Here is a simple 3 column dataset showing Categories, Date and Value
Catagorie | Date | Value |
Fish | 08-12-2015 | 6 |
Crab | 05-12-2015 | 7 |
Crab | 04-12-2015 | 6 |
Bird | 27-11-2015 | 4 |
Snow | 25-11-2015 | 10 |
Cat | 21-11-2015 | 7 |
Dog | 12-11-2015 | 5 |
Dog | 28-10-2015 | 5 |
Fish | 12-10-2015 | 3 |
Bird | 11-10-2015 | 9 |
Dog | 22-09-2015 | 9 |
Crab | 17-08-2015 | 8 |
Cat | 11-08-2015 | 1 |
Fish | 20-07-2015 | 5 |
Crab | 03-07-2015 | 2 |
Fish | 02-06-2015 | 8 |
Fish | 26-05-2015 | 9 |
Dog | 14-05-2015 | 4 |
Snow | 07-05-2015 | 7 |
Bird | 03-05-2015 | 9 |
Cat | 20-04-2015 | 10 |
Cat | 15-04-2015 | 2 |
Snow | 13-04-2015 | 3 |
Crab | 29-03-2015 | 5 |
Crab | 23-03-2015 | 2 |
Bird | 14-03-2015 | 5 |
Cat | 14-03-2015 | 1 |
Dog | 26-02-2015 | 9 |
Fish | 16-02-2015 | 4 |
Fish | 08-02-2015 | 6 |
Bird | 18-01-2015 | 1 |
Snow | 06-01-2015 | 10 |
The objective is to compute category wise average of values against the 5 most recent dates. So the expected result is:
Categorie | Category wise average values on 5 most recent dates |
Bird | 5.60 |
Cat | 4.20 |
Crab | 5.60 |
Dog | 6.40 |
Fish | 6.20 |
Snow | 7.50 |
So for the Category of Fish (dates are sorted in descending order), the average should be 6.2 (average of 6,3,5,8,9)
Catagorie | Date | Value |
Fish | 08-12-2015 | 6 |
Fish | 12-10-2015 | 3 |
Fish | 20-07-2015 | 5 |
Fish | 02-06-2015 | 8 |
Fish | 26-05-2015 | 9 |
Fish | 16-02-2015 | 4 |
Fish | 08-02-2015 | 6 |
I have solved this problem using the PowerPivot. You may download my solution workbook from here.
Compute the average of values against the 5 most recent dates of each Category
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