Communicating with Pie Charts

Dark Horse Analytics are back with the third instalment of their 'Data Looks Better Naked' series. This time they're improving the pie chart

I don't quite agree with their conclusion because pie charts are a useful communications tool when you want to communicate simple part-to-whole relationships without having to talk through the numbers.

Using charts to tell a quick story

For example, I find pie charts useful when showing the proportion of men vs women in a particular sample set. Or the results of a series of yes/no questions.

Take a look at these pie and bar charts: 

If I was going to use these charts to tell a story during a presentation, I'd much rather put those pie charts up on the screen and say something like: "Most people voted 'yes' in Question 1; about two-thirds voted 'yes' in Question 2; but a little under half voted 'yes' in Question 3". That explanation wouldn't work as well if I had used the bar charts, instead.

On the other hand, if I had wanted to talk about the actual number of yes-vs-no votes cast for each question (or their percentage values), then I'd use the bar charts.

Of course if I wasn't going to show this on a big screen at all, but was instead including the results in a written report, then I might not even use charts. I might just put all those numbers in a table.

Communicating a rough sense of the numbers

The other situation in which pie charts are useful to me is when I want to communicate approximate results for a slightly larger data series but, again, without having to talk about the actual numbers.

For example, every Tuesday at work I email around a social media activity report that tells my colleagues how we did on our various social media channels over the previous week. One of the charts I include in my report is a Twitter sentiment pie chart for various geographical regions. This chart gives you an idea of how people felt about us on Twitter over the previous week.

The thing is: the people I send this report to don't particularly care whether 15% or 20% of people expressed excitement about our brand on Twitter last week. They really just want an approximate sense of how things went. They want to be able to say "a lot of people were positive about us on Twitter last week" or "people didn't like us very much on Twitter last week." And the pie charts I get from Hootsuite (one of the social media management tools we use) helps them reach that single-sentence conclusion pretty quickly.

Here are the Twitter sentiment charts for three of the regions we keep an eye on. The 3-D pie chart plus data table combo in the top row is what we get from Hootsuite (and is what I include in my reports). Below that I've converted this data into stacked 100% column charts and into bar charts: 

Each of these charts tells a slightly different story. The pie chart plus data table combo is nice because you can quickly look at the charts and think: "Okay, not too much dark red or dark green for Region 1; so a mostly average week there. Quite a bit of orange, but no dark red, for Region 2; so people were unhappy, but not angry. And plenty of dark red and dark green for Region 3; which suggests some people were very happy but some people were very upset. And I know that last week we had a great sale but a bunch of flight delays in Region 3 so this result makes sense."

The stacked column charts help you tell a similar story but, in my opinion, it's harder to judge the proportion of one colour to the whole in this type of chart so you're forced to look at the numbers to give you additional context. So you'd look at Region 3's chart and think: "Okay, 24+8 = 28%, so a little over quarter of the people were unhappy. And 21+12 = 33%, so about a third were happy." But now you're stuck comparing 33% green to 28% red instead of just getting a sense of what people thought, and then moving on.

The bar chart at the bottom does possibly the best job of comparing one colour/sentiment with another - but what you're missing here is the relative proportion of that colour compared to the whole. So, for example, you'd look at the Region 2 chart and think: "Okay, light orange is the highest bar so a lot of people were unhappy with us." But then you'd have to add 42% and 17% to see that about half the people were unhappy (though not angry) last week. You could reach that same conclusion with a single glance at the pie chart which shows that it's about half light+dark orange.

In my opinion the pie chart plus data table combo works best. If you just want to get a feeling for the data you only need to look at the pie chart and get a sense of the colour spread. But, if you want to dive deeper it's easy to move on to the table and add the numbers to do a more detailed analysis.

But no other pie chart use

Those are the only two situations in which I use pie charts. In most other situations I'm showing a data trend (as opposed to a snapshot) or a larger series of values - both of which require a different kind of explanation and, therefore, a different kind of chart.

So what I'd recommend is that, if you're ever not sure about which chart type to use, just chart your data in multiple different ways and then try use each type to tell your story. The one that works best (i.e. tells the best story, is the easiest to explain, and has the least chance of being misinterpreted) is the one you should go with. And if this happens to be a pie chart, then so be it. 

Communicating with Charts and Infographics

I love using pictures, charts, diagrams, and infographics to illustrate and explain complex or hard to visualize ideas, concepts, and relationships.

Using Charts and Infographics at Melbourne Water

Since we deal with pretty complex subjects at Melbourne Water it makes sense for us to use well designed charts and infographics to explain what we do and how we do it. So, over the last year or two, we’ve been working with various vendors to produce graphics and animations that help us communicate better. We’ve also been improving our own chart-making capabilities so we can explain things more effectively to our more interested (which usually means more nerdy) audiences.

Here are some of the things we’ve done.

Explaining Systems

To explain how a system like Melbourne’s Water supply network works, you can use a static and somewhat technical map like this:

Melbourne Water Supply System Map - Old

Or you can use an animated map to really show people what’s going on (click through to see what I mean):

Animated Melbourne water supply network map

That animated map has proven to be very popular: over the last year it’s been viewed over 40,000 times with visitors spending an average of two and a half minutes going through it.

You can explain complex systems without animations, too – like we’ve done with our Eastern Treatment Plant’s sewage processing diagram. This diagram comes in two parts. First, there’s a high-level overview:

ETP sewage processing overview diagram

And, then, there’s a more detailed explanation of the steps we take to process sewage at this plant (including the tertiary treatment bit that’s currently being built):

ETP sewage processing detailed diagram

Explaining Relationships

Another important use for graphics is in explaining relationships between things.

For example, the Melbourne Water website gets about about 10,000 visitors per day. However, this figure jumps to 25,000 when it rains and over 40,000 when there’s a big storm in Melbourne. This happens because people want to know what effect the rainfall is having on our water storage levels.

To explain this relationship, we first used a simple column chart to show the basic trend (though the figures in it are from about a year and a half ago):

Web Traffic Depends on Rainfall bar chart

We then drilled down into a more detailed example and plotted the amount of rainfall recorded in Melbourne in August 2010 and compared that to the number of website visits received over the same period. The relationship between the two is quite obvious when you look at this graph:

Effect of Rainfall on Web Traffic line chart

These diagrams were made to be printed, by the way, which is why the text size on the axes isn’t all that large.

Telling a Story

At times, though, all you want to do with a graph is tell a story.

For example, we used this simple graph to explain the how Melbourne’s dams staged a remarkable turnaround in 2010, jumping from 25.6% full in July 2009 to 53.7% full in December 2010:

Melbourne's dam levels in 2009 and 2010

And we used this graph to explain that Melbourne’s total system storage depends a great deal on how full Thomson Dam is (because Thomson is almost 60% of Melbourne’s total dam capacity):

Melbourne Dams as a Percentage of Total Capacity

More generally, we use this graphic to explain to Melburnians just how big Thomson really is:

Thomson dam is twice the size of Sydney Harbour Bridge and 628 the size of the MCG

Showing Cause and Effect (i.e. Explaining More Complex Relationships)

Recently, though, we’ve gone one step further and have used a couple of charts to explain what, at the face of it, seems to be a strange result: rainfall for spring 2011 was 28.5% above average but water flowing into the dams (i.e. streamflow) over the same period was 22.4% below average. This happened because of what we call the ‘sponge effect’ and we used this graphic to explain what happened:

Effect of spring rainfall on streamflow - Spring 2011

Now this type of graph isn’t for everyone to read and understand but, that’s okay – we know that a lot of our website visitors are water nerds just like us and that they appreciate the extra effort we make in explaining these results to them.

Hopefully, this use of charts and infographics to explain complex things is something Melbourne Water continues to do in the future. I know I certainly will.

Infographic Resumes

Ever wanted your resume to stand out – and I mean really stand out – from the others? How about making it an infographic?

resume-infographic

[Source: ‘Resume / Infographics’ by Michael Anderson]

For more, read ‘16 Infographic Resumes, A Visual Trend’ by Randy Krum on the Cool Infographics blog.

I am very tempted to convert my own resume into this format. I wonder how long it’ll take and what software I can use to do it.