Publications by James
Great Maps with ggplot2
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 in the comments). The map cont...
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Mapped: British, Spanish and Dutch Shipping 1750-1800
I recently stumbled upon a fascinating dataset which contains digitised information from the log books of ships (mostly from Britain, France, Spain and The Netherlands) sailing between 1750 and 1850. The creation of this dataset was completed as part of the Climatological Database for the World’s Oceans 1750-1850 (CLIWOC) project. The routes a...
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Mapping the World’s Biggest Airlines
The map above shows the routes flown by the top 7 airlines (by international passenger distance flown). The base map shows large urban areas and I have attempted to make it look a bit like the beautiful “Earth at Night” composite image produced by NASA. You can clearly see a relationship between where people live and where the big carriers fl...
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Mapped: Twitter Languages in New York
Following the interest in our Twitter Tongues map for London, Ed Manley and I have teamed up with Trendsmap creator John Barratt to offer this snapshot of New York City’s Twitter languages. We have visualised the geography of about 8.5 million geo-located tweets collected between Jan 2010 and Feb 2013. Each tweet is marked by a slightly tra...
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Starting Analysis and Visualisation of Spatial Data with R
Last week I ran an introductory workshop on the analysis and visualisation of spatial data with R. The software has become established as one of the best around for statistics and it is becoming increasingly recognised as a tool for data visualisation (I wrote about this last year, also see here) and spatial analysis. Interest in R is increasin...
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A Crash Course in R
This code has been kindly contributed by Robin Edwards (from UCL CASA). There are many useful introductory guides out there to R, but below is the kind of thing I now wish I’d been given when I first started using it – something with simple logically-progressive examples and minimal explanatory text. Copy the text below into a new script in...
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3D Mapping in R
This tutorial has been kindly contributed by Robin Edwards (from UCL CASA). RGL is R’s box of power-tool for 3D object rendering, with functionality for creating 3d mesh objects and curved surfaces, and for using materials and directional lighting. For example the line: plot3d(rnorm(100),rnorm(100),rnorm(100)) creates a 3d scatterplot o...
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Where is the R Activity?
R has become one of the world’s most widely used statistics and visualisation software packages with an ever growing user community. Thanks to the release of log files containing all hits to http://cran.rstudio.com/ server it is possible to make a map showing the parts of the world with the most active R users (specifically those mostly us...
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Introduction to Spatial Data and ggplot2
For those starting out with spatial data in R, Robin Lovelace and I have prepared this tutorial (funded as part of the University of Leeds and UCL Talisman project). Here we introduce a range of analysis skills before demonstrating how you can deploy the powerful graphics capabilities of ggplot2 to visualise your results. There is also some “bo...
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Coxcomb Plots and Spiecharts in R
I am not a great fan of pie charts since they are often used for the sake of it in circumstances where a chart is not needed at all! That said, I am willing to make an exception for “Coxcomb Plots” as pioneered by Florence Nightingale since they increase the data density on the plot and can enable comparisons across variables. Robin Lovelac...
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