#MakeoverMonday: Tax Havens

tax havens

$2.1 trillion dollars? We are used to hearing monetary values like that, but what does 2.1 trillion dollars look like? It’s such a huge number, I thought it would be good to relate it to other types of expenditure.

It is astonishing that the offshore money is 2/3 the size of the entire US federal budget.

This weeks source was in need of a makeover. Pie charts aren’t a great way to show this data (read Stephen Few’s classic “Save the pies for dessert” for a great explanation). Making a pie with so many slices renders everything virtually unreadable.

European Disc Golf Championships day 3


Loved the battle at the top of the Masters today – Kristian held on so well for 2.5 rounds but just lost it towards the end, allowing Anders to draw level.

Holes change by round
Click for interactive version (and narrow this down by division).

Let’s look at how the holes have changed over the rounds. Is hole 16 the most boring? Sure looks like it: the most pars and very few birdies. Holes 1 and 5 have given up the fewest birdies. 

How about the gold/brown rounds? Here’s team GB. Derek Robins had a difference of only ten between his gold/brown rounds. Well done!

Click for interactive
Click for interactive version to find any gold/brown rounds.

How about some player profiles? Here’s Team GB’s Chris O’Brien who’s been playing brilliantly… over 2 days and had a bit of a shocker today.

Click for interactive version.
Click for interactive version (and to look at any player in the tournament).




European Disc Golf Championships Day 2

Another cracking day, judging by the scores. The leaders were having a good old ding-dong battle. Pasi faded at the end of the second round, but Juho stormed on through:


Players clearly learned a new approach on hole 1 today. In round 1, there were around 60 pars and over 100 over pars. Today? More people got par than any other score:

Hole 1 different rounds

Now – what we all want to know is what are our Golden and Brown rounds? The golden round is when you take the best score of each hole and total that. The brown round is the opposite: what’s the worst score?

Here’s a static image, but the interactive version is below:

Golden and Brown


Finally well done to Team GB’s junior, Ned Morris, who had a great second round. Look at that steady-as-a-rock run of pars from holes 9-16:

Ned Morris day 2

Ned – don’t worry about bogeying holes 16 and 18. Derek’s done the same in both rounds:

Derek round 2

European Disc Golf Championships

It’s disc golf analytics time! My friends are in Finland at the European Disc Golf Championships. Here’s some analytics for you to explore.

Each screenshot has a link to the interactive version.

First of all – you can compare players against each other. Here’s team GB’s progress through round 1. Chris O’Brian did extremely well, while Derek, Dan, James and Si all ended up within 1 shot of each other:

player battle
Interactive here

How about the holes? Well, hole 1 was brutal. 4 birdies and >100 bogeys or worse. Ouch. Hole 4 was the opposite: 40% of all players birdied it today.

Hole 1. Ouch
Hole 1. Ouch. Interactive
Hole 4. Phew.
Hole 4. Phew. Interactive.

And how did the Open division do in terms of Birdies/Bogeys? Well done Pasi Koivu for getting 11 birdies! Amazing.

Open player birdie/bogey ratio
Open player birdie/bogey ratio

Tableau 10 bonus features: Assign highlighted colours to a palette


Check this out. I’ve been using Tableau 10 for months and months, and only discovered this feature today. If you highlight an item in the colour legend, and then right-click, you can set the color palette to be the highlighted state.

This is great for people who like to export static images a lot. Animated GIF below:


MakeoverMonday: Malaria

We’re hoping to bring attention to work helping fight malaria. Go check out how you can help #VisualizeNoMalaria here:

Malaria deaths in Africa


I found myself doing something simple and possibly too experimental. I looked at which countries are seeing growth and decline in Malaria deaths. It turns out that, for the countries with good data, there’s a balance of impriving and worsening countries. Overall, the number of deaths has been pretty static since 2001. Not great news.

My original layout was horizontal but I couldn’t get the country labels to align nicely or fit, so I went for the vertical layout, even though “you should never do vertical time series.” Well, I just did. Below is the horizontal version:

Malaria deaths in Africa (horizontal)

MakeoverMonday: triple whammy of balls, medals and lipstick

I’m back from vacation and in catch up mode, so here is 3 weeks of MakeoverMonday with super-fast summaries of each one. A lesson from catching up like this is that time pressure really helps keeping things simple and thinking about the simplest way to communicate a simple message. It forces you to condense your approach to the pure display of the data itself.

Week 31

Dashboard 1

The photo of Vinnie Jones and Paul Gascoigne is utterly fantastic. I realise that the mentions in this dataset relate to 2016 basketball, but, well, I couldn’t resist using the photo.

Week 32


I tried for a while to show the whole dataset in an interesting way, but I couldn’t find a way to make it feel interesting. I stepped back and noticed the 1920 spike in overall medals. A quick read on Wikipedia revealed the brilliant fact that 1920 Summer Olympics included a week of Winter Sports. Bonus fact!

Week 33

The UK Beauty Industry 2013-2014

Short on time, I went for a super simple nested bar chart. Looking up the information and comparing values is easy, which cannot be said of the original. The thing is, even if I had all the time in the world, I don’t think you could create a more effective display of the information than the nested bar chart.

#Throwback Thursday: share your OLD and GOLD Tableau blog posts

Tableau art from 2013

Rody Zakovich published a great post on using ASCII text in Tableau. In it he referred back to my old post on Bar Charts in Tooltips (which is nearly 6 yrs old!).

It got me thinking: what other pieces of gold (and not so gold) are languishing in our blogging past?

So I call on everyone to share their old stuff. Each Thursday, from this week, I’m going to share one of my really old posts. Some are still relevant, some are showing their age, and some are plain silly.

Join me! If you were blogging before 2013, what should we go back and read?

A classic from 2010!
Charts in a tooltip? Sure.


MakeoverMonday: The Bermuda Population


I am going SUPER-SIMPLE with MakeoverMonday for the foreseeable future! There are 2 reasons for this. Firstly, I’m finishing my book and also going on family vacation.

More importantly, it’s a response to comments in Andy K’s post about how many people are downloading the Makeover datasets but not publishing vizzes.

This one sums them up:


For people who feel intimidated about posting their work: I am sorry. Our intention with MakeoverMonday is to encourage everyone to share their work, in order to help them elevate themselves, whatever their skill level. I want to see people share the vizzes that DO take only an hour. Or less. This week’s took me 20 minutes. It’s a straightforward area chart with the colour scheme copied from the original.

If someone wants to spend hours on their Makeovers then that’s FANTASTIC. If people want to take the datasets and spend hours crafting amazing pieces of work, then I applaud that. I love seeing the amazing styles and approaches people take.

One look at the MakeoverMonday Pinterest board and it does seem to an arms race towards who can do the most elaborate work. Pam G said she stopped doing MakeoverMonday because “so many posts were all about the cool graphics being used and not so much about the charts themselves.”

So with that, here’s my plan for the next few months: I’m going to keep it simple and focus on the charts themselves. If you want to join me, then please do! I recommend you read Chris Love’s Keep It Simple post for more reinforcement of this idea.

Why did I choose an area chart this week?

The original viz was titled “Bermuda Population Growth“. I like unit charts, but this one made it hard to compare each year being shown. Taking the title as my cue, I wanted to make it easier to see the growth. I decided seeing total population was more important than the actual Female/Male breakdown. Therefore I chose an area chart: it shows the total at the expense of accuracy of the gender breakdown.

I’ll be keeping it simple for the next few weeks. Who else wants to join me?


Scribbles and lines: what does iteration look like?

Capital Punishment in the US

What’s the goal of analysing data? It’s about finding insight, and communicating that insight  in an optimal, engaging way.  

How do you reach that goal?

You don’t get there by first deciding which chart types you want and then adding data to them. Saying “I will start with a bar chart” and adding data to it  is the equivalent of trying to create a masterpiece with a paint-by-numbers set.

You do it by starting off with freeform exploration, improvisation, and shifting perspectives. We might try out 100 different views and keep only one. That single output will be powerful, but you’ll know it’s right because all the other views provide small contextual validations that you gained on the journey to the final output.

What does this look like? How about this squiggle?

squiggle narrow

The start is fast, messy and unpredictable. You’re failing fast and moving on. Over time you focus on the insights you’ve found and gradually hone in on the best articulation of the data.

What does the squiggle look like with real data? I got a chance to find out during MakeoverMonday, week 29, when we looked at data on executions in the USA. For a project being run by Tableau’s research team, I captured a screenshot of every view I made in Tableau (this was automated!). My analysis took 90 minutes. In that time, I built 302 different views of the data. The final dashboard is shown at the top of this post.

Here’s what the exploration looked like:

iteration 300ms

You can see all phases of the squiggle in the animation.

  • Rapid exploration at the start. During this phase I discovered the data had a similar shape to Simon Scarr’s Iraq’s Bloody Toll and decided that, based on that insight, I could base my final output on the design of that infographic
  • In the middle phase, there are periods of formatting the time chart interspersed with exploring afresh. I’m not restricted into doing one thing or another. As I play with the data, I get new ideas to go try out. I’m honing in on something, but still exploring.
  • Finally I spend a big chunk of time finessing the main chart. This is the phase when I’m trying to find the absolute best way to represent the data.

I created tables, bubbles, area charts, pie charts, sideways charts, ugly charts, and more. I threw most of them away. What the animation shows is what happens when an analyst is in the flow with their data.

I found this week’s MakeoverMonday fascinating. I have written many times before about exploration and iteration (e.g. here and here) but this GIF is the first time I’ve been able to truly see what exploration looks like. It’s the first time I’ve been able to validate that exploration can look messy from the outside but is actually hugely productive for the person doing it.


  1. The Squiggle is based on Damien Newman’s Design Squiggle. Newman applied the squiggle to design.
  2. The screen captures from Tableau were captured automatically. Only changes to the views themselves are captured. Titles, annotations, and laying out dashboards aren’t captured.