Hello
I wanted to check what is the most efficient way to lookup through multiple columns with similar field names.
In the example file, I want to only output dates if DTn=1. Keep in mind in this file n is from 1-30 so there are about this many date type columns. Hence I want to avoid using the formula tool. The output column shows what the output should look like
ID | DT | Date | DT2 | Date2 | DT3 | Date3 | DTn | Daten | Output |
1 | 1 | 01/01/2018 | 01/01/2018 | ||||||
2 | 1 | 02/01/2018 | 02/01/2018 | ||||||
3 | 1 | 03/01/2018 | 2 | 01/01/2018 | 03/01/2018 | ||||
4 | 1 | 04/01/2018 | 2 | 02/01/2018 | 04/01/2018 | ||||
5 | 1 | 05/01/2018 | 2 | 03/01/2018 | 05/01/2018 | ||||
6 | 1 | 01/01/2018 | 01/01/2018 | ||||||
7 | 1 | 02/01/2018 | 02/01/2018 | ||||||
8 | 1 | 03/01/2018 | 03/01/2018 | ||||||
9 | 1 | 04/01/2018 | 04/01/2018 | ||||||
10 | 1 | 05/01/2018 | 05/01/2018 | ||||||
11 | 1 | 06/01/2018 | 06/01/2018 | ||||||
12 | 1 | 01/01/2018 | 01/01/2018 | ||||||
13 | 2 | 01/01/2018 | 1 | 02/01/2018 | 02/01/2018 | ||||
14 | 2 | 02/01/2018 | 1 | 03/01/2018 | 03/01/2018 | ||||
15 | 2 | 03/01/2018 | 1 | 04/01/2018 | 04/01/2018 | ||||
16 | 2 | 04/01/2018 | 1 | 05/01/2018 | 05/01/2018 | ||||
17 | 2 | 05/01/2018 | 1 | 06/01/2018 | 06/01/2018 |
Solved! Go to Solution.
Hello Aldona
The trick here is create 2 separate transposed lists, one with the DATE* column names/values and one with the DT* names/values. You then join them up on ID and column number. This gives you one list with 3 fields ID, Date and DateFlag that a single Formula tool can process. The Summarize compresses this list back to the original 17 rows with the Output column. Join back to the original on ID if required
Dan
@danilang worked like magic:) thanks a lot!
New marketing slogan for Alteryx. Alteryx...I can't believe it's not magic!
Dan
Yes! It is such a flexible tool. I am also impressed with how you came up with this, thanks again!
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