Construct list from a dataframe and a formula

Question

A dataframe and a right-sided formula are given:

dat <- data.frame(
  A = c("a", "b", "c"),
  B = c("x", "y", "z"),
  NotUsed = c(1, 2, 3)
)

frml <- ~ A + B + A:B

From them, I want to get this list:

# [[1]]
# [1] a b c
# Levels: a b c
# 
# [[2]]
# [1] x y z
# Levels: x y z
# 
# [[3]]
# [1] a:x b:y c:z
# Levels: a:x b:y c:z

Here is how I get this list:

library(lazyeval) # to use 'as.lazy' and 'lazy_eval'
tf <- terms.formula(frml)
factors <- rownames(attr(tf, "factors"))
tvars <- attr(tf, "variables")
tlabs <- attr(tf, "term.labels")
used <- lapply(eval(tvars, envir = dat), as.factor)
names(used) <- factors
lapply(tlabs, function(tlab){
  droplevels(lazy_eval(as.lazy(tlab), data = used))
})

Do you have a better way to propose?

Answer 1

Code Quality

Blank Lines

Generally, your code quality needs some improvement. For example, insert blank lines. So instead of

factors <- rownames(attr(tf, "factors"))
tvars <- attr(tf, "variables")
tlabs <- attr(tf, "term.labels")

I would suggest

factors <- rownames(attr(tf, "factors"))

tvars <- attr(tf, "variables")

tlabs <- attr(tf, "term.labels")

Order Within A Script or Source Code

Generally, one puts package import statements at the top of a file. Which you are not doing, and you also give no reason why you are doing it. So I would put library(lazyeval) at the top.

Further, you set variables before you use them. For example, factors <- rownames(attr(tf, "factors")).

These observations lead to the following script.

# to use 'as.lazy' and 'lazy_eval'
library(lazyeval)


dat <- data.frame(
  A = c("a", "b", "c"),
  B = c("x", "y", "z"),
  NotUsed = c(1, 2, 3))


frml <- ~ A + B + A:B
tf <- terms.formula(frml)


tvars <- attr(tf, "variables")
used <- lapply(eval(tvars, envir = dat), as.factor)
names(used) <- rownames(attr(tf, "factors"))


tlabs <- attr(tf, "term.labels")

lapply(tlabs, function(tlab){
  droplevels(lazy_eval(as.lazy(tlab), data = used))
})

Please pay attention to how a grouped the code lines.

A Better Way

Regarding a better way, for which you have asked, I would propose the following.

dat <- data.frame(A = c("a", "b", "c"),
                  B = c("x", "y", "z"),
                  NotUsed = c(1, 2, 3))

dat <- subset(x = dat, select = -NotUsed)

dat$c <- as.factor(paste(dat$A, dat$B, sep = ":"))

my.list <- lapply(dat,
                  FUN = function(column)
                  {
                      return(column)
                  })

In my view, this is a better way because it expresses your intention better. If you would have given me your code without any comments I would have a hard time explaining what it does or what it's purpose is. In addition, it does not require an additional package.

HTH!