Data Visualization for the Humanities

Undergraduate / Graduate

This course introduces best practices for visualizing data sets to assist the study of human languages, cultures, and history. Python-based tools will be used to create data visualizations, enhancing familiarity with that programming language. The emphasis will be on displaying data in a clear and elegant manner that is appropriate for the type of information we wish to showcase. Students will learn exploratory and explanatory data visualization techniques both to analyze the data and to communicate ideas via data-based storytelling. Possible biases in the way data is presented will be noted so students can learn to guard against them. Examples of data sets derived from research in the humanities will be used to develop creative and technical skills to produce standard 2D and 3D plots for descriptive summaries of the data, to identify outliers, and to do statistical correlations and model predictions that reveal underlying trends and potential anomalies. Social network analysis (a method widely used in the humanities and social sciences) will also be introduced, as well as tools for data visualization using geographical maps and timelines. Prerequisites: DIGS 20001/30001, "Introduction to Computer Programming Using Python," or an equivalent course in computer programming and DIGS 20002/30002, "Introduction to Statistics Using Python," or an equivalent course in statistics.