Data Viz Intro
Overview
Today we'll review the basics of data visualization and try our hands at a visualization exercise.
Class exercise
For this exercise, we'll partner up and work through the process of familiarizing ourselves with a given data set, identifying two or three questions of interest about the data, and then choosing visual forms that can help shed light on those questions. Keep one or more of the data visualization guides handy as an aide in choosing a chart type.
For a given data set, you should do the following:
- Craft two story questions that you can explore visually using the data set.
- Identify the field(s), or variables, that will be used to visually explore the questions. This must include a basic description of the data types involved (e.g. a nominal categorical variable or discrete quantitative variable). It's fine -- and often necessary -- to generate new variables for the purpose of analysis (e.g. aggregating a count of campaign contributions by candidate). You should explain if this type of data summarization is necessary for the analysis, and describe the generated fields and data types.
- Select one or more chart types appropriate for a visual analysis of the questions, and explain which you believe is most appropriate and why (specifically making reference to the fields and data types).
- Create hand-drawn sketches of your charts.
- What interactive features could you add to the charts? Annotate your hand-drawn sketches to illustrate the feature (e.g. a tooltip on hover over a bar chart).
Each group will be assigned one of the below data sets:
- Campaign Finance data - Use the data viewable on the linked web page (as opposed to drilling down into the individual filings or downloading filing data)
- Death Penalty Info Center executions
- Stanford Open Policing Project - Download the data from Stockton (CA), which has a reasonable amount of rows and data attributes available
Assignment 8
Complete the in-class assignment with your partner and be prepared to present your story questions and related data visualization sketches on Thursday May 9th. Partners should collaboratively discuss the story ideas, select visualization types, etc., but you should divide the task of sketching and presentation (so that each person has a chance to sketch and present one visualization).