Makeover Monday Week 45

It had been a few weeks since I’d created a viz for Makeover Monday so I decided to bite the bullet on Sunday evening and download the data. The Myers Briggs data set from Week 43 had looked really interesting but I didn’t get to it unfortunately. There were lots of great visualisations created that week and I find the topic fascinating so I hope to get to it at some point. The data set this week was an interesting one too, looking at life expectancy in countries across the world, from 1960 to 2015. There were several dimensions that could be explored, from gender or income group to country or region. I decided to focus on country and region, as my time was limited and I thought I’d try and avoid putting too much on my dashboard (not sure I quite succeeded, but it could have been worse).

The original visualisation can be seen here, with a screenshot below where I’ve selected Ireland.

What I liked about it:

You could select a country and get a rough idea of where it ranked overall
Clear colour groupings of life expectancy ranges in the bar graph, table and legend
Filter options to allow flexibility at the top left

What I didn’t love so much:

The map looks a bit squished and I’m not a fan of the grey boarders
The appearance seemed a bit dated (like everything, just my opinion)
There is no indication of the change over time

What I wanted to do:

Look at the trend over time across the countries
Compare the distribution across the regions
Get an understanding of the percentage change over time and how it varied across the countries

As usual I went through a few iterations and created a number of views while exploring the data, some of which I didn’t end up including. The first couple of views I created were quite similar to the original. I also created a slope chart looking at the change from 1960 to 2015 and a histogram looking at the distribution of % change across the countries. I liked the idea of showing the trend over time going from the top to the bottom of the dashboard. I really like box plots and thought they worked here as a way of comparing the regions. They are a great way of shining a light on distributions, allow you to compare across the regions and let you see any outliers. I wasn’t convinced the shape map was a great way of showing insights about the % change over time, given the overlapping of the circles, but I think it works better with interactivity rather than being viewed as an image.

I tagged my viz to be included in the viz review webinar (using the hashtag #MMVizreview). This was a first for me as I often don’t complete my viz until later in the week. I had it done and thought that I would benefit from some honest feedback so decided to give it a go. I picked up some useful tips from the webinar. The rate at which Andy Kriebel and Eva Murray fly through the visualisations is impressive. They really make an effort to get through a lot and are interpreting them on the fly, while being recorded (and while on a train in Eva’s case) having not examined them in any great detail beforehand. I took some of the suggestions they made about my visualisation on board and made some changes. The ‘before’ and ‘after’ images are below.

I’m sure there is plenty more I could change, but you have to call it a day at some point. I had initially decided against turning the chart on the left into a line chart as I mistakenly thought that would join the lines where there was missing data. I wasn’t thinking about it correctly at the time however. What I had in mind was the case where there are missing dimension members (like in the case of the Tour de France data set in Week 28), rather than missing data values. When there are missing dimension members e.g. years, the default in Tableau is to join up the data points. When this happens you need to carry out a few steps in order to create a gap in the line. Eva wrote about this point in her blog here and described a way of getting around this, something she had picked up from Adam Crahen. I couldn’t quite recall how to do it and I figured I’d give the circles a go. My thinking was that if you interacted and highlighted regions or countries, you could see patterns and hover over to see more detail. I think the lines look a lot better however and are more effective, allowing you to see the trends more easily.

Before – original version that I shared on Twitter: