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Re: single data extraction

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Franck_GENTILI1
6 - Interface Innovator
6 - Interface Innovator

Hello, I want to extract from the rollup field "noms des participants" only one of these data for which appear in the fields "Nom Prenon 1" "....2" "....3" "....4" .....

 

VUE https://airtable.com/shroD4pRoA52pXcg6

Thank you for your help

Franck from FRANCE

 

7 Replies 7
Sho
11 - Venus
11 - Venus

Hello!

Try this

REGEX_EXTRACT(text,"([^,]+,?){2}")

You can change the location by changing the number in the {2} part.

Hello, BUTthis is not working
thank you for your comeback https://airtable.com/shroD4pRoA52pXcg6
Franck
Hello, Thank you for your return unfortunately it does not work
thank you for your feedback https://airtable.com/shroD4pRoA52pXcg6 FRanck

I found the solution by adding "ARRAYJOIN" in the formula.
Modify location 1 ([^,]+,?){1}") to extract the rest of the string in the following fields.

 

The formula
REGEX_EXTRACT(ARRAYJOIN({Participant nom (from Imported table)}),"([^,]+,?){1}")

best regards

Hello
But here is the problem I encounter on fields that do not contain data

Ex
Lookup contains
ALLIE Pierre, BELUFFI Maeva, MUD Adrien

Formula 1 field 1 =ALLIE Pierre
Formula field 2 = BELUFFI Maeva
Formula field 3 = MUD Adrian
Formula field 4 = n
Formula field 5 = n

https://airtable.com/shroD4pRoA52pXcg6

Thank you for your feedback
Best regards
Frank

It was better this way
Change + to *

REGEX_EXTRACT(ARRAYJOIN({Participant nom (from Imported table)}),"([^,]*,?){1}")

 

MaisieRowe
4 - Data Explorer
4 - Data Explorer

Your pursuit of data extraction seems like a valuable endeavor. Extracting specific information from the "noms des participants" rollup field based on different fields like "Nom Prenom 1," "...2," "...3," and so on can be quite a task, but it's great that you're determined to tackle it.

Speaking of data extraction, it's interesting to note that platforms like Nannostomus provide accessible solutions for customers looking to simplify the process. Easy and accessible data extraction tools can save a lot of time and effort, making tasks like yours more efficient.


It's intriguing to think about the possibilities that such tools could bring to your data exploration project.