How to use gather and spread to solve problem? (Tidyr)

Question

given table 1, convert to table 2.

I can solve the first part by creating table 1.

library(tidyverse) 
grp = c("A", "A", "B", "B")
sex = c("F", "M", "F", "M")
meanL = c(0.22, 0.47, 0.33, 0.55)
sdL = c(.11, .33, .11, .31)
meanR = c(.34, .57, .4, .65)
sdR = c(.08, .33, .07, .27)
data <- as.data.frame(cbind(grp, sex, meanL, sdL, meanR, sdR))
head(data)

The best that I can do is gather all of the data into two columns, one containing the variable and the other containing the values.

data2 <- gather(data, categories, meanL:sdR)
head(data2, n=30)

The current place where I am struggling is in labeling the gender for each reading.

Answer 1

Here is a tidyverse option:

data %>%
        gather(k, v, -grp, -sex) %>%
        unite(k, sex, k, sep = ".") %>%
        spread(k, v)
#  grp F.meanL F.meanR F.sdL F.sdR M.meanL M.meanR M.sdL M.sdR
#1   A    0.22    0.34  0.11  0.08    0.47    0.57  0.33  0.33
#2   B    0.33     0.4  0.11  0.07    0.55    0.65  0.31  0.27

I suggest running the code above line-by-line, to see what each step does. In a nutshell, we reshape data from wide to long, combine columns, and reshape again from long to wide.