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Posted by on Nov 6, 2014 in London, R Spatial, Visualisation | 6 comments

Improving R Data Visualisations Through Design

Improving R Data Visualisations Through Design

When I start an R class, one of my opening lines is nearly always that the software is now used by the likes of the New York Times graphics department or Facebook to manipulate their data and produce great visualisations. After saying this, however, I have always struggled to give tangible examples of how an R output blossoms into a stunning and informative graphic. That is until now… I spent the past year working hard with an amazing designer – Oliver Uberti – to create a book of 100+ maps and graphics about London. The majority of graphics we produced for London: The Information Capital required R code in some shape or form. This was used to do anything from simplifying millions of GPS tracks, to creating bubble charts or simply drawing a load of straight lines. We had to produce a graphic every three days to hit the publication deadline so without the efficiencies of copying and pasting old R code, or the flexibility to do almost any kind of plot, the book would not...

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Posted by on Oct 24, 2013 in Visualisation | 0 comments

Cinematic Mapping

Cinematic Mapping

I recently posted a great visualisation showing 24 hours of shipping in the Baltic. I liked it for its cinematic appeal (was a bit less keen on the music though), and said that such work goes a long way to broaden the appeal of data visualisation. 422 are the masters of this art, producing a great number of innovative visualisations for TV programmes around the world. I first saw their work on the “Britain from Above” series shown on the BBC and have been amazed at what they have been able to produce ever since. The video above is a montage of some of their projects....

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Posted by on May 13, 2013 in Video, Visualisation | 0 comments

The Art of Data Visualisation Video

The Art of Data Visualisation Video

Map design and cartography are now, more than ever, seen as just one set of tools in a growing data visualisation arsenal. This video features well-known data visualisers who talk through some of their guiding principles, offering many insights for those working with geographic data. (via Visualising...

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Posted by on Apr 8, 2013 in R Spatial, Resources, Spatial Analysis | 3 comments

Starting Analysis and Visualisation of Spatial Data with R

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 increasing all the time but many feel put off by its very steep learning curve. The help files are often complex and there are some slightly idiosyncratic aspects to the language you have use to get R to work. That said there is lot more help around on forums and some excellent introductory tutorials to get  you started. Here are a couple of worksheets I use to introduce the wonders of R. The first is written by Richard Harris from the University of Bristol. You can download the worksheet here and the example data from here. I like this worksheet because it is very applied (it is using a real dataset on an important problem), it gets you...

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Posted by on Aug 17, 2012 in Spatial Analysis, Visualisation | 2 comments

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In Maps We Trust

In Maps We Trust

Of all the different types of data visualisation, maps* seem to have the best reputation. I think people are much less likely to trust a pie chart, for example, than a map. In a sense, this is amazing given that all maps are abstractions from reality.  They can never tell the whole truth and are nearly all based on data with some degree of uncertainty that will vary over large geographic areas. An extreme interpretation of this view is that all maps are wrong- in which case we shouldn’t bother making them. A more moderate view (and the one I take) is that maps are never perfect so we need to create and use them responsibly – not making them at all would make us worse off. This responsibility criterion is incredibly important because of the high levels of belief people have in maps. You have to ask: What are the consequences of the map you have made? Now that maps are easier than ever to produce, they risk...

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