My original dataset looks very similar to the sample dataset attached in the workflow. I'm also listing it below:
Id | Name | Country | Department |
1 | Ron | US | HR |
2 | John | US | HR |
2 | John | US | IT |
2 | John | US | IT |
3 | Kelly | US | IT |
3 | Kelly | US | IT |
4 | Dave | US | Sales |
4 | Dave | US | IT |
4 | Dave | US | IT |
4 | Dave | US | Marketing |
5 | Nora | US | IT |
I want to display the names of those employees who have worked only in the IT department. For example, John has worked in both HR and IT, so I would want to exclude his name from my output. Initially I thought of using group by, concatenating the columns country and department and then applying a filter but that does not seem to be a good solution. What should another approach be?
Based on the above example, my output should look something like the table below:
Id | Name | Country | Department |
3 | Kelly | US | IT |
3 | Kelly | US | IT |
5 | Nora | US | IT |
Solved! Go to Solution.
Hi @keeprollin ,
Please find attached a sample workflow. This is one way of doing it. The other way would be using regex.
Hope this helps.
Best,
Jagdeesh
My way was identical to @JagdeeshN - That's the fastest way I can think of doing it.
Yes, that was my initial thought as a potential solution which I have mentioned in the post. However, I was just wondering if there was other approach to it instead of summarizing and concatenating.