Question

我的数据如下：

| Location | ticketPeriod | UserID | ticketUses | Demographic |    Date    |
|----------|--------------|--------|------------|-------------|------------|
| London   | Day          |      1 |          1 | Adult       | 21/03/2019 |
| London   | Day          |      1 |          2 | Adult       | 06/02/2019 |
| Glasgow  | Day          |      1 |          1 | Adult       | 04/04/2019 |
| Glasgow  | Day          |     12 |          3 | Child       | 03/04/2019 |
| Glasgow  | Day          |      3 |          1 | Child       | 04/01/2019 |
| Glasgow  | Week         |      2 |          3 | Child       | 27/01/2019 |
| Glasgow  | Month        |      3 |          3 | Concession  | 04/04/2019 |
| London   | Annual       |      5 |          2 | Concession  | 15/02/2019 |
| London   | Quarterly    |      5 |          1 | Adult       | 13/02/2019 |
| Cardiff  | Annual       |      5 |          1 | Adult       | 24/01/2019 |
| Cardiff  | Quarterly    |      1 |          1 | Child       | 11/03/2019 |
| London   | Week         |      3 |          2 | Child       | 04/04/2019 |
| Cardiff  | Week         |     12 |          4 | Adult       | 04/04/2019 |
| London   | Annual       |      3 |          9 | Adult       | 04/04/2019 |

我想做的是对数据进行分组，以获取最少的日期并计算票证的使用情况，但要保留日期字段，如下所示；

| Location | ticketPeriod | UserID | ticketUses | Demographic |    Date    |  MinDate   | countTicketUses |
|----------|--------------|--------|------------|-------------|------------|------------|-----------------|
| Cardiff  | Annual       |      5 |          1 | Adult       | 24/01/2019 | 24/01/2019 |               1 |
| Cardiff  | Quarterly    |      1 |          1 | Child       | 11/03/2019 | 11/03/2019 |               1 |
| Cardiff  | Week         |     12 |          4 | Adult       | 04/04/2019 | 04/04/2019 |               4 |
| Glasgow  | Day          |      3 |          1 | Child       | 04/04/2019 | 04/01/2019 |               5 |
| Glasgow  | Day          |      3 |          3 | Child       | 03/04/2019 | 04/01/2019 |               5 |
| Glasgow  | Day          |      3 |          1 | Child       | 04/01/2019 | 04/01/2019 |               5 |
| Glasgow  | Week         |      2 |          3 | Child       | 27/01/2019 | 27/01/2019 |               6 |
| Glasgow  | Week         |      3 |          3 | Child       | 04/04/2019 | 27/01/2019 |               6 |
| London   | Day          |      1 |          1 | Adult       | 21/03/2019 | 06/02/2019 |              17 |
| London   | Day          |      1 |          2 | Adult       | 06/02/2019 | 06/02/2019 |              17 |
| London   | Day          |      5 |          2 | Adult       | 15/02/2019 | 06/02/2019 |              17 |
| London   | day          |      5 |          1 | Adult       | 13/02/2019 | 06/02/2019 |              17 |
| London   | day          |      3 |          2 | Adult       | 04/04/2019 | 06/02/2019 |              17 |
| London   | day          |      3 |          9 | Adult       | 04/04/2019 | 06/02/2019 |              17 |

基本上等于group by，在R中进行突变。

Answer 1

您可以使用窗口功能来做到这一点：

select Location, 
       ticketPeriod,
       UserID, 
       ticketUses, 
       Demographic, 
       Date, 
       min(date) over (partition by ticketPeriod, Demographic) as MinDate, 
       sum(ticketUses) over (partition by ticketPeriod, Demographic) as countTicketUses 
from the_table;

在SQL中，如何提取组的记录日期和最小日期？

1 个答案: