Hi @sbatra116!
Will you please provide more details or a sample of your data?
A formula like this might work in the Filter tool, depending on the structure of your data:
[AgeCondition] > 0
Can't really tell too much about the requirement because of the lack of detail in your post. However, if this condition has a need to change dynamically then you may want to explore the dynamic replace tool. I've attached a small sample workflow and you would simply add a filter afterwards to remove nulls:
My bad. I should have written more detail. @DataNath @ddiesel
Update ---
Spreadsheet data
ID | Name | Age_Business_Days |
1 | Test1 | 10 |
2 | Test2 | 0 |
3 | Test3 | 3 |
Now the condition are stored in a different source (can be spreadsheet or db table)
column1 | column2 | column3 |
Age_Business_Days | testdata | >0 |
In order to filter the spreadsheet data ; i'll be creating condition run time using column 1 and column 3 from the second table.
condition: (Age_Business_Days > 0)
if the second source gets updated, my condition should automatically update in the workflow depending upon the columns mentioned in second table.
Hi @sbatra116!
Let's give this a try...
Is the operator in the condition always "greater than"? If there are other operators such as "less than" or "equal", we will need to add a bit more logic.
Please let us know if this works.
Thanks,
Deb
P.S. Just saw @binuacs solution... very slick! I did not think to use the Dynamic Replace tool.
I like the approach here but how to handle once the condition changes (it can be either equal, greater or less than)
Hi binuacs
Like the way you used the dynamic replace tool. But i'm not getting the result i want.
Spreadsheet data
ID | Name | Age_Business_Days |
1 | Test1 | 10 |
2 | Test2 | 0 |
3 | Test3 | 3 |
condition
column1 | column3 |
Age_Business_Days | >0 |
result should be
ID | Name | Age_Business_Days |
1 | Test1 | 10 |
3 | Test3 | 3 |
Hi again @sbatra116!
I still think @binuacs solution is more efficient, but here is how I would modify the logic in the workflow I provided.
Instead of cleansing the operator from the condition, both operator and value are joined to your data. A nested conditional statement in the filter tool is setup to handle the three different expected operators: > = <