Combining two header rows

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White Belt

Combining two header rows

I am receiving data in the format below. I would like to merge the two header rows into one where it would merge 'Date and Product Qty'.  

 

 

 

Black Belt

What does it look like in Domo after you use the file upload?


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“There is a superhero in all of us, we just need the courage to put on the cape.” -Superman
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White Belt

It is an emailed dataset. Since first few headers are blank in the first header row, DOMO is renaming it as C1, C2.... and reading the rest of the lines as data (please see attached)

Black Belt

I don't think there's an easy way per-se to accomplish this.

 

1) create a rownumber called row_id using the Rank & Window Tile.

2) split your data using 2x SELECT tiles, with Row_ID in both SELECTS.  such that SELECT 1 contains all the 'other metrics' and SELECT 2 contains the months of  'projected quanitty.'

 

3) in SELECT 2, filter out the rows where the value = "projected quantity", then convert the data type to numeric. At this point you should have a ton of columns called 'dates' of data type number.

4) use Dynamic Pivot to collapse your data into a column containing Label "Dates", and values are the actual quantity.

5) add a constant "Metric" = "Projected Quantity.

6) JOIN SELECT 1 and reshaped SELECT 2 on the Row_ID.

 

Good luck!

 

 

collapse projected quantity using 'dynamic pivot.'  such that you pivot

 


Jae Wilson
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White Belt

Thanks, I was able to achieve what I was looking for by using 'Dynamic Pivot' function of the magic ETL. Thanks again for your help!

Black Belt

You should also be able to do this using the file connector.  Just click on edit selection and have the header include both rows:

user10539.png

 


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“There is a superhero in all of us, we just need the courage to put on the cape.” -Superman
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White Belt

Thanks. I receive this data every week. If I use data connector upload file, I will have to do it manually every week. I was looking for something that can automate this whole process, which I was able to do by using the unpivot function. Thanks to all of you for your quick replies!

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