The ultimate Fabric, Power BI, SQL, and AI community-led learning event. Save €200 with code FABCOMM.
Get registeredEnhance your career with this limited time 50% discount on Fabric and Power BI exams. Ends September 15. Request your voucher.
Hello,
Can somebody help me out how to transform the data as below?
Thanks in advance.
data here
type | date_time | name | car | Date |
Key In | 2023-11-14T14:25:56.0370000 | Kim | T111 | 11/14/2023 |
Key Out | 2023-11-14T11:33:54.0570000 | Kim | T111 | 11/14/2023 |
Key In | 2023-11-08T16:57:54.0570000 | Kim | T111 | 11/8/2023 |
Key Out | 2023-11-08T14:49:20.0530000 | Kim | T111 | 11/8/2023 |
Key In | 2023-11-06T17:25:38.0530000 | Kim | T111 | 11/6/2023 |
Key Out | 2023-11-06T14:28:34.0500000 | Kim | T111 | 11/6/2023 |
Key In | 2023-10-10T17:45:20.0370000 | Kim | T111 | 10/10/2023 |
Key Out | 2023-10-10T16:30:29.0430000 | Kim | T111 | 10/10/2023 |
Key In | 2023-10-10T10:10:40.0430000 | Kim | T111 | 10/10/2023 |
Key Out | 2023-10-10T08:04:51.0470000 | Kim | T111 | 10/10/2023 |
Key In | 2023-10-06T13:00:23.0370000 | Kim | T111 | 10/6/2023 |
Key Out | 2023-10-06T09:29:57.0400000 | Kim | T111 | 10/6/2023 |
Key In | 2023-10-06T10:03:11.0370000 | Kim | T111 | 10/6/2023 |
Key Out | 2023-10-06T08:22:57.0400000 | Kim | T111 | 10/6/2023 |
Key In | 2023-10-06T07:53:11.0370000 | Kim | T111 | 10/6/2023 |
Key Out | 2023-10-06T07:32:57.0400000 | Kim | T111 | 10/6/2023 |
Solved! Go to Solution.
to know how to do this watch my video
to know how to do this watch my video
Hi,
In the Query Editor, click on any cell in the type column and click on Pivot Column. Select date_time column and the Aggregate function as Don's aggregate.
Shouldn't the duration be Key_in - Key_out ?
User | Count |
---|---|
65 | |
62 | |
60 | |
54 | |
30 |
User | Count |
---|---|
180 | |
88 | |
72 | |
48 | |
46 |