如何对数据框中的行进行分组，同时计算一列中的出现次数并对另一列中的值求和？

Question

我正在尝试修改我的数据框：

  start end duration_time
1     1   2         2.438
2     2   1         3.901
3     1   2        18.037
4     2   3        85.861
5     3   4        83.922

并创建如下内容：

  start end duration_time weight
1     1   2        20.475      2
2     2   1         3.901      1
4     2   3        85.861      1
5     3   4        83.922      1

所以重复的开始-结束组合将被删除，权重将增加，持续时间将相加

我已经有一个零件在工作，我只是无法让重量工作：

library('plyr')

df <- read.table(header = TRUE, text = "start end duration_time
1     1   2         2.438
2     2   1         3.901
3     1   2        18.037
4     2   3        85.861
5     3   4        83.922")

ddply(df, c("start","end"), summarise, weight=? ,duration_time=sum(duration_time))

Answer 1

base R 选项是 aggregate

do.call(data.frame, aggregate(duration_time~., df1,
       FUN = function(x) c(duration_time=sum(x), weight = length(x))))

Answer 2

使用 data.table 的最简单解决方案：

library(data.table)
setDT(df)[, .(duration_time=sum(duration_time), wt = .N) , by  =c("start", "end")]

   start end duration_time wt
1:     1   2        20.475  2
2:     2   1         3.901  1
3:     2   3        85.861  1
4:     3   4        83.922  1

---

尝试使用 dplyr, tidyr

library(dplyr)
library(tidyr)
df1 <- df %>% unite(by_var, start,end)
df2 <- cbind(df1 %>% count(by_var), df1 %>% group_by(by_var)%>% 
    summarise( duration_time=sum(duration_time))%>%
    separate(by_var, c("start","end")))[c(3,4,5,2)]

> df2
  start end duration_time n
1     1   2        20.475 2
2     2   1         3.901 1
3     2   3        85.861 1
4     3   4        83.922 1