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Introducing rleafmap. An R package for interactive maps with Leaflet.

Introducing rleafmap. An R package for interactive maps with Leaflet.

Obviously, I am late…

I released rleafmap about 1 year ago and I am just writing this blog post today. During this time, I presented the package to the french R-users community at the 3eme Rencontres R in Montpellier and could get some good feedbacks. Now, I would like to communicate better on the project. My idea is to post news about the development and communicate on new features illustrated with examples on this blog. The documentation and tutorials will be published on the project website (http://www.francoiskeck.fr/rleafmap/) if I can save time for that.

Purpose and philosophy

rleafmap is an R package that can be used to generate interactive maps with your data. If you manipulate spatial data in the R environment, at some point you probably want to visualize them. The most common way to visualize spatial data is maps. Like other packages (googleVis, rMaps…) rleafmap is designed to produce maps with interactivity to bring a richer experience to the end user. This is made possible by the use of Leaflet, the amazing open-source javascript library created by Vladimir Agafonkin.

There are two things important to be aware for a good start with rleafmap.

  • First, the package use exclusively input data inheriting from the Spatial class of the sp package. These classes are central and allows to work with many packages. If you don’t know it, a good place to start is the vignette of the sp package on CRAN. If you prefer a good book have look to Bivand et al. 2013 [1].
  • The second point is about how the package works. Data layers are stored in independent R object with their own symbology. The map consists in a compilation of these objects. The idea is to stick to the philosophy of the traditional GIS software.

For a more complete view of the package I strongly recommend that you have a look to the website.

[1] Bivand R.S., Pebesma E.J. & Gómez-Rubio V. (2013) Applied Spatial Data Analysis with R, 2nd edn. Springer, New York.

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