Trying to use dplyr to group_by and apply scale()

Question

Trying to use dplyr to group_by the stud_ID variable in the following data frame, as in this SO question:

> str(df)         


        

Answer 1

This was a known problem in dplyr, a fix has been merged to the development version, which you can install via

# install.packages("devtools")
devtools::install_github("hadley/dplyr")

In the stable version, the following should work, too:

scale_this <- function(x) as.vector(scale(x))

Answer 2

The problem seems to be in the base scale() function, which expects a matrix. Try writing your own.

scale_this <- function(x){
  (x - mean(x, na.rm=TRUE)) / sd(x, na.rm=TRUE)
}

Then this works:

library("dplyr")

# reproducible sample data
set.seed(123)
n = 1000
df <- data.frame(stud_ID = sample(LETTERS, size=n, replace=TRUE),
                 behavioral_scale = runif(n, 0, 10),
                 cognitive_scale = runif(n, 1, 20),
                 affective_scale = runif(n, 0, 1) )
scaled_data <- 
  df %>%
  group_by(stud_ID) %>%
  mutate(behavioral_scale_ind = scale_this(behavioral_scale),
         cognitive_scale_ind = scale_this(cognitive_scale),
         affective_scale_ind = scale_this(affective_scale))

Or, if you're open to a data.table solution:

library("data.table")

setDT(df)

cols_to_scale <- c("behavioral_scale","cognitive_scale","affective_scale")

df[, lapply(.SD, scale_this), .SDcols = cols_to_scale, keyby = factor(stud_ID)]