These packages can be installed individually with install.packages("spData") etc or by uncommenting and executing the first command in the code chunk, which installs all packages needed to reproduce the code in Geocomputation with R.THESE days, in the thick of the American presidential primaries, it’s easy to see how the 50 states continue to drive the political system. I also encourage community contributions on any part of the book, for example by using the issue tracker. It can be edited from our github repo or by clicking on the ‘edit’ pencil-shaped symbol at the top left of any part of the book: A regularly updated online version of the Geocomputation with R book can be found at. The blogpost builds on the content in Chapter 8 of the book Geocomputation with R. This improves on maps of the United States that only show the mainland or greatly reduce the relative size of Hawaii and Alaska.īut there is scope for further improvement building on the reproducible code above (a fun challenge is to recreate the map without any copy-pasting): I look forward to any suggestions how this map can be improved! Contact me on twitter or github - see information below. The final map is an approximation of areal relationships between the mainland, Alaska and Hawaii. Height = us_states_hawaii_ratio / sum( c( us_states_alaska_ratio, 1)))) Print( hawaii_map, vp = viewport(x = 0.3, y = 0.07, Print( us_states_map, vp = viewport( = 2)) Heights = unit( c( us_states_alaska_ratio, 1), "null")))) PushViewport( viewport(layout = grid.layout( 2, 1,
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