I have a dataframe in a wide format, like below. i want to reshape the wide to long using data.table melt function.in simple case, i can split two data, and rbind two datasets. but in my case, there are multiple test(i) testgr(i) columns. But there must be a better and a more efficient way to do this. thx in advance.
from =>
id<-c("106E1258","106E2037","104E1182","105E1248","105E1470","10241247",
"10241703")
yr<-c(2017,2017,2015,2016,2016,2013,2013)
finalgr<-c(72,76,75,71,75,77,78)
test01<-c("R0560","R0066","R0308","R0129","R0354","R0483",
"R0503")
test01gr<-c(73,74,67,80,64,80,70)
test02<-c("R0660","R0266","R0302","R0139","R0324","R0383" ,
"R0503")
test02gr<-c(71,54,67,70,68,81,61)
dt<-data.frame(id=id,yr=yr,
finalgr=finalgr,
test01=test01,test01gr=test01gr,
test02=test02,test02gr=test02gr)
to=>
id2<-c("106E1258","106E1258","104E1182","104E1182")
yr2<-c(2017,2017,2015,2015)
finalgr<-c(72,72,75,75)
testid<-c("R0560","R0660","R0308","R0302")
testgr<-c(73,71,67,67)
dt2<-data.frame(id=id2,yr=yr2,finalgr=finalgr,testid=testid,testgr=testgr)
You indeed should use melt
:
setDT(dt)
melt(dt, id.vars = c('id', 'yr', 'finalgr'),
measure.vars = list(testid = c('test01', 'test02'),
testgr = c('test01gr', 'test02gr')))
# id yr finalgr variable testid testgr
# 1: 106E1258 2017 72 1 R0560 73
# 2: 106E2037 2017 76 1 R0066 74
# 3: 104E1182 2015 75 1 R0308 67
# 4: 105E1248 2016 71 1 R0129 80
# 5: 105E1470 2016 75 1 R0354 64
# 6: 10241247 2013 77 1 R0483 80
# 7: 10241703 2013 78 1 R0503 70
# 8: 106E1258 2017 72 2 R0660 71
# 9: 106E2037 2017 76 2 R0266 54
# 10: 104E1182 2015 75 2 R0302 67
# 11: 105E1248 2016 71 2 R0139 70
# 12: 105E1470 2016 75 2 R0324 68
# 13: 10241247 2013 77 2 R0383 81
# 14: 10241703 2013 78 2 R0503 61
If there are many more test
columns, you can use patterns
:
melt(dt, id.vars = c('id', 'yr', 'finalgr'),
measure.vars = patterns(testid = 'test[0-9]+$', testgr = 'test[0-9]+gr'))
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