As some of you may know, I’ve recently started teaching data visualization at the University of Utah. I’ve only been at it a couple of weeks, but it has been a great learning experience for me (and hopefully my students). Now that I am teaching the subject, it seemed like a decent time to do some self reflection to see what I might do differently in some of my past Tableau Public projects.
Much (exactly) like Makeover Monday, this series will take a look at a visualization (of my own) that is in need of improvement, with the end result being a new improved visualization that clarifies the original message. Customary to Andy’s original format, I’ll also be describing things that work well/didn’t work well with the original visualization.
For the second entry to this series, I’ll be looking at my most popular Tableau Public viz: #IronViz Wikibirths. This viz was created in March 2015, and was my first venture into the Iron Viz ring. This viz was a fun project for me, as it also started my interest in scraping web data with Python. The dataset used for my entry was harvested across 366 Wikipedia pages (like this one) in only minutes.. it was then that I started to understand the power of having additional dev skills outside of Tableau.
My viz didn’t win a trip to Vegas… Shine showcased his amazing storytelling skills and went on to win the main competition later that year. Somewhere along the way, this crazy orange viz of mine went viral, and somehow has over 200,000 views to date! After taking a careful look back, I don’t think all those views are really warranted, as the viz itself is pretty confusing. Join me, and guest bloggers Pooja Gandhi and Adam Crahen of the Data Duo, as we critique and makeover this orange mess.
I will never not be amazed at the amount of views this viz has, so I must have been doing something right, but let’s turn the time over to the Data Duo to see what actually works and doesn’t work. I’m guessing there will be more that doesn’t work…
The Data Duo Perspective
We chat with Curtis all the time and have become great friends over the last year and a half. We often share work amongst each other and ask for feedback. One day, during a recent conversation, he casually slips in this request…
We both eagerly agreed. Only realizing minutes later that he just asked us to critique a single viz that has more views than probably all our 200+ public visualizations put together. No pressure at all so here goes.
What works well?
- The viz is visually striking and draws you in.
- The question in the title and instructions provoke interaction to make the dashboard personalized for the user.
- We love the ‘You’ label on the heat map for the value entered in the parameter – again personalized for my choice. But maybe the font could be slightly bigger!
- The custom legend for the significant births on the selected day (arrow) compared with the most per day (23) is very cool
- Detailed list of births for each day
- Good use of limited colors
- Good use of space
What doesn’t work well?
- What does a significant birth mean? How is it defined? The data source isn’t listed.
- Could use some structure and divider lines to break the visual components for better readability.
- Some people get confused by a stacked area chart since the individual values do not correspond to the axis.
- Would be nice if there is a way to highlight a month selected from the legend to see it on the area chart with years of min/max births as labels
- The area chart axis is on the left and hard to use because of the heat map. A dual axis would have worked well there. Heat map could be placed outside of the area chart space to avoid that confusion
- Five charts encode the same color differently.
- Four of them encode color as darker orange = more births, but they are all different ranges. The area chart does not follow the same encoding (darker color = later month)
- The custom legend for significant births, the heat map, and stacked bar for the selected month have three different colors and all are looking at the same day.
- The Stacked bar for the selected month is repetitive. Perhaps a histogram on both sides of the heat map and some BIG ASS NUMBERS across the top would have been more effective.
- I can’t interact with the list of births. I wish I could link to their wiki page to find out more.
Overall, this is a great viz and is worthy of the views it received. However, we know Curtis has improved over time and we cannot wait to see his makeover. It will probably get another 200 thousand more views.
With Adam and Pooja’s thoughts in mind, let’s break down how we can
trash improve on the original. One key concept I’ve tried to latch onto is the thought that if you visualization still tells the same story in grayscale, then your color and design choices are probably fine.
Let’s take a look at what happens if we push all the colors to the background…
Pushing to gray really highlights one of the Duo’s comments: Five charts encode the same color differently. You could imply that a darker shade of orange/gray represents more significant births, but the coloring is still incorrect… one dark orange does not mean the same thing as another dark orange, and that fact isn’t readily apparent to the audience. The area chart is also in shades of orange, but has nothing to do with volume of births, which simply adds to the confusion.
After pushing the viz to grayscale, I went through a few of the different elements after finally landing on a conclusion.
Padding is your friend
Stacked area charts can be confusing and hard to read… especially this one
I’ll be honest, throwing this area chart in the trash was a tough decision as I think a lot of people immediately recognize that as my work. I went back and forth on a decision to remove or improve..
I thought I had a decent solution to the coloring problem (below), but the stacked area chart was still just for show, and didn’t tie back to the original question in the title.
You’re still here? This got a bit wordy, so I appreciate you sticking around until the end. Here is the new visualization, and some thoughts as to why it is a major improvement to the original.
- The viz is now officially about you and your birthday, it wasn’t before
- You can now easily see how many people with Wikipedia pages share your birth day of year, how many were born on the exact day as you, the same month/year, and same year
- All you need to do is enter your birthday and look… there is no further need for interpretation
- The area chart stayed but the stacks had to go. The chart also tells a different story than before, building on the fact that the dashboard is simply a story about you. We can now see the total growth of births on your birth day of year.
- Background was reverted to a dark gray to add the same pop that the orange viz had. The original was striking to look at, and I didn’t want to let that fade away.
- Since you’ve made it this far I’ll let you in on a secret… the Data Duo actually wanted me to use a white background… I was floored.
- Interactivity has been improved if you do want to explore
- Hover actions have been placed on the strip plot and area chart to let a user see who shares their birthday, but on a different year.
- Color has been used sparingly, and honestly isn’t even needed. If we were to push this chart to grayscale, the story stays the same, bright blue was added simply for design.
Overall, I chose this viz as an exercise in user interaction and color. I was going for high impact in 2015, and consistently trying to do things in Tableau that were out of the common realm… looking back I’m seeing some of the trash that mindset let me to produce. I’m hopeful that the new visualization can hold its own against its orange brother… I’m afraid blue is going to be looking up at those view counts for a long time to come!