This course introduces students of the humanities to Python. It presumes no knowledge of computer programming. Python provides a perfect introductory programming language because it uses simple syntax (style of language), indentation (making it easy to read), and has many libraries (which handle higher-end coding).
I break down the course into seven parts. Part One introduces the student to basic Python syntax and types of data. It presumes no knowledge of data at all. You are introduced to basic terms, such as strings and integers.
Part Two introduces the student to basic data structures, such as lists, tuples, and dictionaries. In these lessons, I show you how to create, load, and modify various data structures.
In Part Three, we begin working with some more complex Python. I show you how to structure different types of loops to iterate across your data, how to form conditional statements, and how write proper functions and classes. These lessons introduce you the core essentials of Python syntax.
Beginning with Part Four, we start putting our skills to use by interacting with data stored outside of Python. I also introduce you to libraries and common solutions to text-based problems. In Part Four, we work with text files, in Part Five, Excel files, and Part Six, web-based data.
Part Seven is the end of this introduction. During these final lessons, we speak about ways to cultivate and store data outside of Python. These lessons do not introduce you to new Python code, rather they are designed to help you consider when and why you should use specific data structures and files, such as text, csv, json, or xml.
Question: Why should you, a humanist, consider using Python?
Answer: The reason is because Python allows humanists to perform quantitative and qualitative data analysis on scales that are impossible in an analog world.
Question: Why can’t I just use available third-party software like Palladio for networks?
Answer: The reason is because third-party software, like Palladio, is designed for ease-of-use. This comes at the cost of control on the part of the user. By working with data in Python you can control the data and manipulate it in ways that you cannot with third-party software.