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I have a data file that contains the following data records:

 

Date:  28/06/22 Time:  18:40:40 Version: 9.10

Events: Y Relays: I Evlog: Y Buftyp: C Bufsiz:  829

Cond:  100 100 100 100 100 100 100 100

Ch: 1  En: Y  Ut: 30  Dt: 30  Uc: 3999  Dc: 995  Sa: 31  Wa: 31

Ch: 2  En: Y  Ut: 25  Dt: 25  Uc:  3  Dc:  1  Sa: 57  Wa: 57

Ch: 3  En: N  Ut: 30  Dt: 30  Uc:  0  Dc:  0  Sa: 37  Wa: 37

Ch: 4  En: Y  Ut: 30  Dt: 30  Uc: 2790  Dc: 439  Sa: 33  Wa: 33

24/06/22 20:08:47 100 4 U 033 

24/06/22 20:08:57 100 4 U 040 

24/06/22 20:34:23 100 4 U 042 

24/06/22 20:34:35 100 4 U 037 

 

How do I split this data file into two separate datasets e.g.

 

Dataset #1:

Date:  28/06/22 Time:  18:40:40 Version: 9.10

Events: Y Relays: I Evlog: Y Buftyp: C Bufsiz:  829

Cond:  100 100 100 100 100 100 100 100

Ch: 1  En: Y  Ut: 30  Dt: 30  Uc: 3999  Dc: 995  Sa: 31  Wa: 31

Ch: 2  En: Y  Ut: 25  Dt: 25  Uc:  3  Dc:  1  Sa: 57  Wa: 57

Ch: 3  En: N  Ut: 30  Dt: 30  Uc:  0  Dc:  0  Sa: 37  Wa: 37

Ch: 4  En: Y  Ut: 30  Dt: 30  Uc: 2790  Dc: 439  Sa: 33  Wa: 33

 

Dataset #2:

24/06/22 20:08:47 100 4 U 033 

24/06/22 20:08:57 100 4 U 040 

24/06/22 20:34:23 100 4 U 042 

24/06/22 20:34:35 100 4 U 037 

 

Please advise.

One way to do this is to read the file as text. Then use anything you need to determine where the seperation lies. Something like text_line_data contains / or if the header is always 7 rows, the rownumber. Then write out to two different files. If you use a FeatureWriter and a FeatureReader, you will be able to read the second part with a csv reader. As an alternative you can skip the write and read csv step by splitting the columns using an attributesplitter.

One way to do this is to read the file as text. Then use anything you need to determine where the seperation lies. Something like text_line_data contains / or if the header is always 7 rows, the rownumber. Then write out to two different files. If you use a FeatureWriter and a FeatureReader, you will be able to read the second part with a csv reader. As an alternative you can skip the write and read csv step by splitting the columns using an attributesplitter.

Something like this.

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