In R, when you coerce a vector from binary to numeric, the names are stripped away.
There are a few possible solutions, which I've outlined before. It seems dangerous to rely on implicit conversion by adding 0 to all the values, and the sapply() adds an additional loop to my operations (which seems inefficient). Is there any other way to preserve the names when converting a vector using as.numeric?
# Set the seed
set.seed(1045)
# Create a small sample vector and give it names
example_vec <- sample(x = c(TRUE,FALSE),size = 10,replace = TRUE)
names(example_vec) <- sample(x = LETTERS,size = 10,replace = FALSE)
example_vec
# Y N M P L J H O F D
# FALSE TRUE FALSE FALSE TRUE TRUE TRUE TRUE TRUE TRUE
as.numeric(x = example_vec)
# [1] 0 1 0 0 1 1 1 1 1 1
example_vec + 0
# Y N M P L J H O F D
# 0 1 0 0 1 1 1 1 1 1
sapply(X = example_vec,FUN = as.numeric)
# Y N M P L J H O F D
# 0 1 0 0 1 1 1 1 1 1
Just to throw another option out there, since your input is a logical vector, you can use ifelse(). And one could argue this approach is more explicit and straightforward:
ifelse(example_vec,1L,0L);
## Y N M P L J H O F D
## 0 1 0 0 1 1 1 1 1 1
Benchmarking
library(microbenchmark);
ifelse. <- function(x) ifelse(x,1L,0L);
sapply. <- function(x) sapply(x,as.integer);
setstoragemode <- function(x) { storage.mode(x) <- 'integer'; x; };
setmode <- function(x) { mode(x) <- 'integer'; x; };
setclass <- function(x) { class(x) <- 'integer'; x; };
as.and.setnames <- function(x) setNames(as.integer(x),names(x));
plus <- function(x) +x;
addzero <- function(x) x+0L;
## small scale (OP's example input)
set.seed(1045L);
x <- sample(c(T,F),10L,T);
names(x) <- sample(LETTERS,10L);
ex <- ifelse.(x);
identical(ex,sapply.(x));
## [1] TRUE
identical(ex,setstoragemode(x));
## [1] TRUE
identical(ex,setmode(x));
## [1] TRUE
identical(ex,setclass(x));
## [1] TRUE
identical(ex,as.and.setnames(x));
## [1] TRUE
identical(ex,plus(x));
## [1] TRUE
identical(ex,addzero(x));
## [1] TRUE
microbenchmark(ifelse.(x),sapply.(x),setstoragemode(x),setmode(x),setclass(x),as.and.setnames(x),plus(x),addzero(x));
## Unit: nanoseconds
## expr min lq mean median uq max neval
## ifelse.(x) 6843 8126.0 9627.13 8981 9837.0 21810 100
## sapply.(x) 18817 20100.5 23234.93 21383 22666.5 71418 100
## setstoragemode(x) 856 1283.0 1745.54 1284 1711.0 15396 100
## setmode(x) 7270 8126.0 9862.36 8982 10264.0 32074 100
## setclass(x) 429 1283.0 2138.97 1284 1712.0 32075 100
## as.and.setnames(x) 1283 1711.0 1997.78 1712 2139.0 7271 100
## plus(x) 0 428.0 492.39 428 428.5 9837 100
## addzero(x) 0 428.0 539.39 428 856.0 2566 100
## large scale
set.seed(1L);
N <- 1e5L;
x <- sample(c(T,F),N,T);
names(x) <- make.unique(rep_len(LETTERS,N));
ex <- ifelse.(x);
identical(ex,sapply.(x));
## [1] TRUE
identical(ex,setstoragemode(x));
## [1] TRUE
identical(ex,setmode(x));
## [1] TRUE
identical(ex,setclass(x));
## [1] TRUE
identical(ex,as.and.setnames(x));
## [1] TRUE
identical(ex,plus(x));
## [1] TRUE
identical(ex,addzero(x));
## [1] TRUE
microbenchmark(ifelse.(x),sapply.(x),setstoragemode(x),setmode(x),setclass(x),as.and.setnames(x),plus(x),addzero(x));
## Unit: microseconds
## expr min lq mean median uq max neval
## ifelse.(x) 7633.598 7757.1900 16615.71251 7897.4600 29401.112 96503.642 100
## sapply.(x) 86353.737 102576.0945 125547.32957 123909.1120 137900.406 264442.788 100
## setstoragemode(x) 84.676 92.8015 343.46124 98.3605 113.543 23939.133 100
## setmode(x) 124.020 155.0245 603.15744 167.2125 181.111 22395.736 100
## setclass(x) 85.104 92.3740 328.25393 100.2850 118.460 21807.713 100
## as.and.setnames(x) 70.991 78.2610 656.98177 82.3235 88.953 35710.697 100
## plus(x) 40.200 42.9795 48.68026 44.9040 49.608 88.953 100
## addzero(x) 181.326 186.4580 196.34882 189.6650 201.211 282.679 100
## very large scale
set.seed(1L);
N <- 1e7L;
x <- sample(c(T,F),N,T);
names(x) <- make.unique(rep_len(LETTERS,N));
ex <- ifelse.(x);
identical(ex,sapply.(x));
## [1] TRUE
identical(ex,setstoragemode(x));
## [1] TRUE
identical(ex,setmode(x));
## [1] TRUE
identical(ex,setclass(x));
## [1] TRUE
identical(ex,as.and.setnames(x));
## [1] TRUE
identical(ex,plus(x));
## [1] TRUE
identical(ex,addzero(x));
## [1] TRUE
microbenchmark(ifelse.(x),sapply.(x),setstoragemode(x),setmode(x),setclass(x),as.and.setnames(x),plus(x),addzero(x),times=5L);
## Unit: milliseconds
## expr min lq mean median uq max neval
## ifelse.(x) 1082.220903 1308.106967 3452.639836 1473.723533 6306.320235 7092.82754 5
## sapply.(x) 16766.199371 17431.458634 18401.672635 18398.345499 18843.890150 20568.46952 5
## setstoragemode(x) 13.298283 13.648103 173.574496 19.661753 24.736278 796.52806 5
## setmode(x) 19.043796 19.878573 75.669779 19.969235 39.683589 279.77370 5
## setclass(x) 14.025292 14.119804 259.627934 14.414457 26.838618 1228.74150 5
## as.and.setnames(x) 12.889875 24.241484 178.243948 24.962934 25.103631 804.02182 5
## plus(x) 7.577576 7.676364 9.047674 8.245142 8.253266 13.48602 5
## addzero(x) 18.861615 18.960403 71.284716 26.622226 26.950662 265.02867 5
Looks like the unary plus takes the cake. (And my ifelse() idea kinda sucks.)
One possibility is to use the mode<- replacement function to change the internal storage mode (type) of the object. Also, integers are more appropriate than doubles (i.e. numerics) for this case of logical coercion.
mode(example_vec) <- "integer"
example_vec
# Y N M P L J H O F D
# 0 1 0 0 1 1 1 1 1 1
From help(mode) -
mode(x) <- "newmode"changes the mode of objectxtonewmode. This is only supported if there is an appropriateas.newmodefunction, for example"logical","integer","double","complex","raw","character","list","expression","name","symbol"and"function". Attributes are preserved.
The documentation also notes that storage.mode<- is a more efficient primitive version of mode<-. So the following could also be used.
storage.mode(example_vec) <- "integer"
But as @joran pointed out in the comments, it looks like class<- also does the same thing.
来源：https://stackoverflow.com/questions/37951199/preserve-names-when-coercing-vector-from-binary-to-as-numeric