Posted on Categories data science, Exciting Techniques, Statistics, TutorialsTags , , , 4 Comments on Nifty Upcoming Enhancements to unpack/to

Nifty Upcoming Enhancements to unpack/to

We have some really nifty upcoming enhancements to wrapr unpack/to.

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Posted on Categories AdministrativiaTags , Leave a comment on wrapr Update: Removing Some Under-Used Functions and Classes

wrapr Update: Removing Some Under-Used Functions and Classes

For the next version of the R package wrapr we are going to be removing a number of under-used functions/methods and classes. This update will likely happen in March 2020, and is the start of the wrapr 2.* series.

Most of the items being removed are different abstractions for helping with function composition. We ended up moving most of our work to category-theory based composition, so don’t think these various frameworks are needed any longer. If you have been using these items in your own projects, please reach out and we try and find a way to help you out.

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Posted on Categories Administrativia, data science, Practical Data Science, Pragmatic Data Science, Pragmatic Machine Learning, Statistics, TutorialsTags , , , 2 Comments on wrapr 1.9.6 is now up on CRAN

wrapr 1.9.6 is now up on CRAN

wrapr 1.9.6 is now up on CRAN.

We unfortunately usually forget to say this. A big thank you to the staff and volunteers at CRAN.

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Posted on Categories Exciting Techniques, Practical Data Science, Pragmatic Data Science, Pragmatic Machine Learning, TutorialsTags , , , , Leave a comment on Why we wrote wrapr to/unpack

Why we wrote wrapr to/unpack

One reason we are developing the wrapr to/unpack methods is the following: we wanted to spruce up the R vtreat interface a bit.

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Posted on Categories Exciting Techniques, TutorialsTags , , , Leave a comment on unpack Your Values in R

unpack Your Values in R

I would like to introduce an exciting feature in the upcoming 1.9.6 version of the wrapr R package: value unpacking.

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Posted on Categories Exciting Techniques, TutorialsTags , , , 1 Comment on “If You Were an R Function, What Function Would You Be?”

“If You Were an R Function, What Function Would You Be?”

We’ve been getting some good uptake on our piping in R article announcement.

The article is necessarily a bit technical. But one of its key points comes from the observation that piping into names is a special opportunity to give general objects the following personality quiz: “If you were an R function, what function would you be?”

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R Journal Volume 10/2, December 2018 is out!

We forgot to say: R Journal Volume 10/2, December 2018 is out!

RLogo

A huge thanks to the editors who work very hard to make this possible.

And big “thank you” to the editors, referees, and journal for helping improve, and for including our note on pipes in R.

Posted on Categories Coding, OpinionTags , , , ,

Playing With Pipe Notations

Recently Hadley Wickham prescribed pronouncing the magrittr pipe as “then” and using right-assignment as follows:

NewImage

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.

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Posted on Categories data science, Exciting Techniques, TutorialsTags , , , , 1 Comment on Function Objects and Pipelines in R

Function Objects and Pipelines in R

Composing functions and sequencing operations are core programming concepts.

Some notable realizations of sequencing or pipelining operations include:

The idea is: many important calculations can be considered as a sequence of transforms applied to a data set. Each step may be a function taking many arguments. It is often the case that only one of each function’s arguments is primary, and the rest are parameters. For data science applications this is particularly common, so having convenient pipeline notation can be a plus. An example of a non-trivial data processing pipeline can be found here.

In this note we will discuss the advanced R pipeline operator "dot arrow pipe" and an S4 class (wrapr::UnaryFn) that makes working with pipeline notation much more powerful and much easier.

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