我有一个宽格式的纵向数据，我正试图将其转换为长格式：
#I have a wide data which look like this:
dat_wide <- read.table(text="
cid dyad f1 f2 op2 ed1 junk
1 2 0 0 4 5 0.876
1 5 0 1 4 4 0.765
", header=TRUE)
#I want to convert it to long like this:
dat_long <- read.table(text="
cid dyad f op ed junk Visit
1 2 0 NA 5 0.876 1
1 2 0 4 NA 0.876 2
1 5 0 NA 4 0.765 1
1 5 1 4 NA 0.765 2
", header=TRUE)
#R code I was trying:
dat_l2 = reshape(dat_wide,idvar='cid', varying=list(c('f1','f2'), 'op2','ed1'),
#timevar='Visit',
times=c(1,2),
v.names=c('f','op','ed'),
direction='long')
#gives error:Error in reshape(merge_wide1, idvar = "cid", varying = c("f1", : length of 'v.names' does not evenly divide length of 'varying'
它类似于将数据从宽转换为长(使用多列(
我的数据不同之处在于：我有一些变量只记录了较少的时间点。例如，变量"f"从时间1和时间2都被记录；时间2，但变量"op"仅被记录用于时间2(即op2(&变量"ed"只记录了时间1(即ed1(头(数据(
您可以从tidyr:使用pivot_longer
tidyr::pivot_longer(dat_wide,
cols = f1:ed1,
names_to = c('.value', 'Visit'),
names_pattern = '(.*)(\d+)')
# cid dyad junk Visit f op ed
# <int> <int> <dbl> <chr> <int> <int> <int>
#1 1 2 0.876 1 0 NA 5
#2 1 2 0.876 2 0 4 NA
#3 1 5 0.765 1 0 NA 4
#4 1 5 0.765 2 1 4 NA