I want so select a subset of consecutive columns by column name, and rename with a character vector.
example data:
data<-data.frame(foo=1:4, bar=10:13, zoo_1=letters[1:4], zoo_2=letters[5:8])
foo bar zoo_1 zoo_2
1 1 10 a e
2 2 11 b f
3 3 12 c g
4 4 13 d h
colnames to be replaced: 'bar', 'zoo_1', 'zoo_2'
new names:
new_names<-c('a', 'b', 'c')
I wanted to use some sort of : operator to select, for instance, the columns with the names bar to zoo_2
I found some weird solutions:
#1
names(data)[which(names(df)=='bar'):which(names(df)=='zoo_2')]<-new_names
and
#2
my_rename<-function(x,y,z){
names(x)[match(y, names(df))]<-z
names(x)
}
names(data)<-my_rename(data, c('bar', 'zoo_1', 'zoo_2'), c(new_names)
Solution #2 is bad because it requires spelling out all names to be replaced.
Solution #1 allows me to select the names in a 'bar':'zoo_2' style, but is quite verbose and may be confusing to others. I am most interested In a substitute for this (which:which) hack.
Any ideas?
We can use rename_at
library(dplyr)
data <- data %>%
rename_at(vars(bar:zoo_2), ~ new_names)
names(data)
#[1] "foo" "a" "b" "c"
However, in dplyr 1.05, rename_at has been superseded by rename_with:
data2<-data %>%
rename_with(.cols=bar:zoo_2, ~ new_names)
> identical(data, data2)
[1] TRUE