Question

我有一个描述公司所有权级别的数据框，如下所示：

Company   Subsidiary1    Subsidiary2    Subsidiary3
DE5930      DE5931           NA             NA
GB3489      GB3490           NA             NA
GB3489      GB3490         GB3491           NA
US2036      US2037           NA             NA
US2036      US2037         US2038           NA
US2036      US2037         US2038         GB3491
....# and so on

现在，我想为每个公司在所有子公司中创建一列，如下所示：

Company   Subsidiaries
DE5930     DE5931          
GB3489     GB3490
GB3489     GB3491
US2036     US2037
US2036     US2038       
US2036     GB3491

数据集确实很大（超过100.000行），我无法使用group_by或aggregate函数找到任何解决方案，因为大多数示例都是针对数字变量（例如，平均值）。

一个想法是删除带有df[ !duplicated(df$Subsidiary1), ]的重复项，以保留每个子公司的首次出现，然后将值向左移动，但是问题是一个子公司可能属于多个公司（例如“ GB3491 ”），而我不想放弃这些意见。有没有解决这个问题的好方法？

提前谢谢！

Answer 1

我建议使用下一种tidyverse方法：

library(tidyverse)
#Data
df <- structure(list(Company = c("DE5930", "GB3489", "GB3489", "US2036", 
"US2036", "US2036"), Subsidiary1 = c("DE5931", "GB3490", "GB3490", 
"US2037", "US2037", "US2037"), Subsidiary2 = c(NA, NA, "GB3491", 
NA, "US2038", "US2038"), Subsidiary3 = c(NA, NA, NA, NA, NA, 
"GB3491")), class = "data.frame", row.names = c(NA, -6L))

代码：

df %>% pivot_longer(cols = -Company) %>% select(-name) %>%
  filter(!is.na(value)) %>%
  filter(!duplicated(paste(Company,value)))

输出：

# A tibble: 6 x 2
  Company value 
  <chr>   <chr> 
1 DE5930  DE5931
2 GB3489  GB3490
3 GB3489  GB3491
4 US2036  US2037
5 US2036  US2038
6 US2036  GB3491

Answer 2

我们可以使用coalesce

library(dplyr)
df1 %>%
    transmute(Company, Subsidiaries = 
        coalesce(!!! rlang::syms(rev(names(df1)[-1]))))
#  Company Subsidiaries
#1  DE5930       DE5931
#2  GB3489       GB3490
#3  GB3489       GB3491
#4  US2036       US2037
#5  US2036       US2038
#6  US2036       GB3491

或者通过base R使用max.col

cbind(df1[1], Subsidiaries =  df1[-1][cbind(seq_len(nrow(df1)), 
         max.col(!is.na(df1[-1]), "last"))])

数据

df1 <- structure(list(Company = c("DE5930", "GB3489", "GB3489", "US2036", 
"US2036", "US2036"), Subsidiary1 = c("DE5931", "GB3490", "GB3490", 
"US2037", "US2037", "US2037"), Subsidiary2 = c(NA, NA, "GB3491", 
NA, "US2038", "US2038"), Subsidiary3 = c(NA, NA, NA, NA, NA, 
"GB3491")), class = "data.frame", row.names = c(NA, -6L))

如何按组汇总/列出多个列的值？

2 个答案:

数据