R data.table中的一个复杂求和，它涉及到查看其他列

我有一个数据表，其中变量

v1

和

v2

的每个值都有一个关联的“类型”，编码在一个单独的列中。这里是一个MWE：

X <- data.table(id = 1:5, group = c(1,1,2,2,2), v1 = c(10,12,14,16,18), type_v1 = c("t1","t2","t1","t1","t2"), v2 = c(3,NA,NA,7,8), type_v2 = c("t2", "", "", "t3","t3"))
print(X)
   id group v1 type_v1 v2 type_v2
1:  1     1 10      t1  3      t2
2:  2     1 12      t2 NA        
3:  3     2 14      t1 NA        
4:  4     2 16      t1  7      t3
5:  5     2 18      t2  8      t3

有很多不同的“类型”，并不是所有的类型都出现在所有的群体中。我可能需要创建变量

v3

，

v4

，等等（请注意，在我的示例中，一个额外的列是如何容纳组2中的t1、t2和t3的）

我的数据当前为长格式。如果可能的话，我不想把它改成宽幅格式。我对不涉及创建列“t1”、“t2”等的解决方案感兴趣。这是因为“t1”、“t2”和“t3”实际上是很长的字符串

---

编辑：输入所需的输出

您可以

melt

将数据转换为长格式

library(data.table)
X1 <-
  melt(
    X,
    id.vars = "group",
    
    # we melt multiple value vars simultaneously,
    # those starting with "v" and those starting 
    # with "type_v" followed by 1 or more digit
    measure.vars = patterns(c("^v\\d+$", "^type_v\\d+$")),
    value.name = c("value", "type")
  )
X1
#     group variable value type
# 1:     1        1     10   t1
# 2:     1        1     12   t2
# 3:     2        1     14   t1
# 4:     2        1     16   t1
# 5:     2        1     18   t2
# 6:     1        2      3   t2
# 7:     1        2     NA     
# 8:     2        2     NA     
# 9:     2        2      7   t3
#10:     2        2      8   t3

library(data.table)
X1 <-
  melt(
    X,
    id.vars = "group",
    
    # we melt multiple value vars simultaneously,
    # those starting with "v" and those starting 
    # with "type_v" followed by 1 or more digit
    measure.vars = patterns(c("^v\\d+$", "^type_v\\d+$")),
    value.name = c("value", "type")
  )
X1
#     group variable value type
# 1:     1        1     10   t1
# 2:     1        1     12   t2
# 3:     2        1     14   t1
# 4:     2        1     16   t1
# 5:     2        1     18   t2
# 6:     1        2      3   t2
# 7:     1        2     NA     
# 8:     2        2     NA     
# 9:     2        2      7   t3
#10:     2        2      8   t3

tmp <- X1[type!="", .("v" = sum(value)), by=.(group, type)]
tmp
#   group type  v
#1:     1   t1 10
#2:     1   t2 15
#3:     2   t1 30
#4:     2   t2 18
#5:     2   t3 15

out <- dcast(tmp, group ~ rowid(group), value.var = c("v", "type")) 
out
#   group v_1 v_2 v_3 type_1 type_2 type_3
#1:     1  10  15  NA     t1     t2   <NA>
#2:     2  30  18  15     t1     t2     t3

tmp2 <- setdiff(names(out), "group")

# create a vector based on the order of the numeric part of 'tmp2'
idx <- order(as.numeric(gsub("\\D", "", tmp2)))
setcolorder(out, c("group", tmp2[idx]))
out
#   group v_1 type_1 v_2 type_2 v_3 type_3
#1:     1  10     t1  15     t2  NA   <NA>
#2:     2  30     t1  18     t2  15     t3