Data Visualization Pictionary

The Chicago Data Visualization Group teamed up with the American Evaluation Association’s Data Visualization special interest group for a joint meetup. It was a tremendous pleasure and very fun to team-up with Stephanie Evergreen and Kate Livingston to work on the meetup. In particular, we were able to derive a Data Visualization Pictionary game.

Below are the rules and some example outcomes

Teams:

  • Split group into teams– ideally teams of 3-6 people so all have a chance to draw.
  • Each team has 2 mins to come up with data viz related team name.

Rules:

  1. It’s more fun if everyone gets a chance (or is forced) to draw; each team needs to choose what order they will draw in (assign each person a number);
  2. When it’s your turn to draw, come up to the drawing board and the game masters will give you your card;
  3. Cards are in the following categories: people, objects, “visualize this”, and difficult;
    1. People – data visualization experts and practitioners
    2. Objects – types of graphs
    3. “Visualize this” category requires you to create a visualization based on the phrase. Drawers may use one label on the graph to provide a hint.
    4. Difficult – a miscellaneous category of difficult topics, graphs
  4. Game masters will announce the category out loud to everyone, but only the drawer will get to see the card;
  5. The drawer will have 15 seconds to look at and take in their clue;
  6. The drawer can choose to pass, in which case the game masters will give them a different card; if a drawer does pass, their team loses a point; it’s best to try to draw what’s on your card, even if you don’t know what it is or what it means; you never know, your team may guess it;
  7. The person drawing will have 60 seconds to draw what’s on the card; only their own team mates are allowed to guess during that time; teammates can just should out anything that comes to mind; the game masters will decide if they get it or if it’s close enough within the allotted 60 seconds to award the team a point.;
  8. The person drawing may not use gestures, words, hand signals, head nods, or any other signs to indicate if their team is on the right track or not;  
  9. The person drawing may not include letters or numbers in their drawing;
  10. At the end of 60 seconds, if the team has not correctly guessed the card other teams will have a chance to guess; game masters will ask teams in order of which team is next until either one of the teams guesses correctly or until each team has had a guess and all were wrong; if a team guesses correctly, they get a point;
  11. The next team, determined by the game master’s order, has a drawer come up and the process starts again;
  12. Game play continues until one team has 5 points

The team name that game masters like the best is the team that draws first; the other teams are in a random order decided by the game masters.

First team has drawer come up and game begins.

Game masters keep score, remind teams of order, and decide on ‘close’ guesses and points awarded.

Game play continues until a team gets 5 points.

Examples

People Graph Types Visualize This Difficult
Edward Tufte Bar Chart Time series of Bobby Jindal’s poll numbers Slope Graph
Stephanie Evergreen Dot plot Correlation of temperature and happiness Voronoi map
IMAG1016
Data Viz Pictionary Challenge: The quality of Chicago’s pizza versus New York

The different categories have their own challenge: the ability to characterize notable data visualization authors or just simply remember how to draw particular graphs. But, perhaps most fun, is to visualize a phrase: above, the relative quality of Chicago deep dish pizza to New York’s style. Below, an visualization of Bobby Jindal’s poll numbers.

IMAG1014
Visualize Bobby Jindal’s poll numbers
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CDVG members will meet to discuss free online data visualization course offered by Knight Center.

Alberto Cairo and the Knight Center for Journalism in the Americas is offering a free online introduction to data journalism and infographics course in October. I am signing up and I hope that some of you will join me. If you want to discuss the course materials with your fellow CDVG members also taking the course then sign up for the meeting at our meetup site.

Workshop: Graphing with R & ggplot2

Descriptionggplot2 example by Hadley Wickham

Introduce yourself to R and the powerful graphing library based on the Grammar of Graphics–ggplot2. Attendees will work in small teams to learn how to generate basic and advanced plots in ggplot2 to solve a variety of problems. The workshop will also review the fundamentals of data visualization to increase the readability and clarity of plots.

The workshop is open to all types of users, including those who are unfamiliar with R. We will mix some demonstration with small group-based projects. Basic principles of data visualization will also be emphasized alongside ggplot2 demonstrations to put the program into a larger context.

Audience

The workshop is targeted to individuals who are not familiar with ggplot2, including beginners who are new to the R software. Attendees will need to bring there own computer where we will install the R and ggplot2 software–don’t worry, both are open source and free.

Time, Location, & Signup

The workshop begins October 8  in the IMSA classroom at 1871 located on the 12th floor of The Merchandise Mart (222 W. Merchandise Mart Plaza). It includes four sessions (outline below) meeting on consecutive Mondays at 6pm. The IMSA room isn’t available on October 22 so, depending on the number of attendees, we will either meet in a smaller conference room or push the schedule a week.

There are only 30 seats available for this workshop due to the size limitations of the IMSA classroom. Interested attendees need to go to the CDVG meetup site to sign up for each of the four sessions.

Workshop Leaders

The workshop will be led by CDVG member Tom Schenk. Tom is a Senior Research Data Analyst at Northwestern University, Department of Medical Social Sciences. You can read more about Tom on his website. He also curates Data Nouveau–a collection of interesting data visualizations on the web.

Tom will be assisted by CDVG member Josh Doyle (who is relatively new to R & ggplot2 and will ask the dumb questions so others won’t have to). We also expect to have some other experienced folks in the room to help out.

Workshop Outline

Introduction to R (October 8)

We will familiarized ourselves with the R environment with a gentle introduction to the basic functions. After installing R, we will import and inspect data sets while becoming familiar with R terminology. By the end of the class, we will conduct basic descriptions and plots of the data.

  • Learn how to import data into R.
  • Understand the structure of data sets and their components..
  • Learn how to describe data.
  • Download and install new packages from CRAN.
  • Plot data using basic R functions.

Introduction to ggplot2 (October 15)

We will begin to use the ggplot2 package to create basic, but handsome, univariate, bivariate, and time-series graphs. We will introduce the functions and terminology used in ggplot2. We will also explain the fundamentals of proper data visualization techniques and how it relates to the ggplot2 defaults.

  • Install the ggplot2 package.
  • Use geometric shapes to display data.

Grammar of Graphics (October 22 or 29)

We will continue to show more advanced features of ggplot2, including how it relates to Leland Wilkinson’s Grammar of Graphics. We will show how to plot more than 2 variables in a single graph using colors, shapes, and sizes. We will also discuss how human ability to perceive different shapes and colors should drive the choices we make in data visualization.

  • Using scales to add information.
  • Using coordinates to aid interpretations.
  • Easily create small multiple graphs.

Plots for Publications (October 29 or November 5)

After learning how to make plots, we will learn how to customize graphs with custom colors, labels, and themes. We will emphasize how to create a customized look to be included in publications, including adding labels in diagrams to help readers.

  • Saving graphs from R into publication-friendly formats.
  • Use custom colors for plots.
  • Use your own fonts.
  • Customizing ggplot2 graphs with the new themes feature.

Coming in October: CDVG hosting weekly datavis hacking/learning!

I’m happy to announce that the CDVG will host weekly learning sessions at 1871 focused on tools and technologies. That’s right. Every Monday we will get our hands dirty with data, code, and utilities. Some nights we may have an instructor and other nights we’ll just all learn together. All levels of knowledge will be welcome. CDVG member Tom Schenk, Jr and I are still working through the organization of topics. I’ll provide more details on the content of these weekly sessions soon.

Really looking forward to this.

Video of Andy Kirk presenting “The 8 Hats of Data Visualization Design” at Orbitz

You can see a video of Andy Kirk of visualisingdata.com presenting “The 8 Hats of Data Visualization Design” at Orbitz in Chicago on June 14th on Devops.com.  This is the same talk he presented at the CDVG meetup that evening.  The Q&A session at the end introduces some topics that we didn’t discuss at the CDVG meeting.  It is worth watching.

Thanks to Martin J. Logan of Orbitz for posting.