The 5 most popular R packages

November 18, 2016

(This article was first published on Revolutions, and kindly contributed to R-bloggers)

The good folks at DataCamp track activity related to R packages on the 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:

  1. dplyr, a grammar of data manipulation
  2. devtools, a collection of package development tools
  3. foreign, read data stored by Minitab, S, SAS, SPSS, Stata, and more
  4. cluster, methods for cluster analysis
  5. 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:

  1. Rcpp, seamless R and C++ Integration. (Many packages incorporate C or C++ code via this package.)
  2. ggplot2, An implementation of the grammar of graphics in R
  3. stringr, simple, consistent wrappers for common string operations
  4. stringi, character string processing facilities
  5. 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 website, check out the link below.

DataCamp blog: The 5 most downloaded R packages 



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