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9781529707489 Academic Inspection Copy

From Social Science to Data Science

Key Data Collection and Analysis Skills in Python
  • ISBN-13: 9781529707489
  • Publisher: SAGE PUBLICATIONS
    Imprint: SAGE PUBLICATIONS
  • By Bernie Hogan
  • Price: AUD $112.00
  • Stock: 2 in stock
  • Availability: Order will be despatched as soon as possible.
  • Local release date: 31/12/2022
  • Format: Paperback (242.00mm X 170.00mm) 400 pages Weight: 740g
  • Categories: Research methods: general [GPS]
Description
Table of
Contents
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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.
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
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