Publications by Joseph Rickert
Missing Values, Data Science and R
by Joseph Rickert One great advantages of working in R is the quantity and sophistication of the statistical functions and techniques available. For example, R’s quantile() function allows you to select one of the nine different methods for computing quantiles. Who would have thought there could be so many ways to do something that seems to be ...
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Writing Good R Code and Writing Well
by Joseph Rickert If you are aspiring to write good R code, you may find it helpful to occasionally spend some time reading about writing: reading about writing R code, and reading about writing about R code that you’ve written. (If you write some excellent R code, you will likely have the opportunity to write about it.) For reading about writi...
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November Package Picks
by Joseph Rickert November was a prolific month for R developers: 189 new packages landed in CRAN. I have selected more than a quarter of them for this post, but I haven’t listed everything that is worth a look. My November 2016 picks are organized into four categories: Biotech (4 picks), Data (6 picks), Machine Learning (9 picks) , Statistics ...
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Get Ready for RStudio::Conf
by Joseph Rickert The 2017 R Conference season will get off to an early start on January 13th and 14th with RStudio::Conf 2017 in Orlando, Florida. The schedule promises an intense but collegial experience with plenty of hands-on practice working with R and the RStudio tool chain of packages and products. To prepare for the conference, I thought ...
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Interview with Joe Cheng
by Joseph Rickert Recently, I had the opportunity to interview RStudio’s Joe Cheng. Joe, the inventor and lead developer for Shiny, was the first person that J.J. Allaire invited to join the RStudio IDE project. We talked about those early days, how Shiny got started, Joe’s background as a software developer, his take on the R language and mo...
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10,000 CRAN Packages
by Joseph Rickert The R package system continues to expand as the number of packages on CRAN is about to blow through the 10,000 mark sometime soon. This is astonishing! Not only are new packages arriving at a rate of about 190 per month, but CRAN itself continues to tick along like a well-oiled machine, 24 by 7. We all owe a great deal of gratit...
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December 2016 Package Picks
by Joseph Rickert Last month, 217 new packages were submitted to CRAN. By my count this was the highest monthly value recorded for the past nine years. Below, are brief descriptions of fifty-two of these new-for-December packages grouped into six categories: Data, Data Science, Financial Analysis, Statistics, Utilities and Visualizations. The Fin...
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Some R News
by Joseph Rickert Here are a few things of some interest in the R world: The Gordon and Betty Moore Foundation has joined the R Consortium! This is a very positive development for the R Consortium and the R Community in general. The Moore Foundation has been a positive force for supporting technology that can make a real difference in people’s...
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Introducing sparklyr to the Madrid R User Group
by Carlos Ortega In the last meeting of 2016, the 40th in Madrid’s R Users Group five-year history, we had the opportunity to listen (via Skype) to a very interesting talk by Javier Luraschi, the main author of the package sparklyr. In our previous meeting, a colleague of the Community (José Luis Cañadas) made a first introduction to sparkly...
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The R Formula Method: The Good Parts
by Max Kuhn Introduction The formula interface to symbolically specify blocks of data is ubiquitous in R. It is commonly used to generate design matrices for modeling function (e.g. lm). In traditional linear model statistics, the design matrix is the two-dimensional representation of the predictor set where instances of data are in rows and vari...
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