I've got a long list of numbers in character format (around 50000 terms) which can be converted to numeric very quickly with "as.numeric":
y = c("-1", "1", "1", ...)
The problem is that I've extended the functionality to include fractions and calling
y = c("-1/2", "1", "1", ...)
y = as.numeric(y);
produces an "NAs introduced by coercion" warning message, while calling
sapply(y , function(x) {
eval(parse(text=x));
});
solves the problem, but takes much longer to execute. Is there a better way to do this?
eval(parse(text)) is very slow - as you know what you will be doing, you can write a quicker function:
y = c("-1/2", "1", "1", "1/2")
fixnums <- function(x){
temp <- as.numeric(x)
temp[is.na(temp)] <- lapply(strsplit(x[is.na(temp)], "/"), function(x) as.numeric(x[1])/as.numeric(x[2]))
unlist(temp)
}
fixnums(y)
A faster version, avoiding the lapply, suggested in the comment below by @DavidArenburg:
davidfixnums <- function(x){
temp <- as.numeric(x)
temp2 <- as.numeric(unlist(strsplit(y[is.na(temp)], "/", fixed = TRUE)))
temp[is.na(temp)] <- temp2[c(T, F)]/temp2[c(F, T)]
temp
}
Some benchmarks, using @akrun and @DavidArenburgs suggestions:
library(microbenchmark)
set.seed(1234)
y <- sample(c("-1/2", "1", "1", "1/2"), 10000, replace = TRUE)
akrunfixnums <- function(y){
x1 <- as.numeric(y)
x1[is.na(x1)] <- vapply(y[is.na(x1)], function(x)
eval(parse(text=x)), numeric(1))
x1
}
microbenchmark(fixnums(y), davidfixnums(y), akrunfixnums(y))
Unit: milliseconds
expr min lq mean median uq max neval cld
fixnums(y) 22.643745 23.157345 25.326465 23.435554 23.98544 154.16316 100 b
davidfixnums(y) 6.676234 6.778378 6.957626 6.824459 6.93025 10.12763 100 a
akrunfixnums(y) 845.404840 858.031737 869.886625 865.255363 875.54351 960.86497 100 c