#MakeoverMonday got shortlisted for the Kantar Information Is Beautiful Awards

What an honour! #MakeoverMonday has been shortlisted for “Best DataViz Project” in the Kantar Information Is Beautiful Awards.


If you’ve enjoyed the project, please go vote for us.

Click this link and press the grey vote button (note that you can only click the button once per category, so choose wisely! subliminal messaging: choose MakeoverMonday! )

It’s really been an astonishing year and this project has blown me away.

It’s not about us. It’s about community.

Andy and I predicted it would be a small thing and nobody would care. But then 372 people got involved over 38 weeks. WTF? 54 makeovers a week? Amazing.

Some highlights

Go and look at the Pinterest board: look at the depth and variety of ways to visualize data. When people blog about the impact the project has had, you get the sense it’s really changing the way people work. (Neil Richards and Michael Mixon are two great examples)

Kids are getting involved. Children: enthused by data.

I’ve learnt a lot about how to criticize constructively.  We’ve had some great thoughts on whether things should be complicated or simple.

Who knew that China was the world’s biggest grower of peaches?

Or that a TEU is a measure used by the shipping industry?

Each of the 38 datasets has taught us something. Whether it’s serious or not, participants are learning about the world each week.

#MakeoverMonday live at Tableau Conference in London

We’ve done this live many times and the experience is amazing. You should do it too!

Comcast put MakeoverMonday as a prerequisite in their job descriptions! What? Amazing.

The highlights are long. Andy and I would like to thank everyone who’s been involved in such a rewarding project.

Sounds great! How do I vote? Click here.

#MakeoverMonday: Peaches


When Andy and I were discussing future topics, we were considering the Global Peace Index. I mistyped it as the Global Peach Index. “Wait a minute, that sounds fun. What if there is data on the peach industry?”

And here we are with data on global peach growth.

On the first exploration of the data, the massive domination of China pops out. Below is the percentage of peaches grown in China. >30% of all peaches in 2012.


“But China’s huge. And populous,” I though. And that led me to bring in population and area. Do that and you realise that while China’s clearly growing loadsa peaches, and has been increasing its growth in the last two decade, it’s Greece that’s the biggest relative to are and population.

All of which is a good way to say that in data analytics: think about the contextual implications of each measure in your database.

The original


This week’s source from FAOSTAT is kinda standard fare. Things I think could be improved:

  1. The colour bins have very specific boundaries. I’d rather see them fitting round numbers. This mapping system has to fit all FAOSTAT datasets, so I suspect there’s some automation going on here.
  2. The map has ocean depth and land cover detail. That’s too much detail. Why should I be interested in ocean depth when looking at peach production?
  3. The line chart updates when you select a country, which is nice, but I’d rather also see the title update, otherwise it’s not obvious if you did select anything. There is a country line legend right at the bottom, but I didn’t spot that.

Here’s the horizontal version of the makeover:


MakeoverMonday: World’s biggest data breaches

This week we’re tackling one of the interactives from Information Is Beautiful.

I struggled with this week’s makeover. I couldn’t find any great way to retell the story to the level of detail of the original. In the end I decided to exclude detail and focus on just the growth the hacking and what that means for me and you. Personally, I am a huge fan of Lastpass and recommend everyone to use it or an equivalent.

I spent a long time trying to do a remake but in a “better” way than using circles.

I tried a stacked bar:


The problem? There’s less detail than in the original and it’s not engaging.

I tried a treemap bar (which you can interact with here):


The problem? A treemap is a part-to-whole, and this dataset is only selected breaches. I do like this chart, but because the tree implies part-to-whole it’s not acceptable.

In the end, after more time than I had available to spend on the makeover this week, I figured I’d have to find a simpler, different story and focus on hacks alone:


My conclusion? The original is a very good way to prioritise access to all the data over ease and accuracy of comparing each breach.


What I like

  • It’s engaging. That makes me want to explore it.
  • There is detail, in the form of a short sentence to add context, when you click on a circle.
  • It works well on mobile (the vertical timeline is becoming more prevalent as we move to mobile).
  • I like the interactivity: switching bubble size and color for different categories reveals different insights.

What I dislike

  • It isn’t easy to accurately compare the difference in size of different circles. If the prime purpose is to show differences accurately, then you’d need to use bars. Since that wasn’t the prime purpose here, this isn’t too big a problem.
  • There’s a lot of overlapped marks. A border appears around each circle as you move your mouse over it, making this less of a problem. Making the marks transparent is another possible solution.
  • You can choose to colour the bubble by year, but the “Interesting story” color overrides that, confusingly.


The little of visualization design: grouping with colour

[I’m shamelessly stealing the idea for “the little of” from Andy Kirk. His series has been amazing]

Yesterday in MakeoverMonday we tackled the worldwide shipping industry. Today the Economist shared a chart about the same topic (above). I highly recommend you also read the full article as it’s about an industry trying to save itself through the use of better data.

What’s I like in this chart is the “Proposed alliances” blocks next to the company names. The primary question in the story is the size of the shipping companies. The secondary question, dealt with in the second half of the article, covers alliances. They designed the chart so you can get on with answering the primary question without the initial distraction of the alliance information.

If I’d designed this chart, I’d have probably coloured the whole bar according to the proposed alliance. I’ve mocked that up below.


What’s the problem? You can’t escape the colours. You see the colours before you answer the primary question. What the Economist did was keep simple bars that allow the primary question to be answered first. Once that’s dealt with, you can examine the alliance colours and focus on the secondary question.

MakeoverMonday: global shipping companies

Pareto: do you understand what this is showing?

This week’s original looked so simple, I thought it would take just a few moments to whip up a bar chart. Then I figured that was too obvious. And then I got lost in a fascinating voyage of discovery finding out about the global shipping industry. I never knew capacity was measured in TEU (ie a container). And who can resist looking at images of enormous container ships? Maybe you can, but not me.

Reading about the industry soon pointed out just how dominant those top 20 companies are. Which led me to the Pareto. I’d enjoyed Andy K’s tip on Paretos last week, so they’re on my mind. I don’t actually think we really need a pareto here. In this case, the more compelling view is  the basic bar chart. A simple annotation saying that the top 20 companies account for 90% is enough. It’s easier to read that information than understand it from a pareto.

Or is the bar easier and more compelling?

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#MakeoverMonday: Alan Rickman

Alan Rickman

Just a quick one this week. Alan Rickman’s career was lauded, justifiably, when he died earlier this year. However, I hadn’t realised until tackling this week’s makeover just how much it had been dominated by Harry Potter.

I only have time for a very quick post this week. One thing I did do was to orient the bar chart the opposite way to normal (header on right, bars pointing to the left). Why? Because the photo of Severus was facing to the right – I wanted the makeover to look like Severus was looking at the chart itself.