我有来自国际货币基金组织IFS的季度时间序列经济数据,我需要进入长期形式。
现在,行是每个国家/地区的变量,列是时间,所以它看起来像这样。
country variable Q1 Q2
[1,] "USA" "inflation" "1" "5"
[2,] "USA" "GDPPC" "2" "6"
[3,] "UK" "inflation" "3" "7"
[4,] "UK" "GDPPC" "4" "8"
我需要把它变成长形式:
country Time inflation GDPPC
[1,] "USA" "Q1" "1" "2"
[2,] "USA" "Q2" "5" "6"
[3,] "UK" "Q1" "3" "4"
[4,] "UK" "Q2" "7" "8"
当ID变量和测量变量都在行中时,我无法找到有关使用重塑的任何建议。
答案 0 :(得分:1)
部分melt
后跟dcast
包中的reshape2
:
d = data.table(country = c("USA","USA","UK","UK"), variable = c("inflation","GDPPC","inflation","GDPPC"),Q1=as.character(1:4),Q2=as.character(5:8))
require(reshape2)
d2 = melt(d, id=c("country", "variable"))
colnames(d2)[3] = "Time"
rr=dcast(d2, country +Time ~ variable)
rr = rr[order(rr$country,decreasing=T),c(1:2,4,3)]
给出:
> rr
country Time inflation GDPPC
3 USA Q1 1 2
4 USA Q2 5 6
1 UK Q1 3 4
2 UK Q2 7 8
答案 1 :(得分:0)
使用stack
和reshape
的基本R方法,使用下面的data.frame
d <- data.frame(country = c("USA","USA","UK","UK"), variable = c("inflation","GDPPC","inflation","GDPPC"),Q1=1:4,Q2=5:8)
重塑:
intm <- data.frame(d[,c("country","variable")],stack(d[,c("Q1","Q2")]))
reshape(intm, idvar=c("country","ind"), timevar="variable", direction="wide")
# country ind values.inflation values.GDPPC
#1 USA Q1 1 2
#3 UK Q1 3 4
#5 USA Q2 5 6
#7 UK Q2 7 8