Question
I got a funny task to do during coding my thesis. I have a 2D-matrix(or data.frame) like this:
CACE cheng cheng2 ding ding_ass sun2
mean 0 -0.000467158 0.01219119 0.004284223 0.003803375 0.004204354
sd 0 0.131911914 0.14457078 0.074447198 0.055980336 0.072260046
sun3
mean 0.004202419
sd 0.072266683
Above matrix is describing several models' performance(their mean and sd). I want to list them into my paper, so I need to reshape them like this:
CACE_mean CACE_sd cheng_mean cheng_sd cheng2_mean cheng2_sd
[1,] 0 0 -0.000467158 0.1319119 0.01219119 0.1445708
ding_mean ding_sd ding_ass_mean ding_ass_sd sun2_mean
[1,] 0.004284223 0.0744472 0.003803375 0.05598034 0.004204354
sun2_sd sun3_mean sun3_sd
[1,] 0.07226005 0.004202419 0.07226668
It is like flatten a matrix or data.frame, but not a traditional long to wide reshaping task. I am wondering whether we can do it using high-level functions.
Data
Original data(dput):
structure(c(0, 0, -0.000467157971792085, 0.131911914238178, 0.0121911908647192,
0.144570781843054, 0.00428422254646622, 0.0744471979273107, 0.00380337457776962,
0.0559803359990803, 0.00420435426517323, 0.0722600458117494,
0.00420241918783969, 0.0722666828398023), .Dim = c(2L, 7L), .Dimnames = list(
c("mean", "sd"), c("CACE", "cheng", "cheng2", "ding", "ding_ass",
"sun2", "sun3")))
My try
new_names = c(outer(row.names(a),colnames(a),function(x,y){paste(y,x,sep = '_')}))
new_data = t(data.frame(c(a),row.names = new_names))
rownames(new_data) <- NULL
It workes really well, but I wanna know some other ideas.