Renaming Columns with R

Often data you’re working with has abstract column names, such as (x1, x2, x3…). Typically, the first step I take when renaming columns with r is opening my web browser. 

The dataset cars is data from the 1920s on “Speed and Stopping Distances of Cars”. There is only 2 columns shown below.

colnames(datasets::cars)
[1] "speed" "dist" 

If we wanted to rename the column “dist” to make it easier to know what the data is/means we can do so in a few different ways.

Using Base r:

colnames(cars)[2] <-"Stopping Distance (ft)"

[1] "speed"                  "Stopping Distance (ft)"

colnames(cars)[1:2] <-c("Speed (mph)","Stopping Distance (ft)")

[1] "Speed (mph)"            "Stopping Distance (ft)"

Stopping_Over_60 <- subset(cars, dist > 60)
Stopping_Under_61 <- subset(cars, dist <= 60)
names(Stopping_Over_60)[2] <- names(Stopping_Under_61)[2] <- "Stopping Distance (ft)"

names(Stopping_Over_60)
 [1] "speed"                  "Stopping Distance (ft)"

names(Stopping_Under_61)
 [1] "speed"                  "Stopping Distance (ft)"

Using dplyr:

cars %>% 
  rename("Stopping Distance (ft)" = dist) %>% 
  colnames()

[1] "speed"             "Stopping Distance (ft)"

cars %>%
  rename("Stopping Distance (ft)" = dist, "Speed (mph)" = speed) %>%
  colnames()

[1] "Speed (mph)"            "Stopping Distance (ft)"

Using GREP:

colnames(cars)[grep("dist", colnames(cars))] <-"Stopping Distance (ft)"

"speed"                  "Stopping Distance (ft)"

Using data.table

As mentioned in the comments below, using data.tables is a more efficient way of renaming columns in r due to the handling of memory. Memory is important as the data you start working with grows in size.

library(data.table)
cars_DT <- cars 
cars_DT <-setDT(cars_DT)
# Note have to copy over to a new data structure due to cars  being locked as its a dataset built into a package

setnames(cars_DT, c("speed","dist"), c("Speed (mph)","Stopping Distance (ft)"))

names(cars_DT)
[1] "Speed (mph)" "Stopping Distance (ft)"