Iterate through columns to skip NULL values

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Posted on by CU03021749-0

I have a seemingly simple flow that takes data from excel and imports to Dataverse. The excel data is set up such that column A contains the Part ID. Columns B thru Z contain various measurement fields. My flow maps everything correctly but I'm struggling with values in excel that are blank (NULL) causing a the flow to fail. I've tried a few methods:

1) Check for empty values and write NULL to dataverse. The issue with this is it overwrites any existing dataverse data with a NULL value.

if(empty(items('Apply_to_each')?['Measurement 1']), null,items('Apply_to_each')?['Measurement 1'])
 
2) Send empty value ('') to dataverse. The issue with this is columns require a numeric value.
if(empty(items('Apply_to_each')?['Measurement 1']), '', items('Apply_to_each')?['Measurement 1'])
 
I've read dynamically building each row is the way to go but I don't know how to loop through each column. Is there a way to loop through each column for each row and dynamically check whether the cell contains a value or not? Then build a variable with columns that contain a value and update those in dataverse?

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David_MA 14,499 Super User 2026 Season 1 on at

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Use the coalesce expression to populate Dataverse. It is designed to handle with you have null values: Blank, Coalesce, IsBlank, and IsEmpty functions - Power Platform | Microsoft Learn

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CU03021749-0 2 on at

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I should have mentioned I attempted to use coalesce as well but ran into issues with the blank value trying to be converted:

coalesce(float(items('Apply_to_each')?['Measurement 1']), null)

InvalidTemplate. Unable to process template language expressions in action 'Update_a_row' inputs at line '0' and column '0': 'The template language function 'float' was invoked with a parameter that is not valid. The value cannot be converted to the target type.'.

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