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Hello!
I`m connecting to folder which contains multiply different .xlsx files. Every filename somewhere contains 20 digit account number. At first I need extract account number, recive some number based data from 'dimension table' and make some filtering. After that I want expand 'content' and start working with data inside those files.
That is how my folder looks:
I was unable to get steady result with 'column from examples' so I use small Python code to extract account numbers in my dataset.
# 'dataset' содержит входные данные для этого сценария
regex = r'(\d{20})'
dataset['Номер расчетного счета'] = dataset['Name'].str.extract(regex)
Code works well and returns dataset but in 'Value.Content' instead of previous content I recieve 'System.Byte' value.
It is important for me to make some filtering on regex`ed dataset before expanding 'content'. Is it possible to save all content in one query after regex?
P.S. There is workaround with doubling and merging queries but I would like to stay in one query.
Thank you!
Solved! Go to Solution.
Hi @HeliosOne ,
to my knowledge, these "nested" columns will not survive a passage through Python.
So you have to parse out /expand the columns you need later before applying the Python-Script.
Imke Feldmann (The BIccountant)
If you liked my solution, please give it a thumbs up. And if I did answer your question, please mark this post as a solution. Thanks!
How to integrate M-code into your solution -- How to get your questions answered quickly -- How to provide sample data -- Check out more PBI- learning resources here -- Performance Tipps for M-queries
Hi @HeliosOne ,
to my knowledge, these "nested" columns will not survive a passage through Python.
So you have to parse out /expand the columns you need later before applying the Python-Script.
Imke Feldmann (The BIccountant)
If you liked my solution, please give it a thumbs up. And if I did answer your question, please mark this post as a solution. Thanks!
How to integrate M-code into your solution -- How to get your questions answered quickly -- How to provide sample data -- Check out more PBI- learning resources here -- Performance Tipps for M-queries
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