Introduction to Python for Humanists
- Available for pre-order on May 25, 2023. Item will ship after June 15, 2023
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Book 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
Table of Contents
Part I. Preface Chapter 1. Preface Part 2. The Basics of Python Chapter 2. Introduction to Python Chapter 3. Data and Data Structures Chapter 4. Loops and Logic Chapter 5. Formal Coding: Functions, Classes, and Libraries Chapter 6. Working with External Data Chapter 7. Working with Data on the Web Part 3. Data Analysis with Pandas Chapter 8. Introduction to Pandas Chapter 9. Working with Data in Pandas Chapter 10. Searching for Data Chapter 11. Advanced Pandas Part 4. Natural Language Processing with spaCy Chapter 12. Introduction to spaCy Chapter 13. Rules-Based spaCy Chapter 14. Solving a Domain-Specific Problem: A Case Study with Holocaust NER Part 5. Other Applications of Python Chapter 15. Topic Modeling: Concepts and Theory Chapter 16. Text Analysis with BookNLP Chapter 17. Social Network Analysis Part 6. Designing an Application with Streamlit Chapter 18. Introduction to Streamlit Chapter 19. Advanced Streamlit Features Chapter 20. Building a Database Query Application Part 7. Conclusion Chapter 21. Conclusion
Author(s)
Biography
William Mattingly is a 2022 Harry Frank Guggenheim Distinguished Scholar and a 2022-2023 ACLS Grantee for his work as co-principal investigator and lead developer for the Bitter Aloe Project which examines testimonies of violence from South Africa’s Truth and Reconciliation Commission. He is currently the Postdoctoral Fellow for the Analysis of Historical Documents at the Smithsonian Institution’s Data Science Lab. Mattingly currently works on two projects at the Smithsonian. The first is based at the United States Holocaust Memorial Museum (USHMM), where he is developing a robust pipeline of machine learning image classification and natural language processing (NLP) models to automate the cataloging of millions of images. At the Smithsonian, he is working on a project connected to the American Women’s History Initiative. Here, he is developing machine learning and heuristic pipelines with spaCy, a Python NLP library. This pipeline will identify women in Smithsonian documents and automatically extract knowledge about them so that we can better understand the influential role women played at the Smithsonian.