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On Regular Expression (Regex).. and Alteryx

This post was originally published on The Data School blog between 2018 and July 2025, before our program was renamed to MIP’s Analytics Career Accelerator. References throughout this article to “The Data School” or “DS” all refer to what is now MIP’s Analytics Career Accelerator. The program, its people, and its commitment to launching outstanding analytics careers remain the same – just under a new name.

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Seriously, Regular Expression (Regex) almost made me want to quit Alteryx.

Imagine you are in a huge library and looking for a book, the first person you might think of is the librarian. To data analysts, regex is the librarian, and data is the book they are looking for.

 

But this librarian doesn’t speak English!!!

 

He/She (I haven’t figured out yet) speaks:

….[(d{7})(.*)s((d{4}))sCAT:(.*?)sPUB:(.*?)s$(.*?)…

 

 

Apparently, this librarian doesn’t like chit-chat.

Apart from all the nonsense, Regex is somewhat a lovely person, because:

  1. The library never closes at 6pm, neither Regex
  2. You can meet Regex anywhere as long as you have a computer
  3. You never need to wait for his/her service

 

My Data School colleague clearly knows how to talk to Regex, and she showed me how with a book called ‘White Space’:

([A-Z].+?[a-z].+)([A-Z].)

OK, THIS IS MAGIC.

 

I also discovered that Alteryx thought about the communication problem and put a dictionary on the desk:

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Not sure if this is a good thing or not, but Regex is never in a rush.

Maybe this is something we should all learn from Regex. Patience, and never giving up on looking for a book.

 

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