The good folks at DataCamp track activity related to R packages on the RDocumentation.org Trends page. As of this writing, it tracks statistics on 11,768 packages (distributed across CRAN, BioConductor and Github) comprising over 1.7 million R functions in total. On that page, you can find current rankings on the most downloaded R packages, the most prolific package contributors, and the latest package releases and updates.
In a recent blog post, DataCamp gave an overview of the top 5 most downloaded packages, which currently stand at:
- dplyr, a grammar of data manipulation
- devtools, a collection of package development tools
- foreign, read data stored by Minitab, S, SAS, SPSS, Stata, and more
- cluster, methods for cluster analysis
- ggplot2, An implementation of the grammar of graphics in R
Those rankings are by the number of direct downloads, those initiated when an R user makes an explicit install.packages call. Many popular packages have dependencies, however, which are also downloaded when a package is installed. If you measure the top 5 packages by total downloads including those as a result of being a dependency, the top 5 rankings are:
- Rcpp, seamless R and C++ Integration. (Many packages incorporate C or C++ code via this package.)
- ggplot2, An implementation of the grammar of graphics in R
- stringr, simple, consistent wrappers for common string operations
- stringi, character string processing facilities
- reshape2, flexibly reshape data
If you're an R user who doesn't write R functions very often, the first collection of packages is probably familiar to you. But if you're an R developer who spends a lot of time writing functions (or packages), you're likely intimate with the second list as well.
For more details on the most popular R packages and the RDocumentation.org website, check out the link below.
DataCamp blog: The 5 most downloaded R packages
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