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How to introduce new column(s) to the data set without losing the unmatched data?

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Meteoroid

Hello!

I am building up a data set from multiple resources, I have a matching ID column in both data sets to join the tow separate entries into one wide data set by using the join tool by ID column and get to keep some of the new columns into the blended on data set using join tool. However , Join will only keep the matching ID data and eliminate the non matching IDs into L or R entry!

My goal is to add the new column from the second data set by matching it to its corresponding ID from the first data set while assigning zero values or nulls to the introduced column from data set 2 for the rows that does not find a matching ID 

I tried Union tool but it does not work because When I try to union L & J from the outputs of Joint tool, it only stack up ID column, while I want stack the new introduced column which is not existing in the first data set 

 

Can anyone give me a quick help with that? I need to solve this issue to proceed with my research project and I am stuck !

 

Many thanks

Alteryx Certified Partner

@maxmd

It does sound like you need to use the Union tool but perhaps you need help with it?

Here is a workflow that shows how you union the data from the second dataset with the 1st.  When you union in data from the 2nd dataset with the joined data, it will show null values in the fields that don't exist in the 2nd dataset.  If you need more help with it, put some sample data together and I'll demonstrate with your data.

Let me know if you have more questions.

Meteoroid

Thank you so much.

I tried it before and it did not work for me for some reason! Now after your example, I did it again and it is working.

 

I really appreciate our quick help

Cheers. 

Alteryx Certified Partner

@maxmd,

No problem.  I actually worded my response wrong.  What i created brings in all of the data and fields from dataset2 but puts nulls in the fields from the 1st dataset.

Meteoroid

Now I understand the Union Tool very well. thanks a lot

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