Python Programming for Linguistics and Digital Humanities: Applications for Text-Focused Fields

Python is a versatile programming language used in linguistics, digital humanities, and social science programs for text analytics. This book provides a comprehensive introduction to Python for beginners, covering installation, command line, strings, modular code, GUI, language data annotation, visualizations, and more. It includes hands-on exercises and practical examples to apply concepts to language analysis and data processing. The book is suitable for students pursuing text-based research in the humanities, social sciences, and linguistics, particularly computational linguistics and corpus linguistics.

Format: Paperback / softback
Length: 288 pages
Publication date: 06 February 2024
Publisher: John Wiley and Sons Ltd

Python programming has emerged as a crucial skill in linguistics, the digital humanities (DH), and social science programs that involve text analytics. This comprehensive guide, designed for students with no prior programming experience, offers a thorough introduction to Python, covering essential topics such as installation, command line usage, working with strings, modular code development, GUI design, XML and TEI annotation, basic visualizations, and more. By providing hands-on exercises and real-world examples, the book equips students with the tools they need to conduct their own research projects and address complex data analysis challenges. Each chapter concludes with a detailed discussion of the code applied, potential alternatives, and common errors or pitfalls to avoid. Whether you are a linguistics student, a digital humanities enthusiast, or a social science researcher, Python Programming for Linguistics and Digital Humanities is an invaluable resource that will empower you to leverage the power of Python in your work.

Introduction:
Python programming has transcended its traditional domain of computer science and has become an essential skill in linguistics, the digital humanities (DH), and social science programs that involve text analytics. This comprehensive guide aims to provide students with a solid foundation in Python, enabling them to perform various processing and analysis techniques on text.

Assumptions:
We assume that you have no prior knowledge of programming. However, we will provide a gentle introduction to programming concepts and terminology throughout the guide.

Chapter 1:
Installation and Setup:
In this chapter, we will cover the steps to install Python on your computer. We will also discuss the importance of setting up a development environment and installing necessary packages.

Chapter 2:
Command Line Interface:
The command line interface (CLI) is a powerful tool for interacting with Python. In this chapter, we will learn how to navigate the command line, create and manage files, and execute Python scripts.

Chapter 3:
Strings and Text Processing:
Strings are the building blocks of Python programming. In this chapter, we will explore various string manipulation techniques, such as concatenation, slicing, and regular expressions. We will also learn how to work with text files and perform basic text analysis tasks.

Chapter 4:
Modular Code Development:
Modular code development is a key concept in Python. In this chapter, we will learn how to write modular code, use functions, and create classes to organize and reuse code.

Chapter 5:
Graphical User Interface (GUI) Development:
Creating a user-friendly graphical user interface (GUI) can enhance the usability of your Python programs. In this chapter, we will learn how to use GUI frameworks such as Tkinter to design and build simple GUIs.

Chapter 6:
XML and TEI Annotation:
XML and TEI (Text Encoding Initiative) are standard formats for annotating language data. In this chapter, we will learn how to use Python libraries such as lxml and pytei to annotate language data in XML and TEI formats.

Chapter 7:
Basic Visualizations:
Visualization is a powerful tool for understanding and interpreting data. In this chapter, we will learn how to create basic visualizations using Python libraries such as Matplotlib and Seaborn.

Chapter 8:
Advanced Topics:
As you progress in your Python journey, you may encounter more advanced topics such as machine learning, natural language processing, and data mining. In this chapter, we will explore these topics and discuss their applications in linguistics and the digital humanities.

Conclusion:
Python Programming for Linguistics and Digital Humanities provides a comprehensive introduction to Python programming, covering essential topics and concepts. By the end of this guide, you will have the skills and knowledge necessary to use Python for your own research projects and tackle complex data analysis problems in linguistics and the digital humanities.

Weight: 556g
Dimension: 178 x 255 x 21 (mm)
ISBN-13: 9781119907947