dplyr issue 2916.
The following appears to work.
COL <- "homeworld"
## # A tibble: 1 x 14
## # Groups: COL 
## name height mass hair_color skin_color eye_color birth_year
## <chr> <int> <dbl> <chr> <chr> <chr> <dbl>
## 1 Luke Skywalker 172 77 blond fair blue 19
## # ... with 7 more variables: gender <chr>, homeworld <chr>, species <chr>,
## # films <list>, vehicles <list>, starships <list>, COL <chr>
Though notice it reports the grouping is by "
COL", not by "
homeworld". Also the data set now has
14 columns, not the original
13 from the
starwars data set.
Continue reading Please Consider Using wrapr::let() for Replacement Tasks
The development version of our
R helper function
wrapr::let() has switched from string-based substitution to abstract syntax tree based substitution (AST based subsitution, or language based substitution).
I am looking for some feedback from
wrapr::let() users already doing substantial work with
wrapr::let(). If you are already using
wrapr::let() please test if the current development version of
wrapr works with your code. If you run into problems: I apologize, and please file a
Continue reading wrapr Implementation Update
In this article we will discuss composing standard-evaluation interfaces (SE) and composing non-standard-evaluation interfaces (NSE) in
R the package
rlang is a tool for building domain specific languages intended to allow easier composition of NSE interfaces.
To use it you must know some of its structure and notation. Here are some details paraphrased from the major
rlang client, the package dplyr:
vignette('programming', package = 'dplyr')).
:=" is needed to make left-hand-side re-mapping possible (adding yet another "more than one assignment type operator running around" notation issue).
!!" substitution requires parenthesis to safely bind (so the notation is actually "
(!! )", not "
- Left-hand-sides of expressions are names or strings, while right-hand-sides are
Continue reading Non-Standard Evaluation and Function Composition in R
Here is an absolutely horrible way to confuse yourself and get an inflated reported
R-squared on a simple linear regression model in
We have written about this before, but we found a new twist on the problem (interactions with categorical variable encoding) which we would like to call out here. Continue reading An easy way to accidentally inflate reported R-squared in linear regression models
This note describes a useful
replyr tool we call a "join controller" (and is part of our "R and Big Data" series, please see here for the introduction, and here for one our big data courses).
Continue reading Use a Join Controller to Document Your Work
Let’s worry a bit about substitution in
R. Substitution is very powerful, which means it can be both used and mis-used. However, that does not mean every use is unsafe or a mistake.
Continue reading More on safe substitution in R
Python has a fairly famous design principle (from “PEP 20 — The Zen of Python”):
There should be one– and preferably only one –obvious way to do it.
R (especially once you add many packages) there is usually more than one way. As an example we will talk about the common
head(), and the
glimpse(). Continue reading There is usually more than one way in R
Here is a really nice feature found in the current 3.4.0 version of R: summary() has become a lot more reasonable.
# Min. 1st Qu. Median Mean 3rd Qu. Max.
# 15555 15555 15555 15555 15555 15555
Please read on for some background. Continue reading R summary() got better!