r - 如何转换 data.table 的多个列和值？

Question

我的数据结构如下:

DT <- data.table(Id = c(1, 1, 1, 1, 10, 100, 100, 101, 101, 101), 
                 Date = as.Date(c("1997-01-01", "1997-01-02", "1997-01-03", "1997-01-04", 
                                  "1997-01-02", "1997-01-02", "1997-01-04", "1997-01-03", 
                                  "1997-01-04", "1997-01-04")),
                 group = c(1,1,1,1,1,2,2,2,2,2),
                 Price.1 = c(29, 25, 14, 26, 30, 16, 13, 62, 12,  6), 
                 Price.2 = c(4, 5, 6, 6, 8, 2, 3, 5, 7, 8))

>DT
     Id       Date group Price.1 Price.2
 1:   1 1997-01-01     1      29       4
 2:   1 1997-01-02     1      25       5
 3:   1 1997-01-03     1      14       6
 4:   1 1997-01-04     1      26       6
 5:  10 1997-01-02     1      30       8
 6: 100 1997-01-02     2      16       2
 7: 100 1997-01-04     2      13       3
 8: 101 1997-01-03     2      62       5
 9: 101 1997-01-04     2      12       7
10: 101 1997-01-04     2       6       8

我正在尝试转换它(使用 dcast.data.table):

dcast.data.table(DT, Id ~ Date, fun = sum, value.var = "Price.1") 
dcast.data.table(DT, Id ~ group, fun = sum, value.var = "Price.1")
dcast.data.table(DT, Id ~ Date, fun = sum, value.var = "Price.2")
dcast.data.table(DT, Id ~ group, fun = sum, value.var = "Price.2")

但不是 4 个单独的输出，我试图获得以下内容:

    Id 1997-01-01 1997-01-02 1997-01-03 1997-01-04  1  2   Price
1:   1         29         25         14         26 94  0 Price.1
2:  10          0         30          0          0 30  0 Price.1
3: 100          0         16          0         13  0 29 Price.1
4: 101          0          0         62         18  0 80 Price.1
5:   1          4          5          6          6 21  0 Price.2
6:  10          0          8          0          0  8  0 Price.2
7: 100          0          2          0          3  0  5 Price.2
8: 101          0          0          5         15  0 20 Price.2

我的解决方法是使用 rbind、cbind 和 merge。

cbind(rbind(merge(dcast.data.table(DT, Id ~ Date, fun = sum, value.var = "Price.1"), 
            dcast.data.table(DT, Id ~ group, fun = sum, value.var = "Price.1"), by = "Id", all.x  = T),
      merge(dcast.data.table(DT, Id ~ Date, fun = sum, value.var = "Price.2"),
            dcast.data.table(DT, Id ~ group, fun = sum, value.var = "Price.2"), by = "Id", all.x  = T)),
      Price = c("Price.1","Price.1","Price.1","Price.1","Price.2","Price.2","Price.2","Price.2"))

有没有一种现有的和更清洁的方法来做到这一点？

Answer 1

我假设每个 Id映射到唯一的 group并摆脱该变量，但除此之外，这与@ user227710 的答案基本相同。

Idg <- unique(DT[,.(Id,group)])
DT[,group:=NULL]

res <- dcast(
  melt(DT, id.vars = c("Id","Date")),
  variable+Id ~ Date,
  value.var = "value",
  fill = 0,
  margins = "Date",
  fun.aggregate = sum
)

# and if you want the group back...
setDT(res) # needed before data.table 1.9.5, where using dcast.data.table is another option
setkey(res,Id)
res[Idg][order(variable,Id)]

这使

   variable  Id 1997-01-01 1997-01-02 1997-01-03 1997-01-04 (all) group
1:  Price.1   1         29         25         14         26    94     1
2:  Price.2   1          4          5          6          6    21     1
3:  Price.1  10          0         30          0          0    30     1
4:  Price.2  10          0          8          0          0     8     1
5:  Price.1 100          0         16          0         13    29     2
6:  Price.2 100          0          2          0          3     5     2
7:  Price.1 101          0          0         62         18    80     2
8:  Price.2 101          0          0          5         15    20     2