CODEWITHSUNDEEP
r
Ricky
Ricky

Reputation: 4686

Selecting value based on variable name of data frame column in R

I have a data frame with a few columns containing values, and a column containing the name of the relevant column. e.g.

df <- data.frame(p1=c("A", "B", "A"),
                 p2=c("C", "C", "D"),
                 name=c("p2", "p1", "p1"), stringsAsFactors=FALSE)

What I want to do is to retrieve a value from the column specified by the name field, i.e. the output as below.

> df
  p1 p2 name value
1  A  C   p2     C
2  B  C   p1     B
3  A  D   p1     A

I currently get by with df$value <- ifelse(df$name=="p1", df$p1, ifelse(df$name=="p2", df$p2, NA)) , which is inelegant and unscalable if there are more than just p1 and p2.

Any suggestion on a better approach for this?

Upvotes: 1

Views: 1611

Answers (2)

akrun
akrun

Reputation: 886938

You could try

df$value <- df[cbind(seq_len(nrow(df)), match(df$name, names(df)))]

The above is a vectorized solution. Or if you need only a compact solution (based on the number of characters) 

diag(as.matrix(df[,df$name]))
#[1] "C" "B" "A"

Benchmarks

df1 <- df[rep(1:nrow(df),1e5),]

akrun <- function() {df1[cbind(seq_len(nrow(df1)),
                     match(df1$name, names(df1)))]}
colonel <- function() {apply(df1, 1 ,function(u) u[u['name']])}

library(microbenchmark)
microbenchmark(akrun(), colonel(), times=20L, unit='relative')
#Unit: relative
#  expr      min       lq     mean   median       uq      max neval cld
#  akrun()   1.0000   1.0000  1.00000  1.00000  1.00000  1.00000    20  a 
#colonel() 118.2858 102.3968 46.25946 77.92023 59.15559 23.56562    20   b

Upvotes: 2

Colonel Beauvel
Colonel Beauvel

Reputation: 31161

Or very simply (but using a loop):

df$value = apply(df, 1 ,function(u) u[u['name']])

#> df
#  p1 p2 name value
#1  A  C   p2     C
#2  B  C   p1     B
#3  A  D   p1     A

Upvotes: 1

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