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Pandadev
Post Prodigy
Post Prodigy

Remove text from column based on another column in same table

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

1 ACCEPTED SOLUTION
v-shex-msft
Community Support
Community Support

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],"")

9.png

Regards,

Xiaoxin Sheng

Community Support Team _ Xiaoxin
If this post helps, please consider accept as solution to help other members find it more quickly.

View solution in original post

4 REPLIES 4
v-shex-msft
Community Support
Community Support

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],"")

9.png

Regards,

Xiaoxin Sheng

Community Support Team _ Xiaoxin
If this post helps, please consider accept as solution to help other members find it more quickly.
Anonymous
Not applicable


@Pandadev  you can make use of below measure

extract name = LEFT('Table'[Name Address  ],LEN('Table'[Name Address  ])-LEN('Table'[Addresss])))

Regards
Husna
amitchandak
Super User
Super User

@Pandadev , is that name will be the first two words?

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unfortunately not , sometimes it can be like

Smith, Arnold James

John & Mary Smith

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