The last larger dump of census data arrived today with lots of interesting variables. We wanted to have a quick look at commuting data. Journey to Work Journey to work data tells us about where people work relative to where they live. We first look at what proportion of the population of Metro Vancouver municipalities lives in the same community that they work in. On CensusMapper we have an interactive Canada-wide map for that.
Currently we are at record levels of dwelling units under construction in Metro Vancouver. At the same time, we are also at record timelines from building start to completion. Those two are of course related in that the more projects are being worked on simultaneously, the harder it is to find and coordinate all the labour and materials to finish the projects. There are other reasons too for escalating construction times.
The election data got posted on the Vancouver Open Data website so we decided to take a very quick peek at how the candidates fared by polling station. Citizens can vote at any station they want, so there is are no voting districts. But proximity to home is probably a large factor in determining where people vote, although some may choose locations close to work or somewhere else convenient. For anyone that wants to refine the analysis, the R Notebook that generated this post lives on GitHub.
Not sure how long this has been live, but this morning fellow cancensus developer Dmitry flagged a new StatCan feature. Interactive thematic web maps. Essentially it enables users to choose from the a selection of 2016 census variables and map them. You can zoom and pan around, and select the aggregation levels to display the data at down to census tracts. And there is a option to download single variables as CSV.
Earlier today I came across Gil Meslin’s tweet suggesting to reproduce this rent graph for neighbourhoods in Toronto. I agree that this would be fun to do. All it requires is mixing the Toronto neighbourhoods with renal listings data, which I happen to have handy. So time to get working. Neighbourhoods To do this we need to grab the Toronto neighbourhoods which can be found on Toronto’s open data website.