From social science to data science / Bernie Hogan.

Author/creator Hogan, Bernie
Format Electronic
Publication InfoLos Angeles : Sage, [2023]
Descriptionxxxiv, 361 pages : illustrations (chiefly color) ; 26 cm
Supplemental ContentFull text available from SAGE Research Methods Core
Subjects

Contents Part I: Thinking Pragmatically--Chapter 1. Introduction --Chapter 2. The Series --Chapter 3. The DataFrame --Part II: Accessing and Converting Data--Chapter 4. File Types --Chapter 5. Merging and Grouping Data --Chapter 6. Accessing the Web --Chapter 7. Accessing APIs --Part III. Interpreting Data: Expectations versus Observations--Chapter 8. Research Questions --Chapter 9. Visualising Expectations --Part IV: Social Data Science in Practice: Four Approaches--Chapter 10. Cleaning Data --Chapter 11. Introducing Natural Language Processing --Chapter 12. Introducing Time Series Data --Chapter 13. Introducing Network Analysis --Chapter 14. Introducing Geographic Information Systems --Chapter 15. Conclusion
Abstract From Social Science to Data Science is a fundamental guide to scaling up and advancing your programming skills in Python. From beginning to end, this book will enable you to understand merging, accessing, cleaning and interpreting data whilst gaining a deeper understanding into computational techniques and seeing the bigger picture. With key features such as tables, figures, step-by-step instruction and explanations giving a wider context, Hogan presents a clear and concise analysis on key data collection and skills in Python. -- Provided by publisher.
Bibliography noteIncludes bibliographical references and index.
Access restrictionAvailable only to authorized users.
Technical detailsMode of access: World Wide Web
Genre/formElectronic books.
LCCN 2022938266
ISBN9781529707489 paperback
ISBN152970748X paperback
ISBN9781529707496 hardcover
ISBN1529707498 hardcover