Forum Discussion
Calculated column RANKX with multiple columns
Hi Anonymous
The problem is because of that change you did in the code, remove that SUM from line 4 in the code (based on the screenshot you sent)
try this and don't change anything (copy past):
Rankx = RANKX ( FILTER ( ALL ( 'Sales' ), [Customer] = EARLIER ( 'Sales'[Customer] ) ), [Sales], , DESC, DENSE )Output:
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Appreciate your Kudos!!
LinkedIn: www.linkedin.com/in/vahid-dm/
Hi VahidDM
It works!! You have helped to save my potential endless hours on trying to solve this!
I will go ahead and apply the same to my real case and hopefully it does not turn complicated!
Thank you so much!! Appreciate it!😀
Hi VahidDM
Sorry to bother you again. I have additional question on the above topic.
I use the Summarize function to create a table to summarise customer, product, sales from another data table, before I rankx them.
If I want to add additional columns such as "Month Category" in my summarised table, how will it change the RANKX formula above? I want to achieve the same result as before, i.e. rank top products within customer group, regardless of month category. The month category is for other calculation purpose.
I tried to use the sample dataset below, it works but when i apply it to my real case scenario, the RANKX does not seem to work. The RankX was affected by the month category. I am not sure which part I am doing wrong. Please see the second screenshot below (based on real case scenario but confidential info is modified).
Appreciate your help! Thank you!
| Customer | Product | Month Category | Sales |
| Ally | Product A | M-1 | 1,000 |
| Ally | Product D | M-1 | 200 |
| Ally | Product A | M-2 | 1,000 |
| Ally | Product B | M-2 | 300 |
| Ally | Product B | M-3 | 300 |
| Ally | Product C | M-4 | 50 |
| Jason | Product A | M-2 | 1,000 |
| Jason | Product A | M-2 | 1,000 |
| Jason | Product A | M-3 | 1,000 |
| Jason | Product A | M-3 | 1,000 |
| Jason | Product B | M-4 | 200 |
| Jason | Product C | M-4 | 100 |
| Jason | Product D | M-5 | 60 |