删除/移动其他数据框中具有匹配值的行

发布于 2025-02-04 01:31:14 字数 1781 浏览 4 评论 0原文

我目前正在努力在某些系统错误发生后管理产品退款。我有一个巨大的XLXS列表（表1），所有等待的退款几周。但是，该表中的某些记录已手动退还并存储在单独的文件中（表2）。

以下是我的数据集的示例：

所有退款表：

数字	订购	数量	状态
1	123456789	150.50	待定
2	235641458	250.30	待定
3	235984258	50.20 50.20 50.20	迫在眉睫
4	283478566	102.45	悬而未决

数字	订单	数量	状态
1 1	123456789	150.50	退还
2	235641458	250.30 250.30	退还

我现在希望做的是删除（最好移动到单独的表中）“所有退款表”中的行与“订单订单”匹配的“订单”的“手动退还表”的订单Number匹配。你们能帮我吗？

谢谢！

原文

I'm currently working on managing refunding of products after some systems errors occured.
I have a huge xlxs list (table 1) with all pending refunds of a couple of weeks. However, some of the records in that table have been manually refunded and stored in a seperate file (table 2).

Here is an example of my data sets:

All refunds table:

number	ordernumber	Amount	Status
1	123456789	150.50	pending
2	235641458	250.30	pending
3	235984258	50.20	pending
4	283478566	102.45	pending

Manually refunded table

number	ordernumber	Amount	Status
1	123456789	150.50	refunded
2	235641458	250.30	refunded

What I now wish to do is delete (preferably move to a separate table) the rows in the 'all refunds table' whenever the ordernumber matches the ordernumber in the 'manually refunded table'. Could you guys help me out?

Thanks!

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九公里浅绿 2025-02-11 01:31:14

使用base r，您可以将匹配的OrderNumber与以下代码进行子集匹配：

all_refunds <- data.frame(
  ordernumber = c(123456789, 235641458,     235984258,  283478566),
  amount = c(150.50, 250.30, 50.20, 102.45),
  status = rep("pending", 4)
)

manual_refunds <- data.frame(
  ordernumber = c(123456789, 235641458),
  amount = c(150.50, 250.30)
)

matching <- all_refunds$ordernumber %in% manual_refunds$ordernumber #Find matching ordernumbers.

然后您可以制作一个带有匹配行的新表，然后从All_refunds表中删除行，例如：

registered_refunds <- all_refunds[matching, ] #Select only matching from all_refunds
all_refunds <- all_refunds[!matching, ] #Select rows that DO NOT match in all_refunds and reassign the table.

给出输出：

>all_refunds
  ordernumber amount  status
3   235984258  50.20 pending
4   283478566 102.45 pending
> registered_refunds
  ordernumber amount  status
1   123456789  150.5 pending
2   235641458  250.3 pending

With base R you can subset matching ordernumber's with following code:

all_refunds <- data.frame(
  ordernumber = c(123456789, 235641458,     235984258,  283478566),
  amount = c(150.50, 250.30, 50.20, 102.45),
  status = rep("pending", 4)
)

manual_refunds <- data.frame(
  ordernumber = c(123456789, 235641458),
  amount = c(150.50, 250.30)
)

matching <- all_refunds$ordernumber %in% manual_refunds$ordernumber #Find matching ordernumbers.

You can then make a new table with matching rows and remove the rows from all_refunds table, like this:

registered_refunds <- all_refunds[matching, ] #Select only matching from all_refunds
all_refunds <- all_refunds[!matching, ] #Select rows that DO NOT match in all_refunds and reassign the table.

Giving the output:

>all_refunds
  ordernumber amount  status
3   235984258  50.20 pending
4   283478566 102.45 pending
> registered_refunds
  ordernumber amount  status
1   123456789  150.5 pending
2   235641458  250.3 pending

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冷默言语 2025-02-11 01:31:14

您可以尝试

all_refund <- read.table(text = "number ordernumber Amount  Status
1   123456789   150.50  pending
2   235641458   250.30  pending
3   235984258   50.20   pending
4   283478566   102.45  pending", header = T)
manually <- read.table(text = "number   ordernumber Amount  Status
1   123456789   150.50  refunded
2   235641458   250.30  refunded", header = T)

all_refund[!(all_refund$ordernumber %in% manually$ordernumber),]

  number ordernumber Amount  Status
3      3   235984258  50.20 pending
4      4   283478566 102.45 pending

You may try

all_refund <- read.table(text = "number ordernumber Amount  Status
1   123456789   150.50  pending
2   235641458   250.30  pending
3   235984258   50.20   pending
4   283478566   102.45  pending", header = T)
manually <- read.table(text = "number   ordernumber Amount  Status
1   123456789   150.50  refunded
2   235641458   250.30  refunded", header = T)

all_refund[!(all_refund$ordernumber %in% manually$ordernumber),]

  number ordernumber Amount  Status
3      3   235984258  50.20 pending
4      4   283478566 102.45 pending

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