r - R中的列表操作向量化列表

Question

类似于我昨天在 reshaping matrices in R 上的问题，我现在正在尝试 reshape 数据框，以便我可以矢量化我的函数。在下面的代码中，主函数是scorecard .它接收一个名为 subset.loans 的数据框。和 subset.collateral .我想知道我是否可以 reshape 两个框架loans和 collaterals ，两者看起来像这样:

  LOANS              COLLATERAL           
id | value       id | value   type             
----------       -------------------             
 1     200        1     600      a
 2    4390        1     899      b               
 2     860        2     190      d               
 2    9750        3    4930      e               
 3     600        3     300      a               
 :       :        :       :      :

进入这个:

id | loans             collateral
-----------------------------
 1   c(200)            data.frame(a=c(600,899), b=('a','b'))
 2   c(4390,860,9750)  data.frame(a=c(190), b=c('d'))
 3   c(600)            data.frame(a=c(4930,300), b=c('e','a'))

我希望如果我这样做，我可以使用 *apply 之一函数 - 或来自 plyr 的东西工具箱 - 简单地应用 scorecard作用于整个事物。如果有更好/更简单的方法，请提及!我目前正在使用的代码(带有一个被遗弃的 for 循环)如下:

# An Nx2 data frame of loans (ID, amount)
loans <- read.table(...)

# An Mx4 data frame of collaterals to loans (ID, type, value, lien)
collateral <- read.table(...)

# One person (ID) can have >1 loan and >1 collateral, so first just
# find all unique IDs
loans.ID.unique = unique(loans$ID)

# Run an analysis on each ID grouping:
for(n in 1:length(loans.ID.unique)) {

  # ...all loans for that ID...
  subset.loans      <- loans$loans[
                         which(
                           loans$scorecard_id == loans.ID.unique[n])]

  # ...all collateral for that ID...
  subset.collateral <- collateral[
                         which(
                           collateral$scorecard_id == loans.ID.unique[n]),
                         c('type','value','lien')]

  # Output scores for each ID
  scores[n,1]   <- loans.ID.unique[n]
  scores[n,c(2,3)] <- scorecard(loans=subset.loans,
                                collateral=subset.collateral,
}

谢谢!

Answer 1

1) 无数据结构 .在 R 中创建这样的结构是不寻常的。建议你随时捕获你需要的东西。这里Loans和 Collateral是你的两个输入数据框和loans和 collateral是当前 id 的部分正在处理。用您自己的代码替换下面函数的双哈希行:

ids <- union(Loans$id, Collateral$id)
do.call("rbind", lapply(ids, function(id) {
    loans <- Loans[Loans$id == id, "value"]
    collateral <- Collateral[Collateral$id == id, -1]
    c(id = id, score = sum(loans) - sum(collateral$value)) ##
}))

添加:

2) 矩阵 .另一方面，如果我们真的想创建这样的结构，可以这样做:

ids <- union(Loans$id, Collateral$id) 
m <- cbind(id = ids,
    loans = lapply(ids, function(id)  Loans[Loans$id == id, "value"]),
    collateral = lapply(ids, function(id)  Collateral[Collateral$id == id, -1])
)

do.call("rbind", lapply(1:nrow(m), function(i) with(m[i,],
   c(id = id, score = sum(loans) - sum(collateral$value))
)))

3) 数据帧 .我们可以交替将结构表示为数据框 d <- as.date.frame(m)或以下几乎相同:

d <- data.frame(id = ids,
  loans = I(lapply(ids, function(id)  Loans[Loans$id == id, "value"])),
  collateral = I(lapply(ids, function(id)  Collateral[Collateral$id == id, -1]))
)
do.call("rbind", lapply(1:nrow(m), function(i) with(d, 
   c(id = id[[i]], score = sum(loans[[i]]) - sum(collateral[[i]]$value))
)))

编辑:简化了构建 m 的代码.

添加:数据框表示。