В базе R мы можем сделать:
df[] <- lapply(df, as.numeric)
или
df[cols_to_convert] <- lapply(df[cols_to_convert], as.numeric)
Вот эталон решения (игнорируя соображения о факторах):
DF <- data.frame(a = 1:10000, b = letters[1:10000],
c = seq(as.Date("2004-01-01"), by = "week", len = 10000),
stringsAsFactors = TRUE)
DF <- setNames(do.call(cbind,replicate(50,DF,simplify = F)),paste0("V",1:150))
dim(DF)
# [1] 10000 150
library(dplyr)
n1tk <- function(x) data.frame(data.matrix(x))
mm <- function(x) {x[] <- lapply(x,as.numeric); x}
akrun <- function(x) mutate_all(x, as.numeric)
mo <- function(x) {for(i in 1:150){ x[, i] <- as.numeric(x[, i])}}
microbenchmark::microbenchmark(
akrun = akrun(DF),
n1tk = n1tk(DF),
mo = mo(DF),
mm = mm(DF)
)
# Unit: milliseconds
# expr min lq mean median uq max neval
# akrun 152.9837 177.48150 198.292412 190.38610 206.56800 432.2679 100
# n1tk 10.8700 14.48015 22.632782 17.43660 21.68520 89.4694 100
# mo 9.3512 11.41880 15.313889 14.71970 17.66530 37.6390 100
# mm 4.8294 5.91975 8.906348 7.80095 10.11335 71.2647 100