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Full Description
This book will introduce digital humanists at all levels of education to Python. It provides background and guidance on learning the Python computer programming language, and as it presumes no knowledge on the part of the reader about computers or coding concepts allows the reader to gradually learn the more complex tasks that are currently popular in the field of digital humanities. This book will be aimed at undergraduates, graduates, and faculty who are interested in learning how to use Python as a tool within their workflow. An Introduction to Python for Digital Humanists will act as a primer for students who wish to use Python, allowing them to engage with more advanced textbooks. This book fills a real need, as it is first Python introduction to be aimed squarely at humanities students, as other books currently available do not approach Python from a humanities perspective. It will be designed so that those experienced in Python can teach from it, in addition to allowing those who are interested in being self-taught can use it for that purpose.
Key Features:
Data analysis
Data science
Computational humanities
Digital humanities
Python
Natural language processing
Social network analysis
App development
Contents
Part I. The Basics of Python. Chapter 1. Introduction to Python. Chapter 2. Data and Data Structures. Chapter 3. Loops and Logic. Chapter 4. Formal Coding: Functions, Classes, and Libraries. Chapter 5. Working with External Data. Chapter 6. Working with Data on the Web. Part II. Data Analysis with Pandas. Chapter 7. Introduction to Pandas. Chapter 8. Working with Data in Pandas. Chapter 9. Searching for Data. Chapter 10. Advanced Pandas. Part III. Natural Language Processing with spaCy. Chapter 11. Introduction to spaCy. Chapter 12. Rules-Based spaCy. Chapter 13. Solving a Domain-Specific Problem: A Case Study with Holocaust NER. Chapter 14. Topic Modeling: Concepts and Theory. Chapter 15. Text Analysis with BookNLP. Chapter 16. Social Network Analysis. Part IV. Designing an Application with Streamlit. Chapter 17. Introduction to Streamlit. Chapter 18. Advanced Streamlit Features. Chapter 19. Building a Database Query Application. Part V. Conclusion. Chapter 21. Conclusion.
