I don’t usually participate in Tableau #WorkoutWednesday, but this week the chart we had to reproduce featured my team so I had to give it a go! Here is the finished chart, which is also available on Tableau Public: <th> Team </th> <th> Total points </th> <td> Arsenal </td> <td> </td> <td> Arsenal </td> <td> 3 </td> So the challenge is to: ...
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. ...
Love is in the air this week with a makeover of an infographic on valentines day spending in the US. The original visualisation is pretty good although some of the key data (like average spend per person) doesn’t necessarily jump out. Also there’s nothing to show changes over time, even though the data source does contain that information. So for my redo I wanted to focus on a very clean presentation of the main trends over time, whilst still highlighting some key stats. I also wanted to offer the viewer the ability to explore the data a little more – something I haven’t done in many of my makeovers this year. ...