source libraries help acquire, organize, and process information. This book is designed for beginners to data analysis and covers the basics of Python data analysis programming and statistics. The book covers the Python fundamentals that are necessary to data analysis, including objects, functions, modules, and libraries. The book provides the statistical background needed to get started in data science programming, including probability, random distributions, hypothesis testing, confidence intervals, and building regression models for prediction||About the Author - John Mueller is a freelance author and technical editor. He has writing in his blood, having produced 99 books and more than 600 articles to date. The topics range from networking to home security and from database management to heads-down programming. During his time at Cubic Corporation, John was exposed to reliability engineering and has had a continued interest in probability ever since||Luca Massaron is a data scientist specialized in organizing and interpreting big data and transforming it into smart data by means of the simplest and most effective data mining and machine learning techniques. Because of his job as a quantitative marketing consultant and marketing researcher, he has been involved in quantitative data since 2000 with different clients and in various industries. Luca was able to quickly rank among the top 10 Kaggle data scientists.