Posted on Categories Coding, OpinionTags , , 15 Comments on Running the Same Task in Python and R

Running the Same Task in Python and R

According to a KDD poll fewer respondents (by rate) used only R in 2017 than in 2016. At the same time more respondents (by rate) used only Python in 2017 than in 2016.

Let’s take this as an excuse to take a quick look at what happens when we try a task in both systems.

Continue reading Running the Same Task in Python and R

Posted on Categories Opinion, ProgrammingTags , 4 Comments on A Better Example of the Confused By The Environment Issue

A Better Example of the Confused By The Environment Issue

Our interference from then environment issue was a bit subtle. But there are variations that can be a bit more insidious.

Please consider the following.

Continue reading A Better Example of the Confused By The Environment Issue

Posted on Categories Opinion, Programming, TutorialsTags , 5 Comments on A Subtle Flaw in Some Popular R NSE Interfaces

A Subtle Flaw in Some Popular R NSE Interfaces

It is no great secret: I like value oriented interfaces that preserve referential transparency. It is the side of the public debate I take in R programming.

"One of the most useful properties of expressions is that called by Quine referential transparency. In essence this means that if we wish to find the value of an expression which contains a sub-expression, the only thing we need to know about the sub-expression is its value."

Christopher Strachey, "Fundamental Concepts in Programming Languages", Higher-Order and Symbolic Computation, 13, 1149, 2000, Kluwer Academic Publishers (lecture notes written by Christopher Strachey for the International Summer School in Computer Programming at Copenhagen in August, 1967).

Please read on for discussion of a subtle bug shared by a few popular non-standard evaluation interfaces.

Continue reading A Subtle Flaw in Some Popular R NSE Interfaces

Posted on Categories Opinion, Programming, TutorialsTags , , ,

Timing Column Indexing in R

I’ve ended up (almost accidentally) collecting a number of different solutions to the “use a column to choose values from other columns in R” problem.

Please read on for a brief benchmark comparing these methods/solutions.

Continue reading Timing Column Indexing in R

Posted on Categories Opinion, Programming, TutorialsTags , , , , 4 Comments on Parameterizing with bquote

Parameterizing with bquote

One thing that is sure to get lost in my long note on macros in R is just how concise and powerful macros are. The problem is macros are concise, but they do a lot for you. So you get bogged down when you explain the joke.

Let’s try to be concise.

Continue reading Parameterizing with bquote

Posted on Categories Opinion, ProgrammingTags , , 2 Comments on Better R Code with wrapr Dot Arrow

Better R Code with wrapr Dot Arrow

Our R package wrapr supplies a "piping operator" that we feel is a real improvement in R code piped-style coding.

The idea is: with wrapr‘s "dot arrow" pipe "%.>%" the expression "A %.>% B" is treated very much like "{. <- A; B}". In particular this lets users think of "A %.>% B(.)" as a left-to-right way to write "B(A)" (i.e. under the convention of writing-out the dot arguments, the pipe looks a bit like left to right function composition, call this explicit dot notation).

This sort of notation becomes useful when we compose many steps. Some consider "A %.>% B(.) %.>% C(.) %.>% D(.)" to be easier to read and easier to maintain than "D(C(B(A)))".

Continue reading Better R Code with wrapr Dot Arrow

Posted on Categories Opinion, Practical Data Science, StatisticsTags , 2 Comments on Practical Data Science with R2

Practical Data Science with R2

The secret is out: Nina Zumel and I are busy working on Practical Data Science with R2, the second edition of our best selling book on learning data science using the R language.

Our publisher, Manning, has a great slide deck describing the book (and a discount code!!!) here:

Pdsr2s

We also just got back our part-1 technical review for the new book. Here is a quote from the technical review we are particularly proud of:

The dot notation for base R and the dplyr package did make me stand up and think. Certain things suddenly made sense.

Continue reading Practical Data Science with R2

Posted on Categories data science, Opinion, Practical Data Science, Pragmatic Data Science, TutorialsTags , , , , 7 Comments on R Tip: Give data.table a Try

R Tip: Give data.table a Try

If your R or dplyr work is taking what you consider to be a too long (seconds instead of instant, or minutes instead of seconds, or hours instead of minutes, or a day instead of an hour) then try data.table.

For some tasks data.table is routinely faster than alternatives at pretty much all scales (example timings here).

If your project is large (millions of rows, hundreds of columns) you really should rent an an Amazon EC2 r4.8xlarge (244 GiB RAM) machine for an hour for about $2.13 (quick setup instructions here) and experience speed at scale.