One often hears that R can not be fast (false), or more correctly that for fast code in R you may have to consider “vectorizing.” A lot of knowledgable R users are not comfortable with the term “vectorize”, and not really familiar with the method. “Vectorize” is just a slightly ...

RcppDynProg is a new Rcpp based R package that implements simple, but powerful, table-based dynamic programming. This package can be used to optimally solve the minimum cost partition into intervals problem (described below) and is useful in building piecewise estimates of functions (shown in this note). The abstract problem The ...

Reusable modeling pipelines are a practical idea that gets re-developed many times in many contexts. wrapr supplies a particularly powerful pipeline notation, and a pipe-stage re-use system (notes here). We will demonstrate this with the vtreat data preparation system. Our example task is to fit a model on some arbitrary ...

This note is a comment on some of the timings shared in the dplyr-0.8.0 pre-release announcement. The original published timings were as follows: With performance metrics: measurements are marketing. So let’s dig in the above a bit. These timings are of the kind of small task large number of ...

This note is just a quick follow-up to our last note on correcting the bias in estimated standard deviations for binomial experiments. For normal deviates there is, of course, a well know scaling correction that returns an unbiased estimate for observed standard deviations. It (from the same source): … provides an ...

This note is about attempting to remove the bias brought in by using sample standard deviation estimates to estimate an unknown true standard deviation of a population. We establish there is a bias, concentrate on why it is not important to remove it for reasonable sized samples, and (despite that) ...

We have our latest note on the theory of data wrangling up here. It discusses the roles of “block records” and “row records” in the cdata data transform tool. With that and the theory of how to design transforms, we think we have a pretty complete description of the system.

R is an interpreted programming language with vectorized data structures. This means a single R command can ask for very many arithmetic operations to be performed. This also means R computation can be fast. We will show an example of this using Conway’s Game of Life. Conway’s Game ...

Authors: John Mount, and Nina Zumel 2018-10-25 As a followup to our previous post, this post goes a bit deeper into reasoning about data transforms using the cdata package. The cdata packages demonstrates the "coordinatized data" theory and includes an implementation of the "fluid data" methodology for general data ...

In our wrapr pipe RJournal article we used piping into ggplot2 layers/geoms/items as an example. Being able to use the same pipe operator for data processing steps and for ggplot2 layering is a question that comes up from time to time (for example: Why can’t ggplot2 use %__%?). ...

Saghir Bashir of ilustat recently shared a nice getting started with R and tidyverse guide. In addition they were generous enough to link to Dirk Eddelbuette’s later adaption of the guide to use data.table. This type of cooperation and user choice is what keeps the R community vital. ...