Mapping London’s Population Change 1801-2030
Buried in the London Datastore are the population estimates for each of the London Boroughs between 2001 – 2030. They predict a declining population for most boroughs with the exception of a few to the east. I was surprised by this general decline and also the numbers involved- I expected larger changes from one year to the next. I think this is because my perception of migration is of the volume of people moving rather than the net effects on the baseline population of these movements. I don’t envy the GLA for making predictions so far into the future, but can understand why they have to do it (think how long it took initiate Crossrail!). Last year I produced a simple animation showing past changes in London’s population density (data) and it provides a nice comparison to the above. In total I have squeezed 40 maps on this page!
Technical Stuff
These maps were all produced to demonstrate the mapping capabilities of R. The first uses ggplot2 (plus classInt + RColorBrewer) and is based on some code (see below) written by Mark Bulling. If you follow the code below you will end up with this map, not the one I have produced above. I will stick my code in a formal tutorial soon. The animation uses the standard plot functions (plus spatial packages) in R as per this example.
Very interesting post James. Interesting blog, though I’ve not commented before. You may be interested in this (or you may not…):
http://undertheraedar.blogspot.com/2010/03/visualising-london-population-growth.html
and this:
http://www.centreforcities.org/granddesigns.html
Keep up the good work!
Great Job!! Keep up the good work.
Cheers from Sweden.
Daniel
Hi,
Thanks for posting this. I’m working through MB’s code and encountered an error at line 30.
> london.data.cast <- cast(london.data.melt, variable~., fun.aggregate=sum)
Error: Casting formula contains variables not found in molten data: variable
Do you know what is needed to successfully cast the data? Any help will be greatly appreciated.
Best regards,
Christy
Hi,
I was able to work through the code provided, to produce the map you linked to, by fixing two lines of code.
The line that reads:
london.data.melt <- melt(x, id=c("Code", "Area",
"Total.Number.of.Registrations", "MYE.Working.age.2008"))
works if changed to:
london.data.melt <- melt(london.data, id=c("Code", "Area",
"Total.Number.of.Registrations"))
and the line that reads:
scale_fill_brewer(palette = "PuRd", label_value = "Number of
registered immigrants")+
works if changed to:
scale_fill_brewer(palette = "PuRd")+
Thanks again for posting!!
Hi,
I was able to work through the code provided, to produce the map you linked to, by fixing two lines of code.
The line that reads:
> london.data.melt london.data.melt scale_fill_brewer(palette = “PuRd”, label_value = “Number of registered immigrants”)+
works if changed to:
> scale_fill_brewer(palette = “PuRd”)+
Thanks again for posting!!
Hi,
I’d to know if you’ve already posted the tutorial. I’ve just turned to R’s geovisualization capabilities recently, so I’d appreciate a lot to see your tutorial as it would help me a lot to master R mapping capabilities, which currently I use mainly in cross-sectional analysis of geodata.