Mountain Doodles

spare time data, analysis, visualization


| Comments

Ever since that Bloomberg article whose claims nobody could reproduce, where the author refused to disclose what data was used, but that got recycled all across the local press there has been a hightened interest in migration patterns in Vancouver. Nathan Lauster took it upon himself to dig deeper and look if Vancouver’s lifeblood was really leaving, which he kept elaborating on as better data became available until the most recent iteration that compares Metro Vancouver to other Candian metropolitan areas as well as the City of Vancouver to other cities within Metro Vancouver using 2016 census data.

This is seriously good work and we thought it would be helpful to reproduce Lauster’s methods in CensusMapper. The result is a series of maps, one for each five-year age cohort, that visualized net migration of the cohort geographically, while hovering over a region reproduces Lauster’s net migration bar graph for that region.

Surprise Maps

| Comments

At CensusMapper we like building models based on census data. We now have a common tiling for 2011 and 2016 geographies that allows us to easily model changes over time. After building a model we often want to see how well the model performs. An easy way to do this is to simply map the difference of observations and model predictions.

Those maps are great and it is easy to understand what is mapped. But they are difficult to interpret properly. In many cases a better metric to map is how consistent the observations in each region are with the model. Which brings us to Bayesian surprise maps.

Marine Gateway and Joyce-Collingwood

| Comments

There has been some recent confusion that got confounded further about transit-oriented development in Vancouver harbouring a large number of non-primary residence homes. Good data is important in moving forward in Vancouver’s crazy housing market. Without proper context, a couple of data points can serve to paint a very misleading picture of what is happening. So I decided to fill in some gaps on the very narrow question of understanding the CT level numbers that get tossed around. No deep analysis, just looking into the CTs in question to see where the numbers that the census picked up came from.


To understand the overall rate of 24.4% non-primary residence dwelling units at the Joyce census tract, one should split the area into the Wall Centre Central Park development (99.2% non primary residence units) and the rest of the CT (3.4% non-primary residence units).

To understand the Marine Gateway CT (24% non-primary residence dwellings), it should be split inte the block with Marine Gateway development (13.7%), the block containing the MC2 development (67.4%), and the rest (10.1%).

Comparing any of these very recent developments to the much older Coal Harbour makes no sense. Coal Harbor is still “filling in” although at a stubbornly slow rate. It will be interesting to see if the new vacancy tax can help speed that up.

Comparing Censuses

| Comments

It’s great to have fresh census data to play with. Right now we only have three variables, population, dwellings and households. There is still lots of interesting information that can be extracted.

So we started exploring in our last post, things get really interesting when looking at change between censuses. But as we noted, there are several technical difficulties that need to be overcome.

So we at CensusMapper took that as and invitation to do what we love most: breaking down barriers.

RS Population Change

| Comments

With reporting on the new census numbers gaining traction, and now Mayor Robertson picking up on single family neighbourhoods losing population we thought it is time to crunch some numbers.

Why does it need number crunching? All the reporting so far is based on looking at CT (Census Tract) aggregates, like e.g. in the map shown and linked to the right. But there is actually no single CT in the City of Vancouver that only contains RS zoning. Deducing results by just looking on CT aggregates can lead to misleading reporting, like we have seen with unoccupied dwellings in the “Marine Gateway Neighbourhood”. Given how prominent this topic has become it is high time to dig into the details.


In summary, we can confirm that RS (single family), RT (duplex) and FSD neighbourhoods have been dropping population. Slightly. Looking separately at the east and the west side, we notice that population in these neighbourhoods dropped by about 1% on the west side and increased slightly on the east side.

In all groupings that we looked at the household size dropped and the rate of unoccupied dwellings increased. This was counter-acted by a growth in dwelling units, mostly confined to RS zones where laneway houses and suites were added (or newly discovered in the 2016 census).

We split the analysis into core regions, blocks that lie completely within RS, RT and FSD zoning, and fringe regions, blocks that have RS, RT or FSD zoning as well as other zoning. Fringe regions grew in population and had overall lower rates of unoccupied units when compared to core regions.

Transit Explorer

| Comments

I have played with Mapzen’s Isochrone serivce in the past with a simple visualization of walksheds.

Recently Mazen updated the isochrone API to allow for a more fine-grained selection of exactly what transit services to include or exclude in transit routing, and they created an amazing mobility explorer based on that.

Partially motivated by chatting with two TransLink planners I decided to riff off of that and take a look at how well TransLink serves different parts of Vancouver. At different times of day. And how susceptible TransLink’s network is to Skytrain service disruptions.

More on Teardowns

| Comments

A little over a year ago we ran some analysis on teardowns of single family homes in the City of Vancouver. We used the City of Vancouver open data to understand why some single family homes got torn down and other’s don’t.

Relying entirely on open data, there were some important questions that could not be answered. So together with Joe Dahmen at UBC’s School Of Architecture And Landscape Architecture we came back to the question and folded in transaction data from BC Assessment to add some more details and rigor.

The result turned out quite similar to what our initial cruder methods came up with, but it lead to some important refinements.

We won’t go into the details of the findings here, you can read the online data story if you are interested. Instead we will go into a little more details how the analysis was done and what is still missing.

2016 Census Data - Part 1

| Comments

Finally the first batch of 2016 census data has arrived on Tuesday AM and CensusMapper was updated with the new census numbers by mid-morning.

Dissemination Block data was a little harder to find, but with the help of some friendly StatCan people I finally managed to locate the data and add that too this afternoon.

Time for writing up some observations. I am hoping to find time to do this regularly as more data gets released.

Jane Jacobs’ Vancouver

| Comments

Some time ago I saw Geoff Boeing’s excellent package to generate Jane Jacobs style street grid images. It’s lots of fun to compare different cities that way.

It can be hard to represent one city by one square mile, so I thought it would be neat to use this to compare different parts of Vancouver. Some common themes emerge for the central parts, the more outlying areas display very differnet patterns.

Bumper Year for Thumb Twiddlers

| Comments

Almost a year has passed since we first noticed how sitting on single family homes and twiddling thumbs generates more income than working. And not just at the level of individual single family households. In the City of Vancouver, the cumulative land value gains of just the single family homes eclipsed the cumulative taxable earnings reported to the CRA for the entire population.

With the new assessment data available now, it is time to run the numbers and see how our thumb-twiddlers fared vs workers this year. If you thought last year’s twiddling thumbs returns were crazy high, you better hold onto your hats!