R 使用data.table将多行宽数据重塑为长数据

我有如下数据

#    am     qsec        vs am     gear     carb
# 1:  1 17.36000 0.5384615  1 4.384615 2.923077
# 2:  1 17.02000 1.0000000  1 4.000000 2.000000
# 3:  0 18.18316 0.3684211  0 3.210526 2.736842
# 4:  0 17.82000 0.0000000  0 3.000000 3.000000

我想生产

 #    variable          0          1
 # 1:     qsec 18.1831579 17.3600000
 # 2:     qsec 17.8200000 17.0200000
 # 3:       vs  0.3684211  0.5384615
 # 4:       vs  0.0000000  1.0000000
 # 5:       am  0.0000000  1.0000000
 # <snip>

---

我问了一个问题，但使用Akrun在评论中给出的解决方案，返回

dcast( melt(tdat, id.var=1), variable~am, value.var='value')
#Aggregate function missing, defaulting to 'length'
#   variable 0 1
#1:     qsec 2 2
#2:       vs 2 2
#3:       am 2 2
#4:     gear 2 2
#5:     carb 2 2

---

可以使用

数据解决此问题。表
的
rowid（）
函数：

library(data.table)
m <- melt(tdat, id.vars="am")
dcast(m, variable + rowid(am) ~ am)[, am := NULL][]

资料
可以使用
数据解决此问题。表
的
rowid（）
函数：

library(data.table)
m <- melt(tdat, id.vars="am")
dcast(m, variable + rowid(am) ~ am)[, am := NULL][]

资料
    variable          0          1
 1:     qsec 18.1831600 17.3600000
 2:     qsec 17.8200000 17.0200000
 3:       vs  0.3684211  0.5384615
 4:       vs  0.0000000  1.0000000
 5:       am  0.0000000  1.0000000
 6:       am  0.0000000  1.0000000
 7:     gear  3.2105260  4.3846150
 8:     gear  3.0000000  4.0000000
 9:     carb  2.7368420  2.9230770
10:     carb  3.0000000  2.0000000

library(data.table)
tdat <- fread(
"# i    am     qsec        vs am     gear     carb
# 1:  1 17.36000 0.5384615  1 4.384615 2.923077
# 2:  1 17.02000 1.0000000  1 4.000000 2.000000
# 3:  0 18.18316 0.3684211  0 3.210526 2.736842
# 4:  0 17.82000 0.0000000  0 3.000000 3.000000", 
  drop = 1:2, colClasses = list(integer = c(3, 6))
)

setDT(mtcars[7:11])[, lapply(.SD, function(y) c(mean(y), median(y))), by = am]

   am     qsec        vs     gear     carb
1:  1 17.36000 0.5384615 4.384615 2.923077
2:  1 17.02000 1.0000000 4.000000 2.000000
3:  0 18.18316 0.3684211 3.210526 2.736842
4:  0 17.82000 0.0000000 3.000000 3.000000