March 31 - April 2, 2025, in Las Vegas, Nevada. Use code MSCUST for a $150 discount! Early bird discount ends December 31.
Register NowBe one of the first to start using Fabric Databases. View on-demand sessions with database experts and the Microsoft product team to learn just how easy it is to get started. Watch now
I have a table imported daily from the web and it contains two columns , one is name and address and the other is just address
I need to extract just the name from the address , by a formula to remove what is in the address column from the name address column
Name Address Addresss
John Smith Johns Beach Bar , Miami , US Johns Beach Bar , Miami , US
Mike Brown Mikes Beach Bar , Florida , US Mikes Beach Bar , Florida , US
I need a Name Column adding which just shows the name
John Smith
Mike Brown
I need to do this in query editor please
Solved! Go to Solution.
HI @Pandadev,
Did you mean to remove the 'text string' stored in the 'address' column from the 'name address' field? If that is the case, you can create a calculated column with SUBSTITUTE function:
Replaced = SUBSTITUTE([Name Address],[Addresss],"")
Regards,
Xiaoxin Sheng
HI @Pandadev,
Did you mean to remove the 'text string' stored in the 'address' column from the 'name address' field? If that is the case, you can create a calculated column with SUBSTITUTE function:
Replaced = SUBSTITUTE([Name Address],[Addresss],"")
Regards,
Xiaoxin Sheng
@Pandadev you can make use of below measure
@Pandadev , is that name will be the first two words?
unfortunately not , sometimes it can be like
Smith, Arnold James
John & Mary Smith
March 31 - April 2, 2025, in Las Vegas, Nevada. Use code MSCUST for a $150 discount!
Your insights matter. That’s why we created a quick survey to learn about your experience finding answers to technical questions.
Arun Ulag shares exciting details about the Microsoft Fabric Conference 2025, which will be held in Las Vegas, NV.
User | Count |
---|---|
133 | |
90 | |
88 | |
64 | |
58 |
User | Count |
---|---|
202 | |
137 | |
106 | |
70 | |
68 |