Metro Vancouver is growing, both in terms of population and jobs. That means the number of people commuting to work is growing and putting a strain on our transportation system. The nature of that strain depends to a large extent on how people are getting to and from work. The Canadian census started collecting data on how people get to work in 1996, which allows us to see how commuters and commute choice have changed over time.
Canada is a large country, with some reasonably densely populated regions, and large areas that are sparsely populated. That makes it hard to map things. CensusMapper, our project to flexibly map Canadian census data, struggles with that. The choropleth maps can be quite misleading. The same problem comes up when mapping Canadian election data.
This map makes it virtually impossible to get a good reading of the distribution of votes.
Following up on our previous post on rents and vacancy rates there is another rental stat originating from City of Vancouver documents that is making the rounds and that is misleading. Again, our housing crisis is fundamentally a rental crisis, so it’s important to keep the numbers straight so that we can better focus our energy and resources. This one is a bit more serious, but still has been making the rounds quite broadly on social media.
This post responds to a misconception about rental housing that has been making the rounds. Our housing crisis is fundamentally a rental crisis, so it’s important to keep the numbers straight so that we can better focus our energy and resources.
The misconception originate from the 2019 Vancouver Housing Data Book. The data book is a huge effort to compile and has a host of valuable information. Vancouver has been doing this for the second year now, and it is successively getting better.
These days I run a fair bit of spatial analysis. And there are three problems that regularly come up:
Getting data on compatible geographies Ecological fallacy Spatial autocorrelation None of these problems is insurmountable, but they are all annoying to various degrees. Often I might ignore them on my first analysis run, but these problems need to be dealt with sooner or later. Which can eat up significant amounts of time.
