The above map (and this one) was produced using R and ggplot2 and serve to demonstrate just how sophisticated R visualisations can be. We are used to seeing similar maps produced with conventional GIS platforms or software such as Processing but I hadn’t yet seen one from the R community (feel free to suggest some ...
I have been using R (a free statistics and graphics software package) now for the past four years or so and I have seen it become an increasingly powerful method of both analysing and visualising spatial data. Crucially, more and more people are writing accessible tutorials (see here) for beginners and intermediate users and the development ...
Migrations of people have existed for millennia and occur at a range of scales and time-periods (from small-scale journeys to work through to intercontinental resettlement). As a geographer I have long been interested in these and thought it was about time I mapped them! Using data from the Global Migrant Origin Database (thanks Adam for the ...
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 ...
Hans Rosling eat your heart out! It is now possible to interface R statistics software to Google’s Gapminder inspired Chart Tools. The plots below were produced using the googleVis R package and three datasets from the Gapminder website. The first shows the relationship between income, life expectancy and population for 20 countries with the highest ...
The visualisation above shows the average relative duration of Boris Bikers’ weekday journeys over a 4 month period at hourly intervals. For each time step the average journey time (in seconds) from each docking station has been calculated.This information is interesting because it shows the preference for short journeys around the City of London, whilst ...
Google Earth has become a popular way of disseminating spatial data. KML is the data format required to do this. It is possible to load almost any type of spatial data format into R and export it as a KML file. In my experience R seems much quicker at doing this than many well-known GIS ...
******Roger Bivand has kindly just emailed me to say: “Your 2 November blog about rgdal on OSX is very misleading. The CRAN rgdal page: http://cran.r-project.org/web/packages/rgdal/index.html says all you need to know unless you need extra drivers, or already have PROJ.4 and GDAL installed. Just do: setRepositories(ind=1:2) install.packages(“rgdal”) installs rgdal with all its external dependencies satisfied. It is ...
The ggplot2 package offers powerful tools to plot data in R. The plots are designed to comply with the “grammar of graphics” philosophy and can be produced to a publishable level relatively easily. For users wishing to create a good map without too much thought I would recommend this worksheet. For those without their own ...
Background: A common function in standard GIS software enables users to create a raster surface and extract values or clip it based on a set of polygons. This may be used in cases where you want analysis to be constrained to within a town’s boundaries or a coastline. This tutorial will outline how to create ...
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