The little of visualisation design: Part 8

This is part of a series of posts about the ‘little of visualisation design’, respecting the small decisions that make a big difference towards the good and bad of this discipline. In each post I’m going to focus on just one small matter – a singular good or bad design choice – as demonstrated by a sample project. Each project may have many effective and ineffective aspects, but I’m just commenting on one.


The ‘little’ of this next design concerns creative thinking about the most meaningful orientation of a chart, in this case a scatterplot produced by FiveThirtyEight that shows analysis about the average favourability and unfavourability scores of a range of political names across the first few months of 2015.

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Rather than leave the chart in its typical y-axis up/x-axis across layout, it is rotated clockwise by 45° to draw focus on the relative mapping of the plotted records according to four meaningful quadrant regions within the chart, indicating the general popularity and profile of each politician. In particular, and substantiated by colour, there is vertical significance in being more popular (above the line) and less popular (below the line).

Although some readers may find it a little more challenging, as a consequence of this rotation, trying to read off the coordinate values compared to the more standard approach (simulated below), the presentational emphasis on the meaning of the position rather than the position itself represents an astute editorial choice.

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(See also this chart by Adam Pearce)

The little of visualisation design: Part 7

This is part of a series of posts about the ‘little of visualisation design’, respecting the small decisions that make a big difference towards the good and bad of this discipline. In each post I’m going to focus on just one small matter – a singular good or bad design choice – as demonstrated by a sample project. Each project may have many effective and ineffective aspects, but I’m just commenting on one.


The ‘little’ of this next design concerns a clever (but quite simple) way of helping to guide a viewer’s eye towards changes on a map between two points in time. This project from the Guardian plots the results of the UK Election in 2010 compared to the projected results for 2015 using adjacent cartograms.

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Only the constituencies that are forecasted to switch to a different political party are emphasised in colour – the exceptions – but it is the inclusion of the arrow and the shape outlining, as you hover over each area, to draw focus towards the related pairs that I find works ever so well.

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Think of this as the equivalent of using your arm/hand/fingers to draw attention to a key feature in a display if you were presenting a visualisation in person.

The little of visualisation design: Part 6

This is part of a series of posts about the ‘little of visualisation design’, respecting the small decisions that make a big difference towards the good and bad of this discipline. In each post I’m going to focus on just one small matter – a singular good or bad design choice – as demonstrated by a sample project. Each project may have many effective and ineffective aspects, but I’m just commenting on one.


The ‘little’ of this next design concerns the use of colour and specifically the restrictions caused by the universal application of ‘corporate’ colour palettes. There are benefits from applying consistent colours to facilitate brand recognition but sometimes this can cause unnecessary obstruction.

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In the Gallup chart above, showing trends for how people identify with the US political parties, it would seem to be more logical to use the established associations of Republican = red, Democrat = blue and Independents = grey.

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Whilst I appreciate it only requires the reader to learn 3 new colour associations, by not utilising the classic colour associations it does undermine the ‘available immediacy’ that this chart should have been able to offer.

The little of visualisation design: Part 5

This is part of a series of posts about the ‘little of visualisation design’, respecting the small decisions that make a big difference towards the good and bad of this discipline. In each post I’m going to focus on just one small matter – a singular good or bad design choice – as demonstrated by a sample project. Each project may have many effective and ineffective aspects, but I’m just commenting on one.


The ‘little’ of this next design concerns a nice way, proposed by Tim Brock, of handling some of the concerns that people raise about the potential misleading effect of using of a non-zero value-axis origin in line charts. (You don’t need to start line chart value axes at zero but I’m not going to get into that here and now).

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In an excellent article Tim discusses various approaches that help avoid giving the reader the sense that the ‘bottom’ of a chart should be read as a zero baseline. One solution that catches my eye is the use of a fading effect at the lower end of the chart. By decreasing the opacity for the colouring of the axis line, any tick marks and the value label, this makes visually clearer that the chart’s view is only presenting the observed range of values.

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The little of visualisation design: Part 4

This is part of a series of posts about the ‘little of visualisation design’, respecting the small decisions that make a big difference towards the good and bad of this discipline. In each post I’m going to focus on just one small matter – a singular good or bad design choice – as demonstrated by a sample project. Each project may have many effective and ineffective aspects, but I’m just commenting on one.


The ‘little’ of this next design concerns a really neat feature demonstrated in a project I reckon 99.9% of visualisation people are well familiar with: Gapminder. Specifically this is a new version of the classic tool, described as being pre-alpha (not sure really what that means).

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The feature I want to point out here is the ‘DATA DOUBTS’ link positioned just below the chart. Data is rarely perfect. The journey it goes through from measurement, processing, statistical treatment and finally on to visualisation will often introduce a need for assumptions, application of counting rules, small inaccuracies, rounding errors etc. ‘Good enough’ is usually a necessary attitude to take otherwise we’d be frozen by the reluctance to publish any information.

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What I love about this feature is that it acknowledges doubts about the data in a very open way: it is acknowledged front and centre, not scuttling around in the shadowy outposts of the site. The trustworthiness of a visualisation has to be of fundamental importance and so this kind of feature is so refreshing to see. Clicking on the link brings up a dialogue box with a brief comment about the reliability of the data, details about some of the necessary adjustments and assumptions and a link to read more in a blog post. Really very sensible and helpful for a reader to get this kind of contextual guidance so transparently before one launches in to forming meaning from the display.

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The little of visualisation design: Part 3

This is part of a series of posts about the ‘little of visualisation design’, respecting the small decisions that make a big difference towards the good and bad of this discipline. In each post I’m going to focus on just one small matter – a singular good or bad design choice – as demonstrated by a sample project. Each project may have many effective and ineffective aspects, but I’m just commenting on one.


The ‘little’ of design today concerns a matter I’ve discussed before relating to the integration of graphic devices into written sentences, as demonstrated in this graphic about the quality of signings being made by football clubs in China signalling the possible emergence of a new power in the game.

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Specifically, in this project, you will see how the ‘key’ explainers that would normally be segregated by a legend adjacent to the chart are instead incorporated into a written guide explaining what the various marks and attributes used in the chart represent. It might look simple but I’m sure it would have been quite a fiddly task making the sizing and alignment of the small graphics align seamlessly with the text and row size.

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(Via a tweet from John Burn-Murdoch who created this graphic and authored the article)

The little of visualisation design: Part 2

This is part of a series of posts about the ‘little of visualisation design’, respecting the small decisions that make a big difference towards the good and bad of this discipline. In each post I’m going to focus on just one small matter – a singular good or bad design choice – as demonstrated by a sample project. Each project may have many effective and ineffective aspects, but I’m just commenting on one.


The ‘little’ of this next design concerns clever axis-scaling decisions in this New York Times graphic about the trial of firebombing of refugees in Germany.

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Across the three line charts at the bottom of the graphic the highest value is 76 but this is a single outlier, with 38 of the 39 values presented less than 50. By effectively setting the y-axis maximum range to 50 notice how the recent increase in incidents of violence against refugees becomes even more striking, as the line climbs up to the height of 76, far beyond the height of the chart and almost intruding on the map area. An example of a subtle but smart editorial design decision.

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(Via a tweet from Gregor Aisch who I’m assuming was involved in the creation of this graphic)


ADDENDUM: A perfect suggestion from Walter Rafelsberger:

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…so, to capture the essence of this post series, here’s a little Al Gore on his little cherry picker

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The little of visualisation design: Part 1

This is part of a series of posts about the ‘little of visualisation design’, respecting the small decisions that make a big difference towards the good and bad of this discipline. In each post I’m going to focus on just one small matter – a singular good or bad design choice – as demonstrated by a sample project. Each project may have many effective and ineffective aspects, but I’m just commenting on one.


Perhaps inevitably, I begin this series looking at a pie chart (side note: don’t blame the pie chart on bad design choices). More specifically the issue here concerns unnecessary duplicate labelling.

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In this example, from the WEF, you see the use of colour legend AND direct labelling to indicate the categories that make up the parts of the whole. You don’t need both. Either directly label or don’t. In this case, due to the colour choices being far too similar, the direct labelling is the better option, which makes the legend entirely redundant.

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(Found via a tweet from Nigel Hawtin)

Data visualisation at its best in a chart about taxes

In my recent ‘Ask Andy Anything’ webinar Andy Cotgreave and I were faced with a particularly challenging pair of questions, one about sharing ‘success stories’ and the other inviting us to offer an elevator pitch for the value of data visualisation. I think this project by the excellent Alvin Chang of Vox is a perfect exhibit of the role of data visualisation. It visualises ‘100 years of tax brackets, in one chart’. Technically, it doesn’t just do this in one chart because it builds up the narrative through a series of carefully introduced sequenced snippets before the big reveal of the full 100 year chart.

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What it shows is the incredibly complex brackets that were in place for so many years – but arguably reflecting a more equal society – and then the hugely reduced and simplified model of the latter years of Reagan’s term, down to just two bands – with middle earners facing the same taxes as the wealthy.

This is data visualisation at its best as a device for facilitating understanding in a way no other form could achieve. You can see the data. You can learn something about the subject if you are new to it, you can confirm what you suspected about the subject if you are not. When next I find myself in an awkward elevator situation being asked about the value of data visualisation, I’m going to have a laminated print-out of this example ready to whip out.

(As a sidenote, take a look at how the responsive design modifies the appearance of the President labels as you widen/narrow the screen)

Quick redesigns of BBC sport graphics

Yesterday I tweeted about a confusing graphic from a BBC article dispelling myths about last season’s Premier League. Its a good article with some really interesting content but some of the accompanying graphics hindered rather than enlightened the points being made.

A couple of people asked what I would do instead. Time rarely allows it but one should always be willing to offer an alternative, even if it is just quickly expressing some ideas verbally. Criticism without suggestion is empty and it is something I fall into all too often. So I thought I would quickly offer a reworking of the two main graphics that I felt caused unnecessary inaccessibility. I assumed the same constraints around space, (similar) typeface and colours as well as the inclusion of the logo and hashtag.

The first concerns the use of a radar chart to demonstrate how Stoke City have evolved from a long-ball team under Tony Pulis, into a more progressive team under Mark Hughes. With Radar Charts, there are almost always better solutions, especially when you are attempting to compare two series of values in the same chart. Radars really only make sense if and when there is some compelling logic for the radial arrangement of values (usually temporal, spatial or, occasionally, intuitive groups).

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The redesign uses a connected dot plot to draw out the differences in rankings between the different measures. The measures themselves are re-ordered to try and group related ones together.

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The second relates to the main graphic I mentioned on Twitter, which looks at dispelling the idea that teams with the most possession have the most success. The donut chart was reasonably fine until the dots landed. Due to their placement within the arcs there is an implication of meaning, especially when we see the two adjacent dots for the call out aggregating the loss and drawn match percentages. Unnecessarily confusing when all we need to learn about is 4 numbers.

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The redesign is very simply a stacked bar-chart. To be honest it still doesn’t add loads of value as a visual, you are essentially getting most of your understanding from the value captions but the stacked bar better aids showing the ‘did not win’ aggregate. I’ve switched the colours to perhaps better suggest bad, medium, good.

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Comparing the before/after versions I suspect that the labelling size and prominence of colour of my redesigns would need fine-tuning. It is interesting to see how faded they look when you shrink the final png file down. In the native Illustrator version they look far more vivid to the naked eye. That’s a good lesson in testing out your prototype designs in the size and setting in which they are likely to exist, to see for yourself how they look. Anyway, I’ve not got time to undertake endless iterations but you get the idea.