Introduction to Spatial Data and ggplot2
For those starting out with spatial data in R, Robin Lo […]
Continue reading »Category: R Spatial Tips
Starting Analysis and Visualisation of Spatial Data with R
Last week I ran an introductory workshop on the analysi […]
Continue reading »Mapped: Twitter Languages in New York
Following the interest in our Twitter Tongues map for L […]
Continue reading »Mapping the World’s Biggest Airlines
The map above shows the routes flown by the top 7 airli […]
Continue reading »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 are plotted from the …
Continue reading »London Cycle Hire and Pollution
As a cyclist in London you can do your best to avoid left turning buses and dozy pedestrians. One thing you can’t really avoid though is pollution (although I accept cyclists probably aren’t much worse off than pedestrians and drivers in this respect). To illustrate this I have taken data for 3.2 million journeys from …
Continue reading »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 …
Continue reading »Coming of Age: R and Spatial Data Visualisation
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 …
Continue reading »Improved Tree Maps with R
“Treemaps display hierarchical (tree-structured) data as a set of nested rectangles. Each branch of the tree is given a rectangle, which is then tiled with smaller rectangles representing sub-branches. A leaf node’s rectangle has an area proportional to a specified dimension on the data. Often the leaf nodes are colored to show a separate dimension of …
Continue reading »Global Migration Maps
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 tip) …
Continue reading »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 …
Continue reading »Using R to Map with Google Chart Tools
The release of the R package “googleVis” has made the production of interactive maps through Google’s Chart Tools a simple task. Ignoring the some basic data manipulation the below map was produced with these two lines of code: library(googleVis) Geo=gvisGeoMap(Map, locationvar=”Country”, numvar=”Percentage”, options=list(height=350, dataMode=’regions’)) plot(Geo) This map, although simple to produce, is nontrivial as it …
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