wrapr 2.0.0 up on CRAN
wrapr 2.0.0 is now up on CRAN. This means the := variant of unpack[] is now easy to install. Please give it a try!
wrapr 2.0.0 is now up on CRAN. This means the := variant of unpack[] is now easy to install. Please give it a try!
For data science projects I recommend using source control or version control, and committing changes at a very fine level of granularity. This means checking in possibly broken code, and the possibly weak commit messages (so when working in a shared project, you may want a private branch or second […]
Here is an example how easy it is to use cdata to re-layout your data. Tim Morris recently tweeted the following problem (corrected). Please will you take pity on me #rstats folks? I only want to reshape two variables x & y from wide to long! Starting with: d xa […]
As of cdata version 1.0.8 cdata implements an operator notation for data transform. The idea is simple, yet powerful.
With all of the excitement surrounding cdata style control table based data transforms (the cdata ideas being named as the “replacements” for tidyr‘s current methodology, by the tidyr authors themselves!) I thought I would take a moment to describe how they work.
Recently ran into something interesting in the R macros/quasi-quotation/substitution/syntax front: Romain François: “.@_lionelhenry reveals planned double curly syntax At #satRdayParis as a possible replacement, addition to !! and enquo()” It appears !! is no longer the last word in substitution (it certainly wasn’t the first).
To make getting started with rquery (an advanced query generator for R) easier we have re-worked the package README for various data-sources (including SparkR!).
Recently Hadley Wickham prescribed pronouncing the magrittr pipe as “then” and using right-assignment as follows: I am not sure if it is a good or bad idea. But let’s play with it a bit, and perhaps readers can submit their experience and opinions in the comments section.
While developing the RcppDynProg R package I took a little extra time to port the core algorithm from C++ to both R and Python. This means I can time the exact same algorithm implemented nearly identically in each of these three languages. So I can extract some comparative “apples to […]
In our last note we used wrapr::qe() to help quote expressions. In this note we will discuss quoting and code-capturing interfaces (interfaces that capture user source code) a bit more.