September Package Picks

[This article was first published on RStudio, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

by Joseph Rickert

September was a bit of a slow month for new R packages. Only 96 new packages showed up un CRAN. Nevertheless, I have picked out 23 for special mention which I have listed in 5 categories. I used the same selection criteria as I described in the post for August picks.

Data and Interfaces

  • darksky V1.0.0: Provides an interface to the Dark Sky API which allows you to look up weather anywhere on the globe. 
  • etseed V0.1.0: Provides a client to interface to the etcd key value store, a database written in Go.
  • LendingClub V0.1.2: Lets investors manage their LendingClub investments from R.
  • sparklyr V0.4: Allows R users to connect, provision and interface to Apache Spark. Detailed examples using MLlib and H2O are available on the RStudio site.
  • trelloR: V0.1.0: Provides access to the Trello API. The vignette explains how to retrieve data from public and private Trello boards.
  • XRPython V0.7: A Python interface structured according to the general form of the package XR described in John Chamber’s book Extending R.

Machine Learning

  • ensembleR V0.1.0: Facilitates constructing ensemble models from machine learning models available in the caret package. There is a vignette to get started.
  • exprso V0.1.7: Provides a framework for supervised machine learning customized for biologists. There are several vignettes including a cheatsheet.


  • lowmemtkmeans V0.1.0: Implements trimmed k-means clustering with low memory use.
  • Textmining V0.0.2: Provides functions for text and topic mining. Full functionality requires installing TreeTagger.

Plots and Visualizations

  • plotluck V1.0.1: Is an intelligent tool built on top of ggplot2 that automatically generates plots from dataframes based on users providing variables to plot.
  • plotwidgets V0.4: Provides functions to produce small, self contained plots for use in larger plots.
hues <- seq(0, 360, by=30)
pos <- a2xy(hues, r=0.75)
for(i in 1:length(hues)) {
  cols <- modhueCol(pal, by=hues[i])
  wgPlanets(x=pos$x[i], y=pos$y[i], w=0.5, h=0.5, v=v, col=cols)
pos <- a2xy(hues[-1], r=0.4)
text(pos$x, pos$y, hues[-1])


  • Barycenter V1.0.0: Provides algorithms to compute the Wasserstein barycenter, the mean of a set of empirical probability measures.
  • musica V0.1.3: Provides functions for working with multivariate time series and custom time scales. There is a vignette to help you get started.
  • nhstplot V1.0.0: Provides functions to graphically illustrate the most common null hypothesis significance tests. The vignette provides some examples, e.g.:

  • nimble V0.6-1: Allows R programmers to write statistical models in the BUGS language. NIMBLE is built in R but compiles in C++. There is extensive documentation at
  • Rdice V1.0.1: Allows conducting sophisticated dice rolling and coin tossing experiments including experiments with Efron like Nontransitive dice. Have a look at the vignette.
  • splines2 V0.1.0: Provides functions for constructing a variety of splines that are not available in the splines package including B-splines,M-splines, I-splines, C-splines, and the integral of B-splines. There is a vignette.
  • scanstatistics V0.1.0: Provides scan statistics functions to detect anomalous clusters in spatial or space-time data. The vignette describes the methodology and presents examples as well.
  • thief V0.2: Implements methods for generating forecasts at different temporal frequencies using hierarchical time series.


With this post, I am up to date with new CRAN packages. I hope to make my package picks a regular, monthly feature of this blog.

To leave a comment for the author, please follow the link and comment on their blog: RStudio. offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)