Adding prefix or suffix to most data.frame variable names in piped R workflow

Question

I want to add a suffix or prefix to most variable names in a data.frame, typically after they've all been transformed in some way and before performing a join. I don't have a way to do this without breaking up my piping.

For example, with this data:

library(dplyr)

set.seed(1)

dat14 <- data.frame(ID = 1:10, speed = runif(10), power = rpois(10, 1),

                    force = rexp(10), class = rep(c("a", "b"),5))

I want to get to this result (note variable names):

  class speed_mean_2014 power_mean_2014 force_mean_2014

1     a       0.5572500             0.8       0.5519802

2     b       0.2850798             0.6       1.0888116

My current approach is:

means14 <- dat14 %>%

  group_by(class) %>%

  select(-ID) %>%

  summarise_each(funs(mean(.)))  



names(means14)[2:length(names(means14))] <- paste0(names(means14)[2:length(names(means14))], "_mean_2014")

Is there an alternative to that clunky last line that breaks up my pipes? I've looked at

select()

and

rename()

but don't want to explicitly specify each variable name, as I usually want to rename all except a single variable and might have a much wider data.frame than in this example.

I'm imagining a final piped command that approximates this made-up function:

appendname(cols = 2:n, str = "_mean_2014", placement = "suffix")

Which doesn't exist as far as I know.

Recommended for you: Get network issues from WhatsUp Gold. Not end users.

Answer 1

After additional experimenting since posting this question, I've found that the setNames function will work with the piping as it returns a data.frame:

dat14 %>%
  group_by(class) %>%
  select(-ID) %>%
  summarise_each(funs(mean(.))) %>%
  setNames(c(names(.)[1], paste0(names(.)[-1],"_mean_2014"))) 

  class speed_mean_2014 power_mean_2014 force_mean_2014
1     a       0.5572500             0.8       0.5519802
2     b       0.2850798             0.6       1.0888116

Adding prefix or suffix to most data.frame variable names in piped R workflow

Sign up