A tough week for me with a hectic work week and a struggle for #MakeoverMonday inspiration.

The aim was to makeover this Myers Briggs chart. I like the 4×4 grid representation of the original as we are basically looking at a mix of four attributes. I don’t really get a sense of the percentages / proportions though as every segment of the grid is the same size. I also had to flick back and forth between another page on the site to get a more detailed explanation of what the letters mean.

Perhaps foolishly I decided I wanted an overlapping area chart showing all four dimensions. I couldn’t do this in Tableau so should have fallen back on a tree map or marimekko, or maybe this beautifully simple reviz from Henrik Lindberg (nice). Instead I banged my head against producing the following:

.

It’s also available on Tableau Public.

Most of the work was actually done in an SQL script as I couldn’t wrap my head around the Tableau table calculations. Was it worth it? Yes and no. The representation isn’t totally accurate due to fudging the bottom row and left hand column start points.  On the other hand it’s quite visually engaging and it was good to nail those calculations even if it was back in SQL!

Making over a table of Formula E racing results from the FIA Formula E website this week.

I was interested in how drivers progressed from practice to qualification so went with a bump chart. I’ve highlighted the winner but dashboard actions also allow the user to highlight the driver that they are hovering over. This way they can see how each driver’s performance changes during an event because the bump chart is quite hard to follow otherwise.

The viz asks a question and gives the user room to explore the data and come to their own conclusions, however a micro chart in the left hand margin also provides a general answer for those with less time or inclination to interact. The micro chart is based on average rank in qualification and race with a trend line to show the correlation.

You’ll spot that for the “super pole” session only six drivers are involved. To avoid a gap in the bump chart for the other drivers I’ve filled this rank from the previous session but not shown a mark / rank.

If I had more time and data I’d dig into the impact that fanboost has on the eventual winner.

The viz is also available on Tableau Public.

Just a brief write up for now! Andy and Eva chose charts relating to adult obesity in America for the 41st makeover with the source data coming from the CDC. The original charts are part of an interactive dashboard and it is well worth checking out.

Similarly to Klaus Schulte I decided to dig into gender differences. Klaus’s makeover is very nice so definitely go take a look at that.

Here is my attempt:

.
It is also available on Tableau Public here.

Challenges were laying out the maps to include the more far flung states and territories, and also getting some decent labelling on the area and line charts. I’ve resorted to reference lines for the latest value and standard header labelling for the states (I would rather have had a label in the area shading).

This week was a makeover of a Financial Times article on the UK economy since the Brexit referendum using data from the OECD.

The original

The original visualisation allows us to easily see the UK, but doesn’t allow us to compare to another G7 country as there is no labelling of the other lines or ability to highlight. The chart also lacks context around when the Brexit vote occurred and what the historical patterns have been; does the UK usually have slower growth than the rest of the G7? Missing 2017 Q2 data is a bit of a shame.

Makeover

I’ve gone with three key elements in my makeover:

1. Retain the line chart and highlighting of the UK, but show a wider period of time and highlight the referendum date
2. Show the range of growth across the G7 without showing too many lines. Instead allow the user to choose which G7 country to compare to
3. Provide a ranking table to highlight the low ranking for the UK in the last two quarters

The viz is also available on Tableau Public.

Final thoughts

My usual approach would be to plot all of the G7 countries as individual lines in a deemphasised colour. This week I wanted to experiment with showing the range of data in a different way. I had hoped that a light area chart would allow me to highlight the UK in red, show another selected country in a mid-grey and still see the G7 range in the background. Whilst the approach does allow the user to get a better idea of stability / variability for each country as they explore the data, the area chart doesn’t really sit in the background when it comes to interacting – e.g. hover over.

The area chart has two parts with the bottom part being shown in white to give the impression that you’re just seeing one area. This required calculations based on min/max values to get the two parts.  An additional challenge was that Tableau doesn’t handle area charts crossing the 0 line particularly well (or didn’t for me at any rate – I ended up with empty shards in the chart!). To work around this I calculated an offset and pushed all data points up by that amount so that everything was above 0. The real, none offset, values are used for labels and tooltips and a reference line was added for a fake 0 line. Upshot: it was a lot of work and fudging and perhaps not worth it. Feel free to download the workbook from the Tableau Public page linked above to see what you think.

I like the way the table at the end tells the ranking part of the story in quite an effective way. I prefer it over a bump chart in this case and in hindsight perhaps the table was actually all that the makeover needed!