Makeover Monday, 2017 #37

For week 37 of Makeover Monday we’re looking at UK bicycle thefts based on data from

The reference site linked above has pretty extensive visualisations and I love the way they unfold as you work your way through the site. I’m not going to try to improve upon the site, instead I’m looking for a different angle to show and, given the bleakness of the data (less than 1% of bike thefts resolved!), it’s an opportunity to try a paired back black and white viz.



Trying to remove unnecessary colour is some advice from Andy and Eva in their weekly roundups. Does it work in my viz? Feel free to let me know on the twitter thread - any feedback is welcome. Also check out the Tableau Public interactive version where you can dig into a particular constabulary to find your local story.

A note about the resolution calculation:

The source data came with a range of outcome descriptions which I’ve mapped to three resolution categories: unknown; resolved and not resolved. If you’re interested in digging into this mapping I’ve included it below. The reason for the unknown category is that there seems to be a lead time on getting a resolution (positive or negative) as a case works its way through the system. Having a yet to be determined / unknown category means that we can factor those out of a resolution rate. Otherwise we’d expect to see a tail off in the most recent months as the thefts are yet to be investigated, etc. Arguably a couple of the outcomes that I’ve categorised as resolved are a little unclear and a proportion of those could actually be unresolved or still in progress.