删除冲销交易 [英] Remove reversal transaction

问题描述

我有一些冲销交易的交易水平数据.这些交易用负数表示，然后用正数表示.

I have transaction level data with some reversal transactions. These transactions are denoted by a negative amount and then a counterpart positive.

trnx_df <- data.frame(Date = c("2018-01-01", "2018-01-01", "2018-01-01", "2018-01-01", "2018-01-03", "2018-01-03", "2018-01-05", "2018-02-01",
                            "2018-02-01", "2018-02-01"),
                   Product = c("A", "A", "A", "A", "B", "B", "B", "A", "A", "A"),
                   Amount = c(-1000, 1000, 1000, 1000, -1000, 1000, 500, -2000, 1000, 2000))

trnx_df

             Date Product Amount
    1  2018-01-01       A  -1000
    2  2018-01-01       A   1000
    3  2018-01-01       A   1000
    4  2018-01-01       A   1000
    5  2018-01-03       B  -1000
    6  2018-01-03       B   1000
    7  2018-01-05       B    500
    8  2018-02-01       A  -2000
    9  2018-02-01       A   1000
    10 2018-02-01       A   2000

我想得出该客户在特定产品上花费的总金额和最高金额.

I want to arrive at total amount and maximum amount spent by that customer on particular product.

通过使用 dplyr 我到达:

library(dplyr)

trnx_summary <- trnx_df %>%
group_by(Product) %>%
summarize(Total_amount = sum(Amount),
        Max_amount = max(Amount))

trnx_summary
  Product Total_amount Max_amount
1       A         3000       2000
2       B          500       1000

总而言之，这是没有问题的，因为负数条目将抵消正数条目，但是如果花费最大，我将得到错误的输出结果.

For total there will be no problem as the negative entry will cancel out positive one but for maximum amount spent I will get wrong output.

产品A 的最大金额应为1000( 2000 和 -2000 将相互抵消).

The maximum amount for Product A should be 1000 (2000 and -2000 will cancel each other out).

我该如何解决?另外，是否有办法从 dataframe 本身删除这些冲销交易?

How can I fix this? Also, is there a way to delete these reversal transactions from the dataframe itself?

推荐答案

df %>% #filter the negative transactions, save in dftemp
  filter(Amount < 0) %>% 
  mutate(Amount = abs(Amount)) -> dftemp # in dftemp, negative transactions are positive to ease looking for matches

df %>%  #filter the positive transactions that do no have a negative duplicate
  filter(Amount > 0) %>% 
  anti_join(dftemp) -> dfuniques  

df %>% 
  filter(Amount > 0) %>% #filter positive transactions
  inner_join(dftemp) %>% #merge obs that are both in the original df and in dftemp 
  group_by(Date, Product, Amount) %>%  #group by date, product and amount
  slice(-1) %>% #for each date, product & amount combo, delete 1 row (which is a duplicate of one negative and one positive transaction)
  full_join(dfuniques) %>% # join the unique positive transactions (from here on, you have your desired dataframe with negative and positive transactions that cancelled each other out deleted)
  group_by(Product) %>% 
  summarise(Total_Amount = sum(Amount), Max_Amount = max(Amount))

  Product Total_Amount Max_Amount
   <fctr>        <dbl>      <dbl>
1       A         3000       1000
2       B          500        500

这篇关于删除冲销交易的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！