This year, one of my many New Year’s resolutions was to participate in The 100 Day Project, a creativity project that requires making one thing, every day for 100 days.

I’m a data visualization designer with a master’s degree in Information Visualization. And I love working with clay. I was a ceramics instructor at a summer camp for six years, and recently finished taking an advanced wheel throwing class. Molding things with my hands comes naturally to me.

I wanted to merge these two seemingly disparate passions of data visualization and ceramics in a playful way. Day-Doh-Viz was born: Data visualizations created out of Play-Doh produced “daily”. #DayDohViz

Play-Doh is a great medium because it’s brightly colored and photogenic. It’s easily moldable; you can pretty much do anything with it. It’s reusable and relatively inexpensive. And taking something from childhood and elevating it for a different use has a playful, nostalgic feel.

Working with Play-Doh also limits precision. It isn’t going to be perfect, but that’s part of the fun. It stops me from being a perfectionist and lets me focus on the bigger theme. It also allows me to visualize things I might not want to show with absolute precision, like my financial data.

My (45 so far!) play-doh visualizations have mostly fallen into 3 categories. Financial, personal data, and remakes of other data visualizations. Here are 6 of my favorite DayDohViz:

Income and Expenditures in April

Talking about money is such a taboo subject. Especially sharing your own financial information. Most of us aren’t great at personal finance, and it doesn’t help that we’re afraid to share this information with others. I like to help destigmatize this by sharing my own information. Play-doh feels like a low risk way to do this. It’s a little imprecise, and I don’t have to label the exact numbers, but the viewer gets the feel of what’s going on, and can maybe relate.

Perceptions of Probability in Play-Doh

What does it mean when something is “probable”? Is it more certain than “highly likely”? I love the original perceptions of probability joyplots, which plotted survey respondents numerical probability estimates for a variety of phrases. It quantifies how people perceive these usually squishy terms. It’s also colorful and fun. Doing a remake of it in Play-Doh was an enjoyable experience.

In doing so, I realized that joyplots are like the side view of violin plots. This Day-Doh-Vis won the most informative #CraftyDataViz Award.

Beverage Enjoyment

I love liquids. When you’re trying to create a whole new visualization every day, sometime you just need to graph something easy with “data” that you know. To me, the chart details make this one especially fun. All the carbonated beverages have a slight bubble texture to them. I added little suggestions of fruit to the drinks that typically come with a lemon, lime or cherry. The size of the sphere is the amount I want to drink and the proximity to the top is my enjoyment level. This was a quick viz to build probably about an hour.

Costs of New Dog Ownership

This one was another way of showing and talking about personal finance using my own experience and data. I knew there were going to be lots of start up costs to adopting a dog. I was surprised at how varied and spread out they were. The gif format helps the labeling not seem overwhelming, and allowed me to try my hand at something different. For just the bar graph, the extruding and assemble portion, took me about 40 minutes.

Birthdays Parties Change with Age

I’m at an age where on a Saturday I can attend a friend’s child’s party and an adult’s birthday. The contrast is quite interesting. When the little ones crash, they crash HARD. It was fun to build and make the numbers out of Play-Doh.

Birth Rate Viz in 3D

Inspired by the popular Scientific America visualization “Why Are so Many Babies Born around 8:00 A.M.” The original visualization has aspects of being 3D but is visualized in two dimensions. I played with that and built it on top of a glass jar. The original chart was so great, I didn’t want to mess with that, just bring out a different aspect that building it in real life could highlight. There was a lot of measuring over three days to create this one and I plastic wrapped it overnight.

Steps of Day-Doh-Viz-ing

1. Conceptualize. Have a brilliant idea of what I want to visualize.
2. Research. Figure out what data is available for what I want to show and how do I get it.
3. Data collection. Find and organize the data. Sometimes I’m tracking my own data over time. Or going through and collecting specific data about a topic.
4. Design. Figure out how I want to show it and either sketch or do some test graphs in google sheets.
5. Gather materials. I have a bin of play doh, but sometimes you need to find the right jar, or custom tape, or print out a graph to build on top of.
6. Color mix. Squish colors together to create colors that will match the visualization or work well being photographed. Warm colors tend to blow out when you don’t add a little black or white to them.
7. Build. Create the visual out of play-doh, sometimes this involves rolling balls, extruding bars, or forming mounds.
8. Lighting set-up. Sometimes window lighting works nicely, sometime I need to use a ring light.
9. Photograph. I always take different angles so it’s usually at least 20+ photos of each visual. Sometimes a video, sometimes a tripod so I can create a gif.
10. Image edit. I try to only stick to apps to keep it simple, so I’ve been using the iphone photo app and Facetune for some detail editing.
11. Annotate. Again, I’m trying to be simple, so I’m using This app to annotate my viz. It limits the amount of choices I have, like font and style.
12. Post. Share on social media and add to my portfolio of creations.

When you’re creating every data point by hand, you get to know your data intimately. As I’ve created more of these visualizations with play-doh, I’ve tried to find and highlight the unique things about this medium. I’m working to push the 3D aspect. And the ability to manipulate data and show different stages, or effects, by just adding elements or building everything and removing parts.

What I’ve Learned

• Most successful = unique form + unique data + well executed
• To remember that I’m doing this for fun
• Play-doh is cheap at TJ Maxx

The project has been highlighted in Andy Kirk’s Best of the Data Visualization for April list, and on Alli Torban’s Data Viz Today podcast. I’ve gotten a few hundred new Twitter followers, and asked to write a couple blog posts. Which is pretty successful for making things out of play-doh.

The best thing, I think, is that I’ve inspired other people to use play-doh for data visualization. Anna Fergusson took play-doh into her class and had her intro stats and data science students make visualizations. I’m not saying that play-doh is the best medium for data viz, but I think there’s something to be said for stepping away from traditional tools, and creating visualizations by hand.

And I think it can be less intimidating and to work with an imperfect medium, rather than pen and paper, or a computer which can feel demandingly precise.

Learn More about #DayDohViz

Follow along on Twitter for more #DayDohViz

The post #DayDohViz: Play-Doh as a Tool for Data Visualization appeared first on Depict Data Studio.

And the winners are… Tony Fujs, Andrea Hutson, Prince Rajan, and Bernadette Wright! Tony re-created the chart in R, and Andrea, Prince, and Bernadette re-created the chart in Excel.

Here’s my how-to guide. At the bottom of this blog post, you can download an Excel file that contains each of the submissions. We each used a slightly different approach, so I encourage you to study the file and see how we manipulated Excel in different ways.

Step 1: Study the Chart that You’re Trying to Reproduce in Excel

Here’s that chart from page 7 of the State of Evaluation 2012 report. We want to see whether we can re-create the chart in the lower right corner. The visualization uses circles, which means we’re going to create a bubble chart in Excel.

Step 2: Learn the Basics of Making a Bubble Chart in Excel

To fool Excel into making circles, we need to create a bubble chart in Excel. Click here for a Microsoft Office tutorial. According to the tutorial, “A bubble chart is a variation of a scatter chart in which the data points are replaced with bubbles. A bubble chart can be used instead of a scatter chart if your data has three data series.”

We’re not creating a true scatter plot or bubble chart because we’re not showing correlations between any variables. Instead, we’re just using the foundation of the bubble chart design – the circles. But, we still need to envision our chart on an x-y axis in order to make the circles.

Step 3: Sketch Your Chart on an X-Y Plane

It helps to sketch this part by hand. I printed page 7 of the report and drew my x and y axes right on top of the chart. For example, 79% of large nonprofit organizations reported that they compile statistics. This bubble would get an x-value of 3 and a y-value of 5.

I didn’t use sequential numbering on my axes. In other words, you’ll notice that my y-axis has values of 1, 3, and 5 instead of 1, 2, and 3. I learned that the formatting seemed to look better when I had a little more space between my bubbles.

Step 4: Fill In Your Data Table in Excel

Open a new Excel file and start typing in your values. For example, we know that 79% of large nonprofit organizations reported that they compile statistics. This bubble has an x-value of 3, a y-value of 5, and a bubble size of 79%.

Go slowly. Check your work. If you make a typo in this step, your chart will get all wonky.

Step 5: Insert a Bubble Chart in Excel

Highlight the three columns on the right – the x column, the y column, and the frequency column. Don’t highlight the headers themselves (x, y, and bubble size). Click on the “Insert” tab at the top of the screen. Click on “Other Charts” and select a “Bubble Chart.”


You’ll get something that looks like this:

Step 6: Add and Format the Data Labels

First, add the basic data labels. Right-click on one of the bubbles. A drop-down menu will appear. Select “Add Data Labels.” You’ll get something that looks like this:


Second, adjust the data labels. Right-click on one of the data labels (not on the bubble). A drop-down menu will appear. Select “Format Data Labels.” A pop-up screen will appear. You need to adjust two things. Under “Label Contains,” select “Bubble Size.” (The default setting on my computer is “Y Value.”) Next, under “Label Position,” select “Center.” (The default setting on my computer is “Right.)

Step 7: Format Everything Else

Your basic bubble chart is finished! Now, you just need to fiddle with the formatting. This is easier said than done, and probably takes the longest out of all the steps.

Here’s how I formatted my chart:

• I formatted the axes so that my x-values ranged from 0 to 10 and my y-values ranged from 0 to 6.
• I inserted separate text boxes for each of the following: the small, medium, and large organizations; the quantitative and qualitative practices; and the type evaluation practice (e.g., compiling statistics, feedback forms, etc.) I also made the text gray instead of black.
• I increased the font size and used bold font.
• I changed the color of the bubbles to blue, light green, and red.
• I made the gridlines gray instead of black, and I inserted a white text box on top of the top and bottom gridlines to hide them from sight.

Your final chart will look something like this:

Bonus! Download the Excel File

Click below to download the Excel file that I used to create this bubble chart. Please explore the chart by right-clicking to see how the various components were made. You’ll notice a lot of text boxes on top of each other!

Thanks again to the dataviz challenge winners, Tony Fujs, Andrea Hutson, Prince Rajan, and Bernadette Wright! Tony, Andrea, Prince, and Bernadette have graciously shared their Excel files. I created a separate tab to showcase each of their charts. We each formatted the data table and the chart a little differently, so I encourage you to explore their approaches and contact them with additional questions (and kudos!).

The post How to Make a Bubble Chart in Microsoft Excel appeared first on Depict Data Studio.

Sometimes evaluators are hesitant to use Excel. One misconception is that Excel is only good for 3-D exploding pie charts, boring bar charts, and random radar charts. But Excel can do more than you think!
Innovation Network recently published State of Evaluation 2012: Evaluation Practice and Capacity in the Nonprofit Sector. Click here to download the report. I loved the visualizations in the report and wondered if I could re-create them in Excel.

Here’s a screenshot from page 7 of State of Evaluation 2012. The visualization shows the percentage of small, medium, and large nonprofit organizations that used quantitative and qualitative evaluation practices. Quantitative practices were more common than qualitative practices, and medium and large organizations were more likely to use these practices than smaller organizations.

And here’s what I made with a little Excel elbow grease:

The formatting’s not identical, but that’s not the point. Did you realize that you can manipulate Excel to produce almost anything you want?

I challenge you to re-create this State of Evaluation chart in Excel or R — no expensive software allowed. Email me your submission or tweet an image to @annkemery. I’ll post the solution on March 12, 2013.

What do you get for playing? A coffee or beer together, my treat, the next time you’re in DC; a workout for your brain; and bragging rights. Game on!

The post Dataviz Challenge #1: Can You Make a Bubble Chart in Excel? appeared first on Depict Data Studio.