Tag Archives: Data Visualisation

Daily Mail pie chart fail, a crime against data visualisation

I have a love/hate relationship with pie charts – when they are used well, they are a brilliant way of showing proportions (x is bigger than y, which is bigger than z) and seeing where a particular slice fits in as part of the whole (mmm pie). I’m certainly not the first person to wax lyrical about pie charts, I’m aware that Nathan Yau has demonstrated a good use of pie charts and I totally agree with him.

However, as I was browsing the web this morning, a story caught my eye in The Mail (don’t judge me) about Britain’s crime hotspots and how Stratford in East London is awarded the country’s worst crime hotspot (I was a Games Maker at the 2012 Olympics and Stratford is very much of interest to me). And then I saw THIS MONSTROSITY…

Daily Mail Pie Fail

Daily Mail Pie Fail
Source: Daily Mail

WHOAAAHHHHH THERE – I’ll give you a couple of minutes to digest that beauty.

This is a perfect example of why I also hate pie charts…I think it should be reported to the data viz police.

Here’s a few of the problems:

  • It contains far too many slices – it’s information overload and it’s really hard to compare categories, it’s just a sea of labels.
  • It’s 3D which really isn’t the best way to project proportions as they are liable to misinterpretation; I can’t really say it any better than Drew Skau on the wonderful Visual.ly blog.
  • It’s not in any order, again making it harder to read (I personally prefer a pie chart in descending order with highest proportion first).

In fact, I think it breaks every rule in this Eager Eyes piece.

So I thought I’d see if I could improve it by turning it in to a bar chart instead…

Bar Chart - click to enlarge

Gosh, that looks much better! It’s in descending order and so is easier to compare categories and to see the categories containing the most/least offences. It’s probably not the prettiest chart but it’s what I could muster up in Excel in 10 mins.

It’s really interesting data and it’s definitely a set I’d like to explore more – for example what would fall under “Other theft”? I’d also be interested to compare these stats to a time when an average 130,000 people weren’t visiting the area every day for four weeks (the amount of people visiting for the Olympics & Paralympics have to skew the figures right?). But that’s for another time. My goal was to make the Mail’s pie chart easier to read and to allow proper dissemination of the data and I think my solution is definitely a step in the right direction!

Week 5 & 6 – A topic of our own

For the final week of the MOOC, we have been given the task of producing an infographic of our own – this means choosing a topic, gathering the information and presenting an idea to show the information in graphic form.

As my previous sketches have been for interactive infographics, I wanted to give a static graphic a go. Having so much freedom was pretty hard – there is a wealth of information and data out there, but choosing which story to go for and what angle to take was going to be hard! It was lucky then that I got a tweet from the team behind the BBC iPlayer pointing me to the latest performance report and that is when inspiration struck.

The BBC produce these performance reports every month and I read them with interest – I am a stats geek and love stuff like this. The report gives stats such as the viewing figures for content on iPlayer, popular programmes, usage by device type and the gender/age group of users. It’s a wealth of information that I find fascinating. But I also love it because it’s about the iPlayer – something I use for at least two hours a day and have a certain affection for, it’s brilliant. For non-UK residents, the iPlayer is a service that the BBC officially launched at the end of 2007 and allows viewers/listeners of BBC TV programmes/radio shows to replay missed content and to watch shows live via the internet. The iPlayer is available on PCs, tablets, mobile phones, via Smart TVs and via cable operators. In essence, it’s brilliant.

I am fairly certain that the report released by the BBC is not aimed at the typical iPlayer user – it feels more for those in the media or for those who have a specific interest in audience figures and so my goal for the infographic was to produce something that everyone could appreciate. Luckily for me, October was a record month for iPlayer usage with 213 million requests for TV or radio content – breaking the 200 million request barrier for the first time and so I had a nice little slant for my infographic. It also meant that the story had been picked up the press too:

BBC iPlayer tops 200 million monthly requests for first time – Digital Spy

iPlayer passes 200 million monthly requests for the first time – Digital TV Europe

Merlin and Jimmy Savile documentary help BBC iPlayer to record month – The Telegraph

BBC enjoys record iPlayer requests in October – Cable.co.uk

…but no-one had produced an infographic, and so I felt it was my duty to produce one to celebrate!

My goals for the infographic were as followed;

  • Produce something for everyone – using the stats from the October performance report but make them easier to read and emphasise their relevance.
  • What were the most popular shows in October? Why did it break the 200 million request barrier in October and not, say, during the Olympics?
  • Who and what is using the iPlayer service? What proportion of requests are coming from tablets?
  • Make a static graphic that could serve as a template for every performance report so that non-industry readers could glean the key information easier on one page as opposed to trawling through the report.

And so with all of this in mind (and not a lot of time to complete the task – despite two weeks to work on it, December is a crazy busy time at work!), here is what I have come up with…

October 2012: A record iPlayer month for the BBC (PDF)

Notes about the graphic

  • This is a static graphic which uses the figures from the October 2012 iPlayer Performance report but could be used as a template for other monthly reports.
  • I extracted the information that I thought would be interesting such as iPlayer requests since 2009 (as far back as the report goes), the gender breakdown of users, the devices used to access the service and the popular TV and radio shows in October. I have also put a few stats in the blurb at the top.
  • The graphic style is largely similar to my last task with minimal use of colour –  I stuck to pink as that is the predominant colour in the iPlayer branding.
  • If I had more time, I would have liked to explore the peaks and troughs around the end of 2010 and beginning of 2011. Do peaks relate to the release of iPlayer apps on mobile and tablet devices for example?
  • This graphic could be made interactive and this is a project I would like to work on in the future – especially to see the variation in the share of the device types – so watch this space! 🙂
I am pretty happy with this graphic but feel there are plenty more angles to explore with this data – but this is good as it gives me something to tinker with over the Christmas holidays. Now, do you think I’ve been good enough for Santa to bring me a copy of Adobe Illustrator?

Week 3: Sketch an interactive graphic

The goal for this week was to think about how an interactive graphic based on a particular report by Publish What You Fund, and also published in a Guardian blog, would look. The data in question relates to how transparent major donor organisations are with their own data and so each organisation has been rated using a distinct set of criteria created by Publish What You Fund, therefore producing an overall transparency index.

This assignment has really stretched me this week and made me take full advantage of the sketching/note-taking apps on my tablet as I found I was coming up with ideas in random places and needed to get them down for exploration.

My first task was to find out what the heck “transparency” actually meant and how it was actually measured and I was thankful that the data originated from a very well organised website. I then looked at both source websites and noted down what I thought was missing and how I would like to play with the data myself. This took about three or four days – and this is where a lot of sketching and brain storming came in; thinking of the “what ifs….” and “oooh how about I just change this…” scenarios.

I toyed with the data in Excel to see if I could find any interesting correlations such as splitting the data right down to individual indicators, looking at the annual resources and budget of each donor and in turn where the money goes but what I was really missing was information about the donor itself. I was very pleased to see the UK’s Department for International Development at the top of the list but in all honesty, I really knew nothing about them  and so I wanted to build that in to the graphic.

And so I started by jotting down potential graphs/data to include in my final interactive graphic and started arranging the sketches until I had something that I thought could work. Incidentally, I find jotting things down on paper like this so helpful as you invest very little time in it and it allows easy rearranging of elements – paper prototypes FTW!



From there, I installed the trial version of Illustrator CS6 and started playing around. To cut a long story short (it really was a long story as I battled with Illustrator’s graphs – I won in the end though!) I came up with the following design;

Aid Transparency Graphic (PDF)                  

Aid Transparency Graphic + Notes (PDF)

Notes about the graphic

  • The bar chart that can be seen at the top of the graphic can be manipulated by the buttons on the right hand side and the user can select to show the results of individual aid information levels or all of them (the total).
  • The user can also select to show particular countries instead of having everything on the graph which I found really hard to read in the Guardian blog.
  • If a user clicks on a donor’s name or the bar associated with that donor, the panel at the bottom will display additional information about the organisation. I added a space for some text about the organisation to add a bit of context and also a timeline to chart their major accomplishments so that users would be able to relate to an organisation’s particular focus. Both pieces of information could be scraped from donors’ websites and annual reports.
  • I have tried to minimise the use of the word “transparency” and instead used “openness” where possible as I personally wasn’t very clear about what this meant at first.

I am personally really pleased with this, as the work involved way more that playing around with a few graphs. I had to think about what I wanted to say, how I was going to represent it in a prototype form that would communicate how an interactive version of it would work. But I’m doing something that I love and time did indeed fly when I was tinkering all weekend!

Week 1: Introduction to Infographics and Data Visualization course

About a month ago, I signed up to a new MOOC offered by the Knight Center for Journalism. The course is run by Alberto Cairo and is exactly the sort of course I’ve been after for a while. As an aside, Higher Education institutions in the US seem to be way ahead of the game when it comes to MOOCs; I have completed courses via Coursera in the past and they have been fabulous.

Anyway, as part of my week 1 assignment, I have been asked to critique and discuss with fellow students the following graphic:

Week 1: Social Web Involvement

As with everything, it is so much easier to critique the work of other people and I realise that I will have fallen in to some common traps when creating my own graphics. Even viewing the first week’s lectures made me cringe at the screen as I am guilty of a lot of them. But that’s why we go on courses right? But the most important point I learned was to stop thinking like a designer and think like a reader – does the graphic convey its point within three seconds?

Do I think the graphic satisfies this? No, not really. If I’m honest, for the first three seconds it did grab my attention and if I’d seen that in a newspaper I probably would have stayed on the page and wanted to explore it. However, it’s only when I delved a bit deeper that I realised how difficult it was to decipher.

So what does the designer want me to do with the graphic? Well, it’s definitely not being used for a geography lesson, as the label for the UK is far up in the North Sea and Germany is over in Russia. The only real clue as to what the graphic is about is the title, “Social Web Involvement” and the rubrik in the bottom right hand side attempts to describe it. However, it is not clear what the sizes of the donut charts mean and also what the millions of users in the tables mean. We are told that 32,000 people were interviewed (2,000 per country) and so where the heck have these figures quoted in millions come from?!?

The graphic does present several variables, but it does not present them very clearly. The variables come in the form of the countries and each type of social web involvement. The graphic does not allow for comparisons, organisation or show correlations easily as the data is bunched by country and so it is not easy to find, for example the country with the second highest proportion of people writing their own blogs. The details are scattered around the graphic and a reader has to memorise the data in order to compare it. There is a lot of redundant grey space on the graphic which could have been used more efficiently.

I would improve the graphic by removing the map completely and just concentrating on the data. The data we have can also be sliced and diced with other data, for example the GDP of the country, the population (Internet users per 100,000 people) or we could look at other methods of social web involvement – why are there no games mentioned when according to Wikipedia there were 10.3 million players of World of Warcraft in May 2011? As a start, I would go back to basics and just ask the question: How does social web involvement vary by country to country?

Let’s take the UK as an example (edited a wee bit to fit):


We could represent this data in a bar chart that could easily be compared to other countries. Of course, sixteen of these graphs may look a little cluttered but I think this is a step in the right direction.


If we wanted to develop this idea and wanted to just focus on one particular aspect of social web involvement, all categories could be greyed out and just one particular item focused upon.


These alteratives are most definitely still a work in progress but I think immediately they are a lot clearer to read and allow the data to be compared and organised a lot easier. Having read the forum for the course, I see that someone else has had a similar idea and created a stunning graphic -> http://www.flickr.com/photos/89317425@N05/8133822514/ so it’s good that I was thinking along similar lines and hope to keep developing my skills as the course progreses.

Data Viz Squirrel

Data Visualisation, Data Viz, Infographics and ‘making pie charts look pretty’ seems to have sky rocketed within the past couple of years. Despite studying database development during my final year of University in *ahem* 2003 and constantly being surrounded by lovely data (whether at work or on the web) I had never really paid much attention to it. I gawped at the screen when I discovered Information is Beautiful (and then ordered the book right away), yet it still hadn’t twigged that this was something I could try for myself, thinking it was only for graphic designers and not a lowly techie like myself.

My moment of epiphany came in 2011 when I was looking for a course to attend – I don’t have a huge training budget at work and so that ruled out any MSC qualifications but I wanted to try something a little bit left-field but which was still related to my job. This is when I discovered Andy Kirk’s ‘Introduction to Data Visualisation’ training and thought I’d give it a go – after all, if it wasn’t for me I’d still get a free trip to Brighton (yippeee!)

The training was fantastic, so much more than I had imagined as it started right from the beginning – it assumed no prior knowledge and covered all aspects of visualising data. Attendees were from a variety of backgrounds: designers, coders, database developers and I finished the day feeling incredibly inspired (you should see the mad scribblings I made in my notepad on the way home).

No more boring pie charts for me – hello stunning data! 

Fast-forward a few months and data visualisation is still at the forefront of my attention. I am overloaded with all the wonderful resources on the web about it; be it free tools, design tips, data…oh the lovely data, tutorials or books. You should see the “Data Viz” folder in my favourites – I’m like a squirrel hoarding the links.

I am a data viz squirrel; hoarding links for the winter.

Well, this is why I have set up this site, I LOVE to play and tinker but will then often finish something and then move on to something else. I have coded Python for the first time, created a Choropleth map of English Counties, I have screen-scraped, made a Heat Map and created my first visualisation for publication. I want to document this work, my thoughts, discoveries and processes so that I can keep a log of everything I have worked on. I have seen some wonderful tutorials online that don’t quite fit what I want to do and so I have modified them and now want to share them. I have so many ideas for blog posts and so many people to credit that I can see this site expanding very quickly!