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Remove specific row

Tala
7 - Meteor

Hi! My dataset includes a column that includes the fiscal year (e.g. "FY22", "FY23",... etc.) and another column that contains names. I want to delete the rows where the name exists in FY23 but not in any of the other years.

 

12 REPLIES 12
Felipe_Ribeir0
16 - Nebula

Hi @Tala 

 

Can you share a sample of your input/expected output?

Tala
7 - Meteor

I unfortunately can not. Is there any way you can help me without a sample?

Felipe_Ribeir0
16 - Nebula

Hi @Tala 

 

Take a look at the attached workflow and see if it make sense.

 

1-With summarize + filter you can remove names with only FY23

2-You can then join the data back by name

 

Screenshot 2023-08-08 142135.png

Tala
7 - Meteor

Thank you but I don't want to remove all names with FY23, I want to remove the row if the name exists in FY23 but does NOT exist in the other fiscal years

Felipe_Ribeir0
16 - Nebula

Hi @Tala 

 

I believe that this workflow is doing exactly what you need. With this summarize concatenate + filter, i am removing just names with ONLY FY23. Please open it and take a look.

Tala
7 - Meteor

I did and I understand what you're saying but what I'm trying to do is keep the names if they exist in FY23 and in any of the other years, I want to remove the name if it exists inn  FY23 but does NOT exist in other fiscal years. In other words I don't want to remove all names with FY23

Felipe_Ribeir0
16 - Nebula

I am not removing names if they exist in 23 + another year. As you can see, John is on the output.

 

names.png

 

Anyway, if this is not the case i am not really understanding. Using a fake input dataset like the one that i provided, can you mock a sample output dataset? So it will be more clear what you need.

Tala
7 - Meteor

Sorry for the late reply. Sure thing, "sample1" is a sample of the input and "sampleoutput" is a sample of the output

 

Tala
7 - Meteor

Oh I'm sorry, I just realized that I kept the end dates and submitted for period end as "2023" but the fiscal year isn't FY23, you can just ignore them and use the "Type" column which is the fiscal year

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