This beginner-friendly textbook is designed to quickly introduce readers to Python programming and its applications in data analytics, emphasizing a hands-on approach throughout. While we assume a basic familiarity with programming languages, relational databases, and statistics, the book caters to learners of all backgrounds interested in data-driven decision making. Key Features: - Focuses on equipping data analysts with essential knowledge and skills - Guides readers through Python fundamentals to intermediate topics like time series and regression analysis - Emphasizes practical implementation using the powerful Python library, Pandas - Introduces visualization techniques to effectively communicate insights, Matplotlib - Covers machine learning fundamentals for predictive analytics Learning Approach: - Utilizes simple datasets in most chapters to help readers grasp the inner workings of tools and techniques - Presents real-world datasets in the final chapter to expose learners to actual data scenarios and challenges - Encourages skill development and problem-solving abilities What's New in the Second Edition: - Updated all code examples - Added many more examples and exercises - Included new sections on data transformation and ARIMA - Added a new chapter summarizing the levels of business data analytics - Expanded coverage of data visualization and machine learning applications, reflecting recent changes in Pandas and industry trends This comprehensive guide is designed to take you from Python basics to intermediate data analytics techniques, equipping you to tackle real-world data challenges effectively and make informed, data-driven decisions.