I have two different datasets. The first one has some missing values and the second datasets contains the missing values.
How do I combine the two columns such that the missing values are filled in?
Identification | Values |
2 | |
3 | h |
4 | |
5 | h |
6 |
Identification | Values |
2 | g |
3 | |
4 | g |
5 | |
6 | |
Solved! Go to Solution.
Check out the join tool.
Firstly filter your top dataset to only those instances where there is no blank value.
You can then take this stream and perform a join to bring through the value from your lookup table.
The next step would be to union this joined dataset with the new value with those records that weren't blank in the first place.
Give this a go and let us know if you need further help!
Ben
Thank you very much for a quick reply, BenMoss.You are a real life saver.
I did still not manage to perform the task, may I get some further help?
Best regards,
Klara
Yes of course, if you send your workflow then we can have a look.
Ben
I built this, then re-read the first post by @BenMoss and realized it's essentially the same thing. So here's what his astute solution might look like!
This checks if there's a value in the first dataset (in case a value exists in both), then grabs the matching records from the second dataset. Hopefully this gets you close!
Code | Item | Date | Place |
123 | shoe | 12/4 | london |
124 | tie | 12/6 | paris
|
125 | 12/7 | Italy | |
126 | trousers | 12/8 | Bergen |
127 | 12/10 | Oslo |
Code | Item |
123 | |
124 | |
125 | dress |
126 | |
127 | tie |
Thank you so much. I made a new example, so that it should be easier to see what my problem is.
So, I cannot manage to get alteryx to merge the two datasets so that the item column is completely filled.
So sorry! Did not see all of your kind replies!
Thanks a lot all of you! It was very helpful!
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