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Intro

Welcome to the wiki for the course Social data analysis and visualization (02806) offered by the Technical University of Denmark. This is the main page, where you can access the weekly exercises. If you take a look in the side-bar, you can read about the administrative details (including a very useful course overview), assignments, books, and more.

The class is taught flipped classroom style, where the the lecture and homework elements of a course are reversed. You'll be able to view short video lectures before (or during) the class session, so in-class time can be devoted to exercises, projects, or discussions. Check out the first lecture to learn more.

Assignments

• Assignment 1 is available here.
• Assignment 2 will be made available here.

Exercises

Week 5: A bigger project begins. Today, we begin to work on a bigger project of visualizing crime-data for NYC. But there's other work to get through also: We'll learn about peer grading, how to make not-bad visualizations in the lectures and read about selections as well as aggregations. Finally, we'll get started with the visualizations.

• Reading. Interactive Data Visualization, 2nd edition Chapter 12,13.

Week 4: Interactivity and Paths. A nice little selection of topics today. In terms of theory, we look at exploratory data analysis for two variables, we then segue into a discussion of explanatory data analysis. Then we'll ready about interactivity and paths in IDV and finally we'll practice our new skills.

• Reading 1. Data Analysis with Open Source Tools. Chapter 3. Get it here
• Reading 2. Interactive Data Visualization, 2nd edition Chapter 10,11.

Week 3: Scales, Axes, and more. We read more of the book, watch a lecture on the components that go into making a visualization, and finally try and text our newfangled skills on reproducing a real-world website (making it our own in the process). You can also see the week's lecture here on github, but the videos won't display properly.

• Reading: Interactive Data Visualization, 2nd edition Chapter 7,8,9.

Week 2: Plotting simple data. This week we start with lectures - learn something about data visualization (so we go beyond javascript). We also keep working with the book and generate our own first plots. You can also see the week's lecture here on github, but the videos won't display properly

• Reading 1: Interactive Data Visualization, 2nd edition Chapter 6.
• Reading 2: Data Analysis with Open Source Tools. Chapter 2 (you can get the text here).

Week 1: Introduction. This week is all about getting started. This year (unlike previous years), we start with visualization. We begin the lecture by introducing the point and methodology of the class. In the second part, we get started on learning how to use D3.js. D3 requires knowledge of javascript so we'll take it slow. But the good news is that D3/javascript is amazing and not that difficult once you wrap your head around it. You can also see the week's lecture here on github, but the videos won't display properly

• Reading: Interactive Data Visualization, 2nd edition Chapter 1-5.