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From Social Science to Data Science

From Social Science to Data Science
Key Data Collection and Analysis Skills in Python

  • Bernie Hogan - University of Oxford, Oxford Internet Institute, UK

December 2022 | 400 pages | SAGE Publications Ltd
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 of 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 of key data collection and skills in Python. 
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
About the Author

Excellent. The students will love I think. It reminds me a bit of a Andy Field’s SPSS/R books, which the students have also loved in the past too. This one has that flavour but also pushes the analytics into the contemporary era with Python. I expect it will be a real success.

Emma Uprichard
Centre for Interdisciplinary Methodologies, Alan Institute Fellow, University of Warwick

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ISBN: 9781529707489
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