How I used the kknn and ggplot2 packages together with some parallel computation to spatially interpolate several hundred thousand points.
Recently I made a point for “true” RMarkdown reproducibility via checkpointed package versions. Shortly thereafter I learned the hard way how crucial it is to use exactly the same R packages that were used when the script was initially written.
Since more than two years I have been preaching reproducibility and transparency in data journalism. My tool of choice: R and reproducible reports with RMarkdown.
But these reports aren’t really reproducible. A solution.
In this blog post, I explain step by step how I (eventually) achieved a nice thematic map with pure ggplot2 – from a very basic, useless, ugly, default map to the publication-ready and (in my opinion) highly aesthetic choropleth.
For me, 2015 was the year of R. The year I finally started to use R productively and on an almost daily basis (after years of learning and forgetting and learning all over again). In this post, I share my experiences and tell you why you should start using it for your next data journalism project in 2016.