The Friday project – week 5

A productive day today as I created two new vizzes and learnt some new skills: how to create a text box with conditional commentary, and how to customise marks on a chart.

Here are the links I used first up in case they are of interest:

http://kb.tableau.com/articles/howto/creating-dynamic-titles-based-on-filters

https://public.tableau.com/s/blog/2013/10/creating-and-utilizing-custom-shapes

And here are the final vizzes…

How much did UK clubs earn from Euro 2016?

euro-2016

This was my first attempt at taking Andy Kirk’s advice to “think like a data journalist”. I had seen this article the previous evening about the amount Ipswich Town had earned, and after some googling found a complete list of earnings for all UK clubs in this BBC article.

I found geodata for each club at https://www.doogal.co.uk/FootballStadiums.php as I was keen on using Tableau’s mapping functionality, as well as which leagues each club was in (with the exception of a few data points I had to source and enter manually).

The end result was almost exactly what I had sketched out the night before, with a selective bar chart on the left and the geographic view for all teams on the right, and more detail available through the tooltips, or on demand for each club via the dropdown.

Makeover Monday – Employment growth in G-7 countries

g-7

I had read Chris Love’s analysis on the data used in this week’s Makeover Monday earlier in the week, but in the end I decided to take the Andy Kriebel route and just make a better f*ing chart.

ak_tweet

I knew I wanted to learn how to use flags for the marks, but the question was: for what chart type? My original idea was a scatterplot, but this felt to me like I was over-emphasising the connection between the two metrics.

Ultimately I ended up using the circle views option, but with the two charts side by side and the countries in the same order on both, to allow comparison between the two metrics without trying to force a connection.

As with all vizzes, it is far from perfect, although in this case the dataset itself had significant limitations. Still, I had learned something new…and it was better than the original f*ing pie charts!

 

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