In an attempt to show how the two categories contribute to traffic violence (crashes resulting in injuries or fatalities) at very different rates, I created this notebook. Perhaps there are other / better ways / charts that might be effective in comparing the two categories?
I explored a little bit looking at how “dangerous” a collision might be depending on the type of vehicle involved. I computed injury rates (the average number of people injured per collision) broken down by injured subject (motorist, cyclist, pedestrian).
The interesting thing to me is the difference between the total injury rate (“persons”) versus the respective operator’s injury rate (cyclists for bicycle-involving collisions, motorists for car-involving collisions).
For bicycle-involving collisions both the total injury rate and the cyclist injury rate are near 1.0, suggesting most of the time there’s a bicycle-involving collision, it’s the cyclist who is injured. However for collisions involving cars and trucks, the total injury rate is about 1.4, while the motorist injury rate is about 1.0. It appears that pedestrian and cyclist injuries make up for most of the difference, which makes sense.
That said I’m not an expert in this data and I would suggest talking to people who are more familiar with it (if you aren’t already!) before drawing conclusions.
P.S. I also tweaked your queries (to use GENERATE_SERIES) and typed-coerced the result. We use these techniques in our internal Observable dashboards and you might find them useful…
Thanks @mbostock! This is really helpful, both in terms of analysis and techniques.