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BahntjeRuben's avatar
BahntjeRuben
Regular Visitor
6 years ago
Solved

Column header and data in same row

I ve this type of records:

date=2020-07-28 time=11:35:29 user="user001" msg="Some String With Spaces" logid=100
date=2020-07-28 time=9:15:10 user="user002" msg="Another Text" logid=102

date=2020-07-27 time=10:55:23 user="user001" msg="The quick brown" logid=105

I want to split first line, and use the text before the = sign as headers and then split every row and use the text after the = sign as data. This is the expected result

date                  time         user         msg                                     logid

2020-07-28     11:35:29    user001     Some String With Spaces     100
2020-07-28     9:15:10      user002     Another Text                         102

2020-07-28     10:55:23    user001     The quick brown                   105

Ane idea how to resolve this?

 

 

  • BahntjeRuben 

    I saved your data as a text file and imported to into PBI, and did the transformation. Please check the steps and codes. This is dynamics, any # of columns and rows will work

     

    You can download the file: HERE

     



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2 Replies

  • BahntjeRuben 

    I saved your data as a text file and imported to into PBI, and did the transformation. Please check the steps and codes. This is dynamics, any # of columns and rows will work

     

    You can download the file: HERE

     



    ________________________

    Did I answer your question? Mark this post as a solution, this will help others!.

    Click on the Thumbs-Up icon on the right if you like this reply 🙂

    YouTube, LinkedIn


  • Anonymous's avatar
    Anonymous
    Not applicable

    Must be an easier way than this but you could use Power Query:

     

    I'm presuming "date=2020-07-28 time=11:35:29 user="user001" msg="Some String With Spaces" logid=100" is in one cell? if so, 

     

    Split by delimited "="

    Then split "time", "user", "msg" and "logid" by delimited by Right most "Space". 

     

    The just remove the redundant columns and rename the remaining.