查找列中的值之间具有给定差异的行

Question

对于 R 中的 data.table（或 data.frame），我希望找到所有包含列“值”中的值的行，这些行与具有相同键的行中的另一个值的给定距离“距离” .因此，鉴于以下情况：

distance <- 22
   key value
   A     1
   B     1
   C     1
   D     1
   A     4
   B     4
   A    23
   B    23
   B    26
   B    26
   C    30

我想用相同键的行数和一个 +22 的值来注释原始表：

  key value count
  A     1     1
  B     1     1
  C     1     0
  D     1     0
  A     4     0
  B     4     2
  A    23     0
  B    23     0
  B    26     0
  B    26     0
  C    30     0

我真的不知道从哪里开始使用这种在 R 中操作数据的自引用方法。我最初的尝试涉及创建第二个表并尝试与之匹配，但这似乎是一种奇怪且糟糕的方法。

注意：我正在使用 data.table 包，但我很乐意在这种情况下使用 data.frame 工作，如果这样可以让事情变得更容易。

可重现性：

require(data.table)
source <- data.table(data.frame(key=c("A","B","C","D","A","B","A","B","B","B", "C"),value=c(1,1,1,1,4,4,23,23,26,26,30)))
result <- data.table(data.frame(key=c("A","B","C","D","A","B","A","B","B","B","C"),value=c(1,1,1,1,4,4,23,23,26,26,30),count=c(1,1,0,0,0,2,0,0,0,0,0)))

Answer 1

这是一个基于data.table 的解决方案。我有兴趣了解可以对其进行哪些改进（如果有的话）。

# Your code
library(data.table)
source <- 
data.table(data.frame(key = c("A","B","C","D","A","B","A","B","B","B", "C"),
                      value = c(1,1,1,1,4,4,23,23,26,26,30)))

那个奇怪的data.table(data.frame(... 是因为data.table() 也有一个叫key 的参数。这是使用名为"key" 的列创建data.table 的一种方法。大写以避免参数名称冲突说明了更标准的语法：

source <- data.table(Key = c("A","B","C","D","A","B","A","B","B","B","C"),
                     Value = c(1,1,1,1,4,4,23,23,26,26,30))

接下来为了避免以后需要as.integer()，我们现在将Value 列的类型从numeric 更改为integer。请记住，R 中的1 是numeric，它是1L，即integer。将integer 数据存储为integer 通常比将integer 存储为numeric 效率更高。下一行比在上面输入大量Ls 更容易。

source[,Value:=as.integer(Value)]   # change type from `numeric` to `integer`

现在继续

distance <- 22L
setkey(source, Key, Value)

# Heart of the solution (following a few explanatory comments):
#  "J()"   : shorthand for 'data.table()'
#  ".N"    : returns the number of rows that matched a line (see ?data.table)
#  "[[3]]" : as with simple data.frames, extracts the vector in column 3

source[,count:=source[J(Key,Value+distance),.N][[3]]]
source
      key value count
 [1,]   A     1     1
 [2,]   A     4     0
 [3,]   A    23     0
 [4,]   B     1     1
 [5,]   B     4     2
 [6,]   B    23     0
 [7,]   B    26     0
 [8,]   B    26     0
 [9,]   C     1     0
[10,]   C    30     0
[11,]   D     1     0

请注意，:= 直接通过引用更改了source，就是这样。但是setkey()也改变了原始数据的顺序。如果需要保留原订单，则：

source <- data.table(Key = c("A","B","C","D","A","B","A","B","B","B","C"),
                     Value = c(1,1,1,1,4,4,23,23,26,26,30))
source[,Value:=as.integer(Value)]   
source[,count:=setkey(copy(source))[source[,list(Key,Value+distance)],.N][[3]]]

      Key Value count
 [1,]   A     1     1
 [2,]   B     1     1
 [3,]   C     1     0
 [4,]   D     1     0
 [5,]   A     4     0
 [6,]   B     4     2
 [7,]   A    23     0
 [8,]   B    23     0
 [9,]   B    26     0
[10,]   B    26     0
[11,]   C    30     0

Answer 2

您可以使用mapply 循环遍历键和值的所有组合：

data.table(t(mapply(function(key,val) 
      c(key=key,value=val,count=length(source$value[source$key==key & source$value>(val+distance)]) )
   , as.character(source$key),source$value)))