Introduction

This week, we went over the structure of the course, as well as some basics of why we visualize, who we visualize for, and how to think about our relationship with our data.

Installation instructions

We will be using several Python packages that will be hosted on the PrairieLearn platform. You do not need to install anything locally at this stage, but if you want to you can follow the OPTIONAL installation instructions. Note that we will try to help you install locally, but the majority of support will be for students using the PrairieLearn platform. Additionally, packages you install locally may provide different interfaces than those on PrairieLearn – it is your responsibility to ensure your code works on your PrairieLearn submission.

Optional Reading List (See syllabus for acronyms)

  1. VAD, Ch. 1: What’s Viz, and Why Do It?
  2. FDV, Ch. 1: Introduction & FDV, Ch. 17: The principle of proportional ink
  3. Same Data, Multiple Perspectives
  4. Intro to Jupyter Notebook Video

Lectures

Lecture 1.1 - Class Introduction

The syllabus for the course, along with discussions about "what" visualizations are, and how to orient yourself in the course.

Lecture 1.2 - Why we Visualize

What are some of the basics of how we interpret visualizations? How can we describe the process of making choices, understanding our audience, and so forth?

Examples

Data

Assignments