循环以汇总大于R中的主题的观察结果

问题描述

我有一个看起来像这样的数据集

I have a data set that looks like that

set.seed(100)
da <- data.frame(exp = c(rep("A", 4), rep("B", 4)), diam = runif(8, 10, 30))

对于数据集中的每一行，我想总结比特定行中的直径大并且包含在"exp"级别中的观察值(直径).为此，我做了一个循环:

For each row in the data set I want to sum up observations (diam) that are bigger than the diam in the specific row and are included in a level "exp".To do that I made a loop:

da$d2 <- 0
for (i in 1:length(da$exp)){
 for (j in 1:length(da$exp)){
  if (da$diam[i] < da$diam[j] & da$exp[i] == da$exp[j]){
    da$d2[i] = da$d2[i] + da$diam[j]}
}
}

lopp正常工作，我得到了结果

The lopp works fine and I got results

  exp     diam       d2
1   A 16.15532 21.04645
2   A 15.15345 37.20177
3   A 21.04645  0.00000
4   A 11.12766 52.35522
5   B 19.37099 45.92347
6   B 19.67541 26.24805
7   B 26.24805  0.00000
8   B 17.40641 65.29445

但是，我的实际数据集远大于该数据集(> 40000行和> 100 exp水平)，因此循环非常慢. 我希望可以使用一些功能来简化计算.

However, my real data set is much bigger than that (> 40000 rows and >100 exp levels) so the loop goes very slow. I hope it is possible to use some function to facilitate calculations.

推荐答案

如果您不需要结果中的初始订单，则可以像这样高效地完成它:

If you don't require the initial order in the result you could do it quite efficiently like this:

library(data.table)
setorder(setDT(da), exp, -diam)
da[, d2 := cumsum(diam) - diam, by = exp]

da
#   exp     diam       d2
#1:   A 21.04645  0.00000
#2:   A 16.15532 21.04645
#3:   A 15.15345 37.20177
#4:   A 11.12766 52.35522
#5:   B 26.24805  0.00000
#6:   B 19.67541 26.24805
#7:   B 19.37099 45.92347
#8:   B 17.40641 65.29445

使用dplyr，那就是:

Using dplyr, that would be:

library(dplyr)
da %>%
  arrange(exp, desc(diam)) %>%
  group_by(exp) %>%
  mutate(d2 = cumsum(diam) - diam)

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