MakeoverMonday

This week Tableau themselves chose the data; a celebration of the importance of data skills based on LinkedIn’s annual Top Skills reports. The Tableau example includes a bump chart and box and whisker plot, whereas the LinkedIn version is a simple list per country in a slide share style: Thoughts on the original charts The LinkedIn version is simple and clear. You can see which skills are ranked highest and how that ranking has changed since last year. However it is hard to compare the countries to each other or to the overall global ranking (you have to flick back and forth in the slide deck). Also you can’t see how rankings have changed from years prior to 2015. ...

Week 16 and it’s back to some big data on EXASOL thanks to Eva and Johannes. This time over 750 million rows of GP practice prescribing data for the UK from 2010 – 2017. The nominal challenge to makeover some of the charts in a House of Commons research briefing based on the data. ...

Uh oh! Making over a 2009 graph by Andy Kriebel this week. No pressure. The graph looks at the correlation between gold and oil prices with the premise that they’re closely related. You can see Andy’s own makeover here. Another of my favourites is one by Mike Cisneros, which you can read about here. I love the story telling element Mike achieves; something I was aiming for myself. ...

The Guardian recently reported on the a PWC report into the risk of UK job losses from breakthroughs in robotics and artificial intelligence. Whilst technological unemployment isn’t a new concept and the report and article certainly do comment on job creation too, the percentages at risk in some sectors are quite striking. ...

I found week 13 of Makeover Monday quite hard. The visualisation in question was an infographic purporting to show the perceived reasons for success by different social strata. The subtitle of the graphic seemed quite inflammatory and so I was keen to trace the data back to source to see what grounds the author had for their claims. Unfortunately, as others found too, it was pretty hard to find the actual Russian survey results used. This University of Illinois blog post has a great critique of the visualisation and is well worth a read. ...

Learning about March Madness / the NCAA college basketball tournament this week. Is it getting harder to pick the winners at each stage? Tableau public version available here.

I finally got around to completing week 11 in late June! A redo of the chart in this tweet. It’s a pretty engaging chart, although the colour choice in the icon chart is a little hard to make out. I haven’t really improved on the infographic, instead it was a chance to try something new in Tableau – a radar chart. The viz is also available in Tableau Public. ...

This week a look at the top 500 gamer channels on YouTube based on this list on socialblade.com. What intrigued me about this week was the immediately interesting disparity between the video views, channel subscribers and the Social Blade ranking (score) and rating (grade). The more influential channels according to Social Blade are not necessarily those with more views or more subscribers. The list itself is pretty handy but not visual engaging and there’s no real story telling or summary. ...

Makeover Monday week 8 and Andy Kriebel challenged the Tableau community to improve on two graphs of his American Express card expenditure. The graphs are very clean and appear to offer some drill down functionality to view transactions. There doesn’t seem to be an intermediary level of detail, e.g. sub-categories (although that may exist and we’re just not seeing it here). Also the use of a 2016 average may not be as useful as a median given that there were a couple of one off large expenses. ...

Week 8 is all about potatoes. European Union potato sector stats to be precise. Eurostat provide a very detailed analysis of the EU potato sector on their website: . The article is very detailed and does take some time to read, but the key points are in bold so it can be scanned to get an idea of the main stories. The use of tables provides a lot of background data but again the emphasis is on taking the time to digest the data. For my makeover I’ve tried to focus on three key points – most of the production is in a small number of countries; Germany is the biggest producer; but France achieves the best price. The viz can also be seen on Tableau Public. ...