We have updated the errata for Practical Data Science with R to reflect that it is no longer worth the effort to use the Java version of SQLScrewdriver as described. We are very sorry for any confusion, trouble, or wasted effort bringing in Java software (something we are very familiar […]

Estimated reading time: 1 minute

replyr is an R package that contains extensions, adaptions, and work-arounds to make remote R dplyr data sources (including big data systems such as Spark) behave more like local data. This allows the analyst to more easily develop and debug procedures that simultaneously work on a variety of data services […]

Estimated reading time: 11 minutes

Consider the common following problem: compute for a data set (say the infamous iris example data set) per-group ranks. Suppose we want the rank of iris Sepal.Lengths on a per-Species basis. Frankly this is an “ugh” problem for many analysts: it involves all at the same time grouping, ordering, and […]

Estimated reading time: 16 minutes

Statisticians and data scientists want a neat world where data is arranged in a table such that every row is an observation or instance, and every column is a variable or measurement. Getting to this state of “ready to model format” (often called a denormalized form by relational algebra types) […]

Estimated reading time: 8 minutes

A great number of readers reacted very positively to Nina Zumel‘s article Using PostgreSQL in R: A quick how-to. Part of the reason is she described an incredibly powerful data science pattern: using a formerly expensive permanent system infrastructure as a simple transient tool. In her case the tools were […]

Estimated reading time: 7 minutes

The combination of R plus SQL offers an attractive way to work with what we call medium-scale data: data that’s perhaps too large to gracefully work with in its entirety within your favorite desktop analysis tool (whether that be R or Excel), but too small to justify the overhead of […]

Estimated reading time: 10 minutes