批处理列聚合和重新排序 R 中的 dataframe

Question

我有人口普查数据将我的年龄变量按性别划分为男性 (varname_m) 和女性 (varname_f) 的值：

Rows: 146,112
Columns: 13
$ tractid    <chr> "01001020100", "01001020100", "01001020200", "01001020200", "01001020300", "01001020300", "01001020400", "01001020400", "01001020500", "01001020500", "0100102060…
$ ag18to19_m <dbl> 37, 57, 24, 15, 49, 27, 87, 33, 293, 159, 57, 40, 19, 41, 18, 56, 143, 86, 25, 155, 41, 7, 40, 0, 35, 0, 99, 25, 190, 420, 61, 157, 63, 110, 37, 127, 67, 45, 198…
$ ag20_m     <dbl> 6, 14, 64, 0, 11, 18, 16, 8, 115, 21, 42, 15, 53, 71, 16, 0, 63, 77, 43, 96, 32, 15, 21, 0, 12, 44, 8, 0, 105, 80, 34, 20, 8, 0, 13, 46, 88, 0, 83, 241, 10, 96, …
$ ag21_m     <dbl> 18, 0, 15, 7, 0, 16, 117, 18, 14, 40, 23, 26, 45, 47, 32, 0, 41, 50, 0, 76, 14, 45, 20, 1, 48, 11, 11, 30, 18, 30, 60, 55, 20, 0, 28, 43, 31, 21, 9, 0, 11, 8, 0,…
$ ag22to24_m <dbl> 48, 64, 109, 45, 25, 62, 65, 41, 224, 531, 28, 51, 31, 60, 0, 24, 132, 96, 59, 98, 27, 45, 111, 30, 113, 58, 71, 61, 46, 114, 11, 86, 116, 99, 28, 158, 72, 135, …
$ ag25to29_m <dbl> 49, 31, 83, 99, 87, 144, 153, 142, 428, 327, 69, 35, 36, 22, 61, 113, 202, 420, 184, 255, 94, 84, 118, 82, 71, 30, 47, 195, 44, 135, 118, 150, 215, 157, 118, 180…
$ ag30to34_m <dbl> 52, 72, 59, 97, 84, 157, 124, 85, 415, 227, 95, 13, 105, 202, 37, 86, 274, 334, 161, 182, 91, 173, 84, 84, 81, 106, 79, 67, 263, 77, 40, 115, 199, 411, 81, 115, …
$ ag18to19_f <dbl> 33, 8, 51, 7, 31, 19, 107, 15, 33, 25, 47, 37, 35, 81, 98, 92, 127, 147, 72, 0, 109, 57, 7, 74, 78, 0, 36, 24, 109, 268, 88, 62, 10, 0, 47, 33, 79, 191, 63, 134,…
$ ag20_f     <dbl> 13, 40, 23, 18, 27, 18, 12, 11, 37, 0, 58, 83, 19, 45, 20, 77, 16, 103, 0, 36, 15, 0, 8, 37, 29, 34, 36, 0, 23, 30, 37, 0, 10, 48, 51, 67, 17, 15, 125, 55, 27, 1…
$ ag21_f     <dbl> 40, 6, 13, 24, 36, 0, 16, 19, 17, 0, 11, 0, 0, 89, 28, 31, 39, 20, 15, 0, 7, 13, 0, 17, 9, 13, 17, 47, 106, 36, 42, 94, 0, 13, 19, 50, 67, 0, 122, 48, 21, 9, 145…
$ ag22to24_f <dbl> 21, 67, 71, 21, 69, 35, 28, 165, 346, 350, 15, 0, 53, 50, 25, 42, 207, 165, 158, 114, 20, 0, 73, 66, 29, 29, 59, 39, 83, 94, 22, 24, 79, 69, 37, 21, 73, 201, 282…
$ ag25to29_f <dbl> 36, 24, 86, 51, 88, 160, 130, 73, 318, 539, 157, 127, 128, 111, 86, 29, 334, 365, 87, 217, 57, 60, 177, 92, 17, 90, 86, 113, 67, 204, 136, 120, 130, 108, 211, 51…
$ ag30to34_f <dbl> 36, 73, 38, 42, 87, 154, 63, 84, 440, 414, 51, 95, 151, 73, 27, 70, 429, 458, 231, 173, 54, 82, 104, 24, 61, 159, 69, 30, 218, 82, 88, 214, 222, 158, 76, 125, 24…

我想将每个按性别划分的变量汇总为一个组合变量。 比如我想添加 ag18to19_m 和 ag18to19_f 来创建 ag18to19。 我可以使用 mutate 和以下代码轻松完成此操作，并将它们排序到数据框的前面：

aggregated <- merged %>% 
  mutate(ag18to19 = ag18to19_m + ag18to19_f) %>% 
  relocate(ag18to19, .before = ag18to19_m)  %>% 
  
  mutate(ag20 = ag20_m + ag20_f) %>% 
  relocate(ag20, .before = ag20_m)  %>% 
  
  mutate(ag21 = ag21_m + ag21_f) %>% 
  relocate(ag21, .before = ag21_m)  %>% 
  
  mutate(ag22to24 = ag22to24_m + ag22to24_f) %>% 
  relocate(ag22to24, .before = ag22to24_m)  %>% 
  
  mutate(ag25to29 = ag25to29_m + ag25to29_f) %>% 
  relocate(ag25to29, .before = ag25to29_m)  %>% 
  
  mutate(ag30to34 = ag30to34_m + ag30to34_f) %>% 
  relocate(ag30to34, .before = ag30to34_m)

我知道有一种更有效的方法可以使用循环或 map_df function 来执行此操作，它还将给我一个数据帧作为 output。 在过去的一个小时里，我一直在尝试编写 function 并使用 map_df 但没有任何成功。 有人有建议吗？

这里更有效的代码是最佳实践，它将帮助我将相同的数据清理步骤应用于以相同方式分组的其他几个变量（例如，按性别分组的收入或按年龄分组的教育）。

任何帮助将不胜感激。 谢谢。

Answer 1

这是tidyverse中的一个选项

library(dplyr)
library(stringr)
merged1 <- merged %>% 
     mutate(across(ends_with('_m'), ~ 
                   . + get(str_replace(cur_column(), '_m', '_f')),
                .names = '{.col}_new')) %>%
       rename_at(vars(ends_with('_new')),
              ~ str_remove(., '_[m]_new$')) %>%
       select(tract_id, order(names(.)[-1]) + 1)