When reading the following helpfile it should be possible to add a prefix to the column names :
colnames(x, do.NULL = TRUE, prefix = \"col\")
The stats::setNames
function works just fine for this, and is in fact much quicker than the alternatives.
iris.dt <- data.table::as.data.table(iris)
microbenchmark::microbenchmark(
base = colnames(iris) <- paste("Sub", colnames(iris), sep = "_"),
stats = setNames(iris, paste("Sub", colnames(iris), sep = "_")),
dplyr = dplyr::rename_with(iris, ~ paste("Sub", .x, sep = "_")),
datatable = data.table::setnames(iris.dt, paste("Sub", names(iris.dt), sep = "_"))
)
#> Unit: microseconds
#> expr min lq mean median uq max neval cld
#> base 11.094 16.2140 21.62408 19.2010 23.681 65.707 100 a
#> stats 8.107 13.8670 17.40435 16.6405 19.841 39.254 100 a
#> dplyr 786.772 842.8785 5236.67222 877.0130 984.959 402378.407 100 a
#> datatable 40.961 49.9200 84.06237 62.2935 73.600 834.560 100 a
Created on 2020-10-21 by the reprex package (v0.3.0)
You have misread the help file. Here's the argument to look at:
do.NULL
: logical. If FALSE
and names are NULL
, names are created.
Notice the and in that description. Your names are no longer NULL
, so using prefix won't work.
Instead, use something like this:
> m2 <- cbind(1,1:4)
> colnames(m2) <- c("x","Y")
> colnames(m2) <- paste("Sub", colnames(m2), sep = "_")
> m2
Sub_x Sub_Y
[1,] 1 1
[2,] 1 2
[3,] 1 3
[4,] 1 4
The updated tidyverse
method (with dplyr 1.0.2
) uses rename_with()
as the rename_all()
function has been superseded.
iris %>% rename_with( ~ paste("Sub", .x, sep = "_"))
I will add a tidyverse
approach to this problem, for which you can both add suffix and prefix to all column names. The following adds a prefix in a dplyr
pipe.
df <- data.frame(x = c(1, 2), y = c(3, 4))
df %>% dplyr::rename_all(function(x) paste0("a", x))
Adding suffix is easier.
df %>% dplyr::rename_all(paste0, "a")