Since 2013, a website I developed has provided information on places from the South African National Census of 2011. Recently I’ve developed a GraphQL API to make that data available to other developers. In parallel with this API development, I’ve also added some extra data, and made some changes to the website. Read on for more details.
I’ve updated my Western Cape number plate map from 2014 to include the new CAA code for Cape Town.
This post presents a selection of maps I have produced in the last few weeks. If you follow me on Twitter or on Reddit you will have seen most of these already. All the images below are clickable thumbnails which link to a full-size version.
Five years ago, after the 2014 general election, I built an interactive map of the election results. Since then the state of the technology for web mapping has moved on, so I’ve developed a completely new version. This new map uses vector tiles for better rendering, includes results for four general elections (2004–2019), and allows you to drill all the way down to voting district level. And here it is.
The linguistic diversity index measures the probability that two people selected at random from a population speak different home languages. The map below, which I produced, depicts the linguistic diversity index calculated on a 10-kilometre-wide hexagonal grid across South Africa.
I’ve made an interactive website with six sets of topographic maps of Cape Town and surrounds covering the period from 1940 to 2010. You can zoom in and move around the maps, switching from one era to another.
The post-apartheid political map of South Africa might well have looked quite different. The Eastern Cape might have been divided into two provinces, with the Kat River and Great Fish River on the boundary. The Northern Cape might not have existed, with the Western Cape meeting North West at the Orange River. Gauteng might have been much bigger – or much smaller. The Western Cape might have stopped south of Citrusdal – or it might have incorporated all of Namaqualand.
After the recent US Supreme Court ruling legalising same-sex marriage (SSM) throughout that country, a claim was recently brought up on a Wikipedia talk page that more than one billion people now live in countries (or states/provinces) where SSM is legal. I thought I’d check out the numbers, and update my old graph showing how this has changed over time.
As “the data guy” for the Democratic Alliance, naturally my job involves working with election result data. This post is a collection of mildly interesting facts I’ve learned about the 2014 elections in the course of my work. I’ll start off with a quite surprising fact: the location of the busiest voting station.
My post yesterday discussed the mean centres of population of South Africa and its provinces. The mean centre is (relatively) easy to calculate, but it may not be the most useful type of population centre. It is essentially an arithmetic mean, which means that outliers can have a massive effect on the centre. It minimizes the average square of distance from the centre, not the average distance from the centre. The centre that does minimize the average distance is called the geometric median, and it is not quite so simple to calculate, since there is no closed form solution. But it can be done!