This beginner-friendly textbook on data analytics is designed to quickly immerse readers in the world of Python programming and its applications in data analysis. While we assume a basic familiarity with programming languages, relational databases, and statistics, the book caters to learners of all backgrounds.
The main focus of the book is to equip data analysts with essential knowledge and skills, guiding them through Python fundamentals and gradually delving into advanced topics like time series and regression analysis. A special emphasis is placed on the practical implementation of concepts using the powerful Python library, Pandas.
Throughout the book, we utilize simple datasets in most chapters, allowing readers to grasp the inner workings of tools and techniques. However, in the final chapter, we present real-world datasets to expose learners to the challenges and complexities of actual data scenarios, encouraging further skill development and problem-solving abilities.
Key topics covered include Python syntax, data loading, cleaning, preparation, aggregation, visualization, time series analysis, and regressions. Our teaching philosophy revolves around active learning, and to facilitate this, we provide numerous code examples for readers to practice. Additionally, the book includes a comprehensive set of 669 review questions that encompass both conceptual understanding and coding proficiency.
By the end of this journey, readers will have gained a solid foundation in data analytics and Python, empowering them to apply their newfound knowledge to real-world challenges with confidence.