I have the following dataset (containing around 25 more variables other than Weight = W and Height = H), all spanning 10 years.
Currently it has the following form and no time index.
df <- structure(list(data = structure(1:4, .Label = c("Ind_1", "Ind_2",
"Ind_3", "Ind_4"), class = "factor"), r1weight = c(56, 76, 87, 64
), r2weight = c(57, 75, 88, 66), r3weight = c(56, 76, 87, 65), r4weight = c(56L,
73L, 85L, 63L), r5weight = c(55L, 77L, 84L, 65L), r1height = c(151L, 163L,
173L, 153L), r2height = c(154L, 164L, NA, 154L), r3height = c(NA, 165L, NA,
152L), r4height = c(153L, 162L, 172L, 154L), r5height = c(152,161,171,154)), class =
"data.frame", row.names = c(NA,
-4L))
data r1w r2w r3w r4w r5w r1h r2h r3h r4h r5h
1 Ind_1 56 57 56 56 55 151 154 NA 153 152
2 Ind_2 76 75 76 73 77 163 164 165 162 161
3 Ind_3 87 88 87 85 84 173 NA NA 172 171
4 Ind_4 64 66 65 63 65 153 154 152 154 154`
I need to add time variable and reshape to long format, hopefully getting something like this.
dflong <- structure(list(time = structure(1:20, .Label = c("1", "2",
"3", "4", "5", "1","2","3","4","5", "1","2","3","4","5","1","2","3","4","5"),
class = "factor"), Ind = c(1,1,1,1,1,2,2,2,2,2,3,3,3,3,3,4,4,4,4,4), W = c(56,57,56,56,55,76,75,76,73,77,87,88,87,85,84,64,66,65,63,65),
H = c(151,154,NA,153,152,163,164,165,162,161,173,NA,NA,172,171,153,154,152,154,154)), class = "data.frame", row.names = c(NA, -20L))
which looks
time Ind W H
1 1 1 56 151
2 2 1 57 154
3 3 1 56 NA
4 4 1 56 153
5 5 1 55 152
6 1 2 76 163
7 2 2 75 164
8 3 2 76 165
9 4 2 73 162
10 5 2 77 161
11 1 3 87 173
12 2 3 88 NA
13 3 3 87 NA
14 4 3 85 172
15 5 3 84 171
16 1 4 64 153
17 2 4 66 154
18 3 4 65 152
19 4 4 63 154
20 5 4 65 154`
I tried to use the reshape2-command and so far I've got:
library(reshape2)
dflong <- melt(df,id.vars = c("idhhpn",r1w-r10w, r1h-r10h (help writing compactly),
time(needs help constructing) )`
I dont want to write "r1w, r2w, r3w", but more like r1weight-r10weight so I dont have to write all 10 time instances for all 25 variable.
So far I've got to this point
by using the follwing code
melt <- melt(setDT(HRSdata), measure = patterns("idhhpn", "srhlt", "highbp", "diabetes", "cancer", "lungev", "heartp", "strokev", "psychev", "arth", "obese", "agey", "marpart", "male", "black", "hispan", "logass", "logdebt", "atotal", "debt", "lths", "hsorged", "somehs", "scorAA", "bachelor", "graduate", "works62", "works65", "momagey", "dadagey", "dadalive", "momalive", "vigact3", "smokesn"),
value.name = c("idhhpn", "srhlt", "highbp", "diabetes", "cancer", "lungev", "heartp", "strokev", "psychev", "arth", "obese", "agey", "marpart", "male", "black", "hispan", "logass", "logdebt", "atotal", "debt", "lths", "hsorged", "somehs", "scorAA", "bachelor", "graduate", "works62", "works65", "momagey", "dadagey", "dadalive", "momalive", "vigact3", "smokesn"),
variable.name = "time")[,
idhhpn := as.integer(sub("\\D+", "", HRSdata))][order(idhhpn)][, .(time, idhhpn, srhlt, highbp, diabetes, cancer, lungev, heartp, strokev, psychev, arth, obese, agey, marpart, male, black, hispan, logass, logdebt, atotal, debt, lths, hsorged, somehs, scorAA, bachelor, graduate, works62, works65, momagey, dadagey, dadalive, momalive, vigact3, smokesn )]
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