Data Viz Done Right

July 28, 2016

Bowdoin vs. Vassar: An Analysis of Malcolm Gladwell’s Revisionist History Podcast

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Malcolm Gladwell, one of my all-time favorite authors, recently started the Revisionist History podcast. In his typical style, it is absolutely amazing!

"Each week for 10 weeks, Revisionist History will go back and reinterpret something from the past: an event, a person, an idea. Something overlooked. Something misunderstood."

In the middle is a three-episode series about education in the United States. One story in particular caught my attention and, coincidentally, I happened to listen to this podcast on the same day that The Data School was working on their dashboards based on the College Scorecard data.

Here’s Gladwell’s summary of episode 5: Food Fight!

Bowdoin College in Maine and Vassar College in upstate New York are roughly the same size. They compete for the same students. Both have long traditions of academic excellence. But one of those schools is trying hard to close the gap between rich and poor in American society—and paying a high price for its effort. The other is making that problem worse—and reaping rewards as a result.

In the spirit of not accepting statements as fact, I decided to create this visualisation comparing the two colleges. In every section I start with a similarity then next to it I point out a difference. This really helped me compare the schools and confirm much of what Gladwell spoke about in the podcast.

July 26, 2016

The Functional Art - A Tableau Book Cover

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About 3 1/2 years ago Alberto Cairo came to give a talk at Facebook. It was an incredible talk and immediately after I built a viz about how he built his book cover for The Functional Art. One thing bothered me when I built it though; I wasn’t able to include the vertical lines like he did…until this past weekend when I finally figured it out.

So today, while The Data School works through their next dashboard during Dashboard Week, I decided to build it again, this time with the vertical lines. I had to do a lot of finagling with the mark labels. Click on the image below to view the interactive version.

Tableau Tip Tuesday: How to Add Vertical Lines to Slope Graphs

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In this week’s Tableau Tip Tuesday, I show you how I created a slope graph that includes vertical lines. I really like the addition of the vertical lines as they add structure to the overall look and keep the viz neatly aligned. This was originally posted as a Data School Gym challenge, which you can view here.

July 25, 2016

Makeover Monday: Bermuda Population Growth

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Following on from last week’s discussion about Makeover Monday and what might be keeping people from participating, Andy and I are committing ourselves to keeping our visualisations simple and quick. The data set provided this week has A LOT of census information included, but I focused on the data from the original post. Here’s the original from Rhiannon Fox, a graphic designed based in Bermuda.

I spoke to Rhiannon about her work and I’m hoping she becomes part of our teaching curriculum at the Data School. She’s very excited to see what everyone comes up with.

What works well?

  • I love the colors
  • Simple, small multiples layout
  • Great fonts
  • Great labeling
  • Consistent use of shapes for the unit charts
  • Neatly organized in a Z-pattern from oldest to most recent
  • Population growth is easy to see

What doesn’t work well?

  • A unit chart sacrifices accuracy for engagement.
  • The overall pattern is harder to see than it needs to be.
  • It’s too difficult to compare females from year to year.

Given what I like and don’t like, and sticking to the one hour time limit, I decided to go with a diverging bar chart, also known as a back-to-back bar chart or a bikini chart or a population pyramid.

July 23, 2016

The Data School Gym - Slope Graphs with Vertical Lines


It’s my birthday, so what else would I be doing other than practicing Tableau and having a cold beer? I’m working on a project (more to come in a couple months) and needed a way to create vertical lines in slope graphs that are based on dimensions.

So here’s your challenge. Given this data set of fruit sales by region, build this slope graph. If you can’t access the data, email me and I’ll send it to you.

Some formatting tips:

  • I used Avenir Next Condensed for the font - 18pt title, 12pt in the chart.
  • The decreasing value is highlighted with color #E15759 and the increasing values are using #A5ACAF.

This was a fun little challenge for me. You’ll likely either get it immediately or get stuck. Upload your answer to Tableau Public and leave a link in the comments. Have fun! I need to get back to my Punk IPA.

July 21, 2016

Downloads vs. Vizzes - Why aren’t people sharing their Makeover Monday creations?


A couple weeks ago, I started using a shortlink service for the links to the Makeover Monday data sets. Each week I publish both a flat file (Excel or CSV) and a Tableau Extract. When Andy and I started this, we figured a TDE would be the easiest way for people to start. But I was wrong…well, that’s assuming the last 2 weeks are representative of every week.

To our surprise, people are using the Excel files at about a 2-to-1 rate to the TDE. That was surprising enough; I just assumed people would use the TDE because it’s simpler.

And look at those download numbers! 285 people downloaded the week 28 data and 219 have downloaded week 29 (as of this writing). I combined that with the number of vizzes uploaded to Twitter for those weeks and tagged #MakeoverMonday.

Yes, you’re seeing the same thing I am. We are getting an incredible number of submissions, but pretty small compared to the number of downloads. To give the situation a bit more context, consider this visualisation:

I’m curious. Who are these people that are downloading the data, yet not sharing their work? Do you have any ideas as to why aren’t they sharing their work? I don’t have the answer. I’m hoping you, the Community, can help explain this. What can we do to encourage more people to share their work? Are we doing anything that may be putting them off?

Please share your thoughts in the comments below. Thank you!

July 19, 2016

Tableau Tip Tuesday: Layout Tips for Long Form Dashboards


In this week’s tip, I look back at the Makeover Monday dashboard I created for week 29 and some tricks I learned about designing a long form dashboard.

Tap for the tutorial

July 18, 2016

Makeover Monday: Home of the Free - Land of the Walking Dead

Click for interactive version

This week’s Makeover Monday is a bit morbid, as pointed out to me by David Pires. Regardless, it’s a fascinating data set and often a devisive political topic in the United States. The data for this week come from The Death Penalty Information Center Exectution Database and the charts of reference come from The Marshall Project.

I’m going to review all three visualisations. Let’s start with this map:

What works well?

  • Clearly shows which states have carried out executions most recently
  • Easy to understand
  • All states are given equal weight
  • Neatly organized

What doesn’t work?

  • No sense of the number of executions
  • States are weirdly placed (e.g., Why is West Virginia so far south)
  • Doesn’t provide much context

Next up is a stacked bar chart of executions by race (or method) over time.

What works well?

  • Great summary and explanation above the chart
  • Easy to understand
  • Neatly organized
  • Flips neatly between race and execution method

What doesn’t work?

  • Colors are a bit tough to see against the dark background 
  • Stacked bar chart makes the trends hard to see except for the overall and whites (for the by race view)
  • For the by method view, it would be better to have lethal injection at the bottom of the stacked bars since it’s the largest. 

The third chart is a line chart showing the volume of exections by state. This is the chart that first caught my attention.

What works well?

  • Nice summary table
  • Easy to understand
  • Nice description to go with the chart

What doesn’t work?

  • The logarithmic scale is very misleading and isn’t called out.
  • The colors are way too hard to see against the dark background.
  • My eyes have to go back and forth between the chart and the table to know which state is which. 

As for my visualisation, I decided to take some advice from Rob Radburn. At a recent London TUG and against during the Zens on Tour event, Rob spoke about how he gets inspiration from visualisations and how that influences what he designs. In essence, he says to “Steal Like an Artist”. So that’s what I did this week. A quick Google search for “death row infographic” and I had three visualisations that I could borrow from and combine into my final version. They are this one and this one from Huffington Post and this one from

I felt an infographic was the best way to tell the story this week. I hope you like it.

July 12, 2016

Tableau Tip Tuesday: How to Use Actions To "Reset" a Chart to the Most Recent Date

This week’s tip is based on a tip written by Richie Fanti back in 2013 when he worked for me at Facebook. In essence this tip shows you how to use a dashboard action to “reset” a chart to show the most recent date after you clear the action. It’s a really useful technique when you want the default view to be the most recent date but you want the user to be able to see details for a specific date when they click on it.

If you have any questions, leave a comment below.

July 11, 2016

Makeover Monday: The Orlando Mass Shooting & the Reaction of Representatives

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As a second take on the Makeover Monday topic this week of what legislators spoke about after the Orlando mass shooting, I thought a better view might be the proportion of representatives who spoke about each topic. Presenting the data this way help provide better context for the overall picture while allowing you to compare both across the parties and within a party.

I think a donut chart works well here because we only have two parts to each donut and the number call out the amount that’s of interest. In addition, this enabled me to design a static visualisation that doesn’t require interactivity. For me, it’s much hard to design static, mobile-friendly visualisations than any other type at the moment.

Makeover Monday: What Lawmakers Spoke About After the Orlando Mass Shooting


This week’s Makeover Monday is a bit of a dark topic that gives us a glimmer into the how politicians in the US respond to a tragedy. Yes, this is a single mass shooting, but they occur nearly every day in America and the responses from politicians are now all too standard. The Orlando mass shooting likely got more attention because it happened at a LGBT club. This and other tragedies beg the question: When will America get its act together?

The chart that we’re reviewing this week is by the grapics team at The Washington Post.

What works well?

  • It’s neatly organised in a 3x3 grid.
  • The semi-circles are all sized relative to each other.
  • It’s very easy to understand.
  • They used colors that are automatically associated with the two political parties
  • Everything is clearly labeled.
  • It’s not over-cluttered.

What could be improved?

  • The chart implies that there are equal representatives in both parties. However, Republicans have 247 seats while Democrats have 187.
  • Using semi-circles makes the shapes hard to compare.
  • It's difficult to compare across the topics.
  • There should be an easier way to which party talks more about each topic

Given these changes I would like to see, I’ve create this version that shows how many representatives talked about each topic in a tornado chart format. I then included a circle with a number inside to show which party talked about the topic more and by how many representatives. Lastly, I added lots of summary details in the tooltips.

July 6, 2016

Dear Data Two @ Zen on Tour

Today was my day to keynote Zens on Tour. Louis Archer asked me to present about Dear Data Two because he had heard about it during a recent London TUG. I was able to record most of it…for some reason it cut off near the end so apologies for that.

Below the view are the slides from the presentation. Enjoy!

You can find all of my Dear Data Two here and all of the combined work from Jeffrey and me here. I refer to four specific weeks in the presentation:

  1. Week 34 - Urban Wildlife
  2. Week 31 - Positive Feelings
  3. Week 24 - Doors
  4. Week 26 - Workspace

July 5, 2016

Tableau Tip Tuesday: How to Swap Between Colorblind and Colorful Dashboards

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This week’s Tableau Tip Tuesday came about from a question during the panel discussion portion our Zens on Tour event in Edinburgh yesterday. Zen Master Craig Bloodworth came up with a very elegant solution that I’ve built upon.

This is super handy for those that need to build dashboards for accessibility purposes.


July 4, 2016

Makeover Monday: Where Are the Best & Worst States to Raise a Child in America?


This week the UK Zens are on Tour and we’re taking Makeover Monday on the road with us. And it’s Independence Day in America so I chose a visualisation about raising children in America. Happy birthday ‘Merica!

What works well?

  • Nice big titles make it easy to know what the map is about
  • The colors make is easy to see the good and bad concentrations.
  • Alaska and Hawaii are neatly brought in under the continental U.S.

What doesn’t work?

  • The ranges for the colors are equivalent.
  • Using a filled map could lead to visually distortion; poor Rhode Island!
  • The separate maps that you have to page through make comparisons too difficult.
  • There’s no way to see a State’s ranking in all categories at once.

I iterated through lots of ideas this week and found two that I think work well.

  1. I changed the filled map to a hex map then put all of the maps side by side.
  2. I created heat maps and bump charts that show the individual State rankings in each category.
  3. I added bar charts in the tooltips.
  4. I included highlighting interactivity. 

Both views are shown below. Which one do you prefer?

July 1, 2016

FFS Friday: Which SEC Teams Lost the Most Offensive Production?

There are just too many visualisations screaming out for makeovers. Following on the huge success of Makeover Monday, I’ve been occasionally sprinkling in other days, like #WTFWednesday and #FixItFriday. But Fix It Friday didn’t really do it for me, so today I’m changing it to #FFSFriday. Not sure what FFS is? Google it.

Today I’m going to look at this viz from Saturday Down South.

What works well?

  • Clear title
  • Including the % returning for context
  • Using team colors
  • Sorting works well
  • Using the team logos instead of the names

What doesn’t work well?

  • Because the bars themselves aren’t sorted, I find it a bit hard to follow
  • Including all of the numbers clutters the viz
  • The title, while clear, doesn’t tell the story as well as it could.

For my version, I changed the story to be about the teams that lost the most offensive production. The tooltips help to provide the addtional content, moving the numbers out of the visualisation and reducing distraction.

If you’d like to give this chart a makeover, you can find the data here (XLS) and here (TDE). Then post an image on twitter with the hashtag #FFSFriday. Most importantly, have fun!

June 29, 2016

WTF Wednesday: Misconceptions About Muslim Population


This morning I was going through the backlog of Makeover Monday candidates that I have saved in Pocket and it’s quite an extensive list. So I thought I’d knock one off the list and start up #WTFWednesday for those of us that just can’t have enough Tableau in our lives.

For this makeover, I look back at this viz from The Guardian about the misconceptions about Muslims by Europeans. If you’d like to have a go at it, the data is here (XLS) and here (TDE).

What works well?

  • It’s neatly organised by the amount of misconception
  • Colors follow Guardian standards
  • Nice title that sets the story

What doesn’t work well?

  • When I first read it, I assumed the darker blue was the average guess, but that’s not the case. This should be made clearer.
  • Comparing countries could be made easier
  • Stacked bars with overlapping labels look very cluttered

I didn’t want to spend a lot of time on this so I decided to make a simple barbell chart sorted by the largest misconception. This was also the first time that I’ve put bar charts in tooltips, which works well for allowing the user to see the precise values.

June 28, 2016

Tableau Tip Tuesday: How to Display KPIs Next to Bars


This week’s tip shows you how to perfectly positive KPIs next to bars irrespective of the dimensions in the view. This started as a Data School Gym Challenge if you’d like to have a go at it before you watch the video.

June 27, 2016

The Data School Gym - Displaying KPIs Next to Bars

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Here’s another Data School Gym challenge for you. I’ll create a video tomorrow for how to solve it. First, let me explain the problem.

I’ve written before about how to use ASCII indicators to compare to a goal.

But there are times when we might want the indicator as part of the chart next to the bars. Start by creating a year over year comparison like this:

Then create a calculated field as a placeholder:

Add the Placeholder as the secondary axis and synchronize. Then create a calculation that compares the two years:

Change the mark type to shape for the Placeholder axis and add the comparison calcuation to the Shapes shelf and the Color shelf. Change the shape and color to something more meaningful.

Then right click on “True” on either the Shape or Color shelf and choose “Hide”. This cleans up the viz nicely. Go ahead and hide the secondary axis while you’re at it.

Ok, looks good. However, what happens when we add another dimension?

The indicator is fixed to -50,000 so now there’s a wider gap between the indicator and the bar (because the value of the primary axis is smaller).

Here’s the challenge:

Notice how in each of the screenshots below, the arrow is always precisely the same distance from the left side of the bar. That’s the tricky bit.

You can download the same version of Superstore Sales that I used for this example here.

Makeover Monday Week 26: Who? When? What?

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For Makeover Monday week 26, we challenged the Community to create a great dashboard that tracks the who, what and when of the project. Let’s start by looking at my original dashboard:

What works well?

  • It’s easy to see how many contributions have been made and how many people have contributed. 
  • The colors are good, but not great. 
  • The word cloud helps highlight the volume of people that have contributed. 
  • You can easily see which weeks had the best participation and which weeks drew the most new people. 
  • The heatmap on the 2nd tab does a good job of letting people see which weeks they have yet to complete. 

What doesn’t work?

  • It’s too hard to see the overall figures. 
  • The 2nd tab should be incorporated into the first. 
  • The word cloud is too busy. 
  • The cumulative graphs don’t provide much insight. 
  • All that’s important is the final number.
  • I don’t like the combination chart on the upper left. 
  • There’s no interactivity. 

I built my makeover in Tableau 10 so all I can post is an image. If you’d like to have a look at it, you can download it here. I’m really excited to see what the Community builds. I’m 99.9% sure someone will come up with something that blows us away.

June 26, 2016

Makeover Monday: Week 26 - Dashboard Design Contest


Wow! We’ve made it to the halfway point of Makeover Monday! Andy and I are so overwhelmed by this little social data project of ours, and by our project, I mean the Community’s project. Y’all are awesome!

So for week 26, we thought we’d have a little contest. I created a rather rudimentary dashboard to track the who, when and what of Makeover Monday, but I know you can come up with something better. For week 26, we’d like you to makeover the Makeover Monday dashboard.

Andy and I will review all of the and pick our favorite sometime this week. We’ll send that person some Information Lab and Tableau swag. I don’t know what we’ll send you yet, but that’s besides the point.

You can download the TDE here or XLS here. The data is as of 12:45pm Sunday 26 March. If I’m missing anything, tweet me and let me know. Good luck!