合并两个数据框并汇总 [英] combine two data frames and aggregate

问题描述

我有以下格式的2个数据帧:

I am having 2 data frames in the below format:

dt1

id     col1    col2    col3    col4 
___    ____    ____    _____   _____
 1      2       3       1       2
 2      3       4       1       1
 3      1       1       1       1
 4      1       2       1       2
 5      1       1       1       1
 6      1       2       1       2

dt2 

id     col1    col2    col3    col4 
___    ____    ____    _____   _____
 1      1       3       1       2
 2      3       4       1       0
 4      1       1       1       1
 6      1       2       1       2
 9      2       1       1       1
12      1       2       1       2

我想通过id和生成的数据帧将这两个数据帧聚合并合并在一起

and I want to aggregate and combine these two data frames by the id and the resulting dataframe like

dt3

 id     col1    col2    col3    col4 
    ___    ____    ____    _____   _____
     1      3       6       2       4
     2      6       8       2       1
     3      1       1       1       1
     4      2       3       2       3
     5      1       1       1       1
     6      2       4       2       4
     9      2       1       1       1
    12      1       2       1       2

我尝试了 dt3 = merge(dt1，dt2，all = TRUE)但没有用，也尝试了 dt3 = merge(dt1，dt2，by = id)也不起作用.感谢您的帮助.

I tried with dt3=merge(dt1,dt2,all=TRUE) but did not work.Also tried dt3=merge(dt1,dt2,by=id) too did not work.Any help is appreciated.

推荐答案

我们可以在 data.table 中使用 rbindlist 并获取 sum 按"id"分组后各列的大小

We can use rbindlist in data.table and get the sum of each column after grouping by 'id'

library(data.table)
rbindlist(mget(paste0('dt', 1:2)))[, lapply(.SD, sum), by = id]
#    id col1 col2 col3 col4
#1:  1    3    6    2    4
#2:  2    6    8    2    1
#3:  3    1    1    1    1
#4:  4    2    3    2    3
#5:  5    1    1    1    1
#6:  6    2    4    2    4
#7:  9    2    1    1    1
#8: 12    1    2    1    2

---

或者将 bind_rows 与 tidyverse

librarydplyr)
bind_rows(dt1, dt2) %>%
          group_by(id) %>%
          summarise_each(funs(sum))

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