Introduction to data systems : building from Python Part I Foundation 1. Introduction 2. File Systems and File Processing 3. Python Native Data Structures 4. Regular Expressions Part II Data Systems: The Data Models 5. Data Systems Models 6. Tabular Model: Structure and Formats 7. Tabular Model: Access Operations and pandas 8. Tabular Model: Advanced Operations and pandas 9. Tabular Model: Transformations and Constraints 10. Relational Model: Structure and Architecture 11. Relational Operations: Single Table 12. Relational Operations: Multiple Tables 13. Relational Database Programming 14. Relational Model: Design Constraints and Creation 15. Hierarchical Model: Structure and Formats 16. Hierarchical Model: Operations and Programming 17. Hierarchical Model: Constraints Part III Data Systems: The Data Sources 18. Overview of Data Systems Sources 19. Networking and Client Server 20. The HyperText Transfer Protocol 21. Interlude: Client Data Acquisition 22. Web Scraping 23. RESTful Application Programming Interfaces 24. Authentication and Authorization. Encompassing a broad range of forms and sources of data this textbook introduces data systems through a progressive presentation. Introduction to Data Systems covers data acquisition starting with local files then progresses to data acquired from relational databases from REST APIs and through web scraping. It teaches data forms formats from tidy data to relationally defined sets of tables to hierarchical structure like XML and JSON using data models to convey the structure operations and constraints of each data form. The starting point of the book is a foundation in Python programming found in introductory computer science classes or short courses on the language and so does not require prerequisites of data structures algorithms or other courses. This makes the material accessible to students early in their educational career and equips them with understanding and skills that can be applied in computer science data science data analytics and information technology programs as well as for internships and research experiences. This book is accessible to a wide variety of students. By drawing together content normally spread across upper level computer science courses it offers a single source providing the essentials for data science practitioners. In our increasingly data centric world students from all domains will benefit from the “data aptitude” built by the material in this book.