Canada’s metropolitan areas are growing, which means we need to add housing. But adding housing often faces stiff oppositions. There are many reasons people don’t like to add housing, this post is trying to look at one particular one. That adding housing causes displacement of the low-income population. Adding new housing to a neighbourhood has two opposing effects. The gentrification effect starts from the observation that new housing is more expensive than old housing (all else being equal).
Vancouver had elections on Saturday, today Toronto had their elections. And as opposed to Vancouver, Toronto has wards. Which makes things more fun, as we can look at census data for each ward to understand how people voted in the ward. We ran a very similar type of analysis the other day for Vancouver, so this is an easy add. The Toronto Open Data catalogue has data for the ward boundaries and a custom tab with census data.
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.
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.
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.