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.   The remainder of the book provides examples and tips and tricks for doing interesting things with data analysis programming. The topics are arranged into the following parts: PART I: Getting Started with Data Science & Python PART II: Getting Your Hands Dirty with Data PART III: Visualizing Information PART IV: Wrangling Data PART V: Learning from Data PART VI: Part of Tens