Geeky

Active Fire

Playing with fire data.

Jens von Bergmann

2 minute read

The other day I saw a link to NASA active fire data fly by on Twitter. It’s a satellite-derived world wide dataset at 375m resolution, where one (or several) polar orbiting satellites scan earth in the infrared band from which fire and fire intensity is computed. Redding, CA With the Redding fire in the news I decided to take the data for a test drive. And also try out the gganimate package to watch the fire evolve over time.

Transit Data

Playing with our new R API wrapper for transit data from Transitland

Jens von Bergmann

3 minute read

The other day I was catching a bus home later at night, which made me acutely aware that I should not take the frequent daytime transit in Vancouver for granted. On the ride home I decided to dig into this and grab some transit data. We have played with transit data before, but since this was going to be the second time it was high time for a quick R package to standardize our efforts and simplify things for the next time around.

A Retrospective Look at NHS Income Data

How bad were the NHS income numbers?

Jens von Bergmann

13 minute read

NHS Income Data, a First Retrospective There was much hand wringing when NHS income data got released. The change in methods were big, most notably the replacement of the mandatory long form census, that was administered to a random 1 in 5 sub sample, by the voluntary NHS that went out to approximately 1 in 3 households. The (design-weighted) response rate for the NHS was 77%, compared to 94% for the long form in 2006.

Evolution of the Income Distribution

Digging deeper into the evolution of incomes

Jens von Bergmann

9 minute read

Vancouver’s median household income has grown. But there are many ways how this could have happened. We want to take a deeper look to understand how the income distribution changed. To that end, we will investigate the change in the number of people in each income bracket between the census years. And put that into context to what happened in the region and Canada wide. This is a mixture of what we have done when comparing the size of age groups between censuses.

dot-density

Multi-category dot-density maps are hard.

Jens von Bergmann

10 minute read

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.