Makeover Monday week 49, 2017: The cost of a curry at Wetherspoon’s

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Last week we spoke about maps and visualizing geographic data more effectively. We ran a webinar with Mapbox and this week’s dataset contains Lat/Lon data so that everyone can apply some of the tips and tricks they learned last week.

For this week’s challenge Andy picked a dataset containing food and drink prices for Wetherspoon pubs around the UK. Yes, I continue to be amazed by the types of datasets that can be found in the wild. Who would have thought… (and we have a long list of topics for Makeover Monday for weeks, months and years to come hahaha)

This week’s viz is accompanied by a lengthy article about the analysis the Financial Times journalists went through to gain a better understanding of the pricing differences across the country for the exact same menu items including curries, burgers, desserts and drinks.

It makes for an interesting and entertaining read with a few remark that made me chuckle. Check it out for yourself here.

So this is the original viz:

 

What works well:

  • For those who read the article ‘around’ this viz it quickly becomes apparent that the blob map does in fact depict the shape of the UK
  • The colours work pretty well together
  • The transparency of the circles helps show the more densely populated areas, i.e. cities and larger towns where more of the Wetherspoon pubs are located
  • The subtitle explains the colour legend somewhat
  • I actually like the title because it goes with the tone of the article, slightly sarcastic and to the point

 

What could be improved:

  • Yes, I said I like the title but it could be so much more descriptive. These days, charts often appear in image searches and without the context of the article, the chart itself doesn’t carry much meaning, so a strong title would be a great addition
  • With the lack of a background map and the use of Lat/Lon as numbers instead, the grid lines don’t add much value unless people are used to thinking about locations with GPS coordinates (I doubt it…). Maybe some reference labels could help, e.g. London, Manchester, Brighton, etc. Some ‘markers’ on the blob map to help clean it up
  • The price bucket labels are not very descriptive. Do they relate to a meal or just one menu item? Does it include drinks? This information would be helpful to include somewhere, e.g. in a subtitle or in the labels
  • The colour legend could sit below the subtitle to bring it closer to the data as the portrait layout means that most people would look down from top to bottom and wouldn’t necessarily look to the side. It doesn’t seem very intuitive

 

What I did:

  • First I aimed to recreate the blob map to ensure I was looking at the data the right way:

 

blob map.png

  • Then I played with the data for a bit to find an interesting angle. Nothing stood out to me until I got hungry. I’m not a drinker, but I’m a big fan of dessert.
  • Turns out, there are a number of pubs where beer actually costs more than dessert. That is a crime and an affront to desserts all over the country…
  • So my story was born and here is my viz…

 

Click on the image to interact

makeover

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