按组以字符格式汇总金额

Question

我有一个数据框，其中包含个人之间的货币交易。交易可以是双向的，即A可以向B转账，B也可以向A转账。数据框的结构如下所示：

From  To  Amount
A     B   $100
A     C   $40
A     D   $30
B     A   $25
B     C   $70
C     A   $190
C     D   $110

我想总结每对相互交易的个体之间的交易总量，结果应该是这样的：

Individual_1  Individual_2    Sum
A             B               $125
A             C               $230
A             D               $30
B             C               $70
C             D               $110

我尝试使用包dplyr 的分组功能，但我认为它不适用于我的情况。

Answer 1

一个没有包的完整解决方案，基于 @RonakShah 的伟大的 pmin/pmax 方法，使用 aggregate 中的列表表示法（与公式表示法相反），它允许名称分配。

with(
  transform(d, a=as.numeric(gsub("\\D", "", Amount)), b=pmin(From, To), c=pmax(From, To)),
  aggregate(list(Sum=a), list(Individual_1=b, Individual_2=c), function(x) 
    paste0("$", sum(x))))
#   Individual_1 Individual_2  Sum
# 1            A            B $125
# 2            A            C $230
# 3            B            C  $70
# 4            A            D  $30
# 5            C            D $110

---

数据：

d <- structure(list(From = c("A", "A", "A", "B", "B", "C", "C"), To = c("B", 
"C", "D", "A", "C", "A", "D"), Amount = c("$100", "$40", "$30", 
"$25", "$70", "$190", "$110")), class = "data.frame", row.names = c(NA, 
-7L))

Answer 2

您可以使用pmin/pmax 对From 和To 列和sum 排序Amount 值。

library(dplyr)

df %>%
  group_by(col1 = pmin(From, To), 
           col2 = pmax(From, To)) %>%
  summarise(Amount = sum(readr::parse_number(Amount)))

#  col1  col2  Amount
#  <chr> <chr>  <dbl>
#1 A     B        125
#2 A     C        230
#3 A     D         30
#4 B     C         70
#5 C     D        110

---

在基础 R 中使用相同的逻辑，您可以这样做：

aggregate(Amount~col1 + col2, 
      transform(df, col1 = pmin(From, To), col2 = pmax(From, To), 
                Amount = as.numeric(sub('$', '', Amount, fixed = TRUE))), sum)

数据

df <- structure(list(From = c("A", "A", "A", "B", "B", "C", "C"), To = c("B", 
"C", "D", "A", "C", "A", "D"), Amount = c("$100", "$40", "$30", 
"$25", "$70", "$190", "$110")), class = "data.frame", row.names = c(NA, -7L))

Answer 3

使用tidyverse 包的解决方案。您需要找到一种方法来创建具有正确的个人顺序的公共分组列。 dat2 是最终输出。

library(tidyverse)

dat2 <- dat %>%
  mutate(Amount = as.numeric(str_remove(Amount, "\\$"))) %>%
  mutate(Group = map2_chr(From, To, ~str_c(sort(c(.x, .y)), collapse = "_"))) %>%
  group_by(Group) %>%
  summarize(Sum = sum(Amount, na.rm = TRUE)) %>%
  separate(Group, into = c("Individual_1", "Individual_2"), sep = "_") %>%
  mutate(Sum = str_c("$", Sum))
print(dat2)
# # A tibble: 5 x 3
#   Individual_1 Individual_2 Sum  
#   <chr>        <chr>        <chr>
# 1 A            B            $125 
# 2 A            C            $230 
# 3 A            D            $30  
# 4 B            C            $70  
# 5 C            D            $110 

数据

dat <- read.table(text = "From  To  Amount
A     B   $100
A     C   $40
A     D   $30
B     A   $25
B     C   $70
C     A   $190
C     D   $110",
                header = TRUE)