Cancensus
Income numbers for the 2016 census are out, and I am taking a first shot to dig a little into the numbers. The numbers correspond to the 2015 income tax data, and this census was the first time that all data was directly linked to CRA tax data. For all people. So the income data is part of the “100% data” this time.
In the standard release we got median income data (no average income numbers this year, for better or worse), individual and household income distributions, income deciles for families, and two low income measures by rough age groups.
I wasn’t really getting into the Amazon HQ2 thing, but then the Upshot did some analysis that excluded Canadian metros. That’s not right. So I decided to fill in the gap. Our cancensus package is perfect for the job. This post is generated from an R markdown document, which is available on GitHub for anyone interested in refining this.
Canadian Metropolitan Areas It probably goes without saying that omitting Canadian cities from the list is more than just a small inconvenience.
The fate of young families in Vancouver is a frequent news topic. And as Vancouver is growing it is important to understand how families navigate the sometime challenging environment and what choices and compromises they make.
So we decided to take a closer look at where families and their children live in Vancouver over the last decade and how they fit into the rest of Vancouver. I had most of scripts already assembled over the long weekend to provide some data for a story by Mike Hager, so I decided to tidy things up and add some visuals.
I started writing this blog post in December 2015, when CensusMapper quite a bit younger and I hacked together some basic dot-density maps. I never much liked the results and have been slowly improving and thinking about them. I am still not entirely happy with the current implementation, but it is slowly getting there. The final impulse to finsish this post was the work on cancensus, and R wrapper for the CensusMapper API my explorations in multi-category dot density maps in R, now tied up into the new dotdensity package.
Density in Vancouver has been one of the recurring themese on this blog, and there are many different ways to come at it. We have looked at density in terms of land use to understand how much land is devoted to what purpose in Metro Vancouver and it’s municipalities. We have looked at density in terms of tax density to understand how property tax revenue depends on land use and zoning.
