r - Reshaping an array to data.frame

Question

I have the following data structure (an "atomic vector?") output from daply in plyr, in which I had the function return three different measures for each subject, condition, and item.

x = structure(c(-0.93, 0.39, 0.88, 0.63, 0.86, -0.69, 1.02, 0.29, 0.94, 
0.93, -0.01, 0.79, 0.32, 0.14, 0.13, -0.07, -0.63, 0.26, 0.07, 0.87,
-0.36, 1.043, 0.33, -0.12, -0.055, 0.07, 0.67, 0.48, 0.002, 0.008, 
-0.19, -1.39, 0.98, 0.43, -0.02, -0.15,-0.08, 0.74, 0.96, 0.44, -0.005,
1.09, 0.36, 0.04, 0.09, 0.17, 0.68, 0.51, 0.09, 0.12, -0.05, 0.11,
0.99, 0.62, 0.13, 0.06, 0.27, 0.74, 0.96, 0.45), .Dim = c(5L, 
2L, 2L, 3L), .Dimnames = structure(list(Subject = c("s1", "s2", 
"s3", "s4", "s5"), Cond = c("A", "B"), Item = c("1", "2"), c("Measure1", 
"Measure2", "Measure3")), .Names = c("Subject", "Cond", 
"Item", "")))

I want to change it to look like:

Subject Cond Item Measure1 Measure2 Measure3
     s1    A    1    -0.93   -0.360   -0.005
     s1    A    2    -0.01    -0.19    -0.05 
     s1    B    1    -0.69    0.070     0.17
     s1    B    2    -0.07    -0.15     0.06
     s2    A    1     0.39    1.043    1.090
     s2    A    2     0.79    -1.39     0.11
     s2    B    1     1.02    0.670     0.68
     s2    B    2    -0.63    -0.08     0.27

etc.

Is there an easy way to do this?

Answer 1

Use as.data.frame.table().

d0 <- as.data.frame.table(x)
head(d0)

#   Subject Cond Item     Var4  Freq
# 1      s1    A    1 Measure1 -0.93
# 2      s2    A    1 Measure1  0.39
# 3      s3    A    1 Measure1  0.88
# 4      s4    A    1 Measure1  0.63
# 5      s5    A    1 Measure1  0.86
# 6      s1    B    1 Measure1 -0.69

library(tidyr)
d1 <- pivot_wider(data = d0, names_from = "Var4", values_from = "Freq")
head(d1)

#   Subject Cond Item Measure1 Measure2 Measure3
# 1      s1    A    1    -0.93   -0.360   -0.005
# 2      s1    A    2    -0.01   -0.190   -0.050
# 3      s1    B    1    -0.69    0.070    0.170
# 4      s1    B    2    -0.07   -0.150    0.060
# 5      s2    A    1     0.39    1.043    1.090
# 6      s2    A    2     0.79   -1.390    0.110