You have the following set of orders for two months, and you are interested in identifying the set of colors that have been sold for each product for each month and the total quantity of product sold for each month.
Source:
| OrderId | Date | Item | Qty | Color |
|---|---|---|---|---|
| 1001 | 1/15/15 | Pants | 1 | red |
| 1002 | 1/15/15 | Shirt | 2 | green |
| 1003 | 1/15/15 | Hat | 3 | blue |
| 1004 | 1/16/15 | Shirt | 4 | yellow |
| 1005 | 1/16/15 | Hat | 5 | red |
| 1006 | 1/20/15 | Pants | 6 | green |
| 1007 | 1/15/15 | Hat | 7 | blue |
| 1008 | 4/15/15 | Shirt | 8 | yellow |
| 1009 | 4/15/15 | Shoes | 9 | brown |
| 1010 | 4/16/15 | Pants | 1 | red |
| 1011 | 4/16/15 | Hat | 2 | green |
| 1012 | 4/16/15 | Shirt | 3 | blue |
| 1013 | 4/20/15 | Shoes | 4 | black |
| 1014 | 4/20/15 | Hat | 5 | blue |
| 1015 | 4/20/15 | Pants | 6 | black |
Transform:
To track by month, you need a column containing the month value extracted from the date:
set col:Date value:DATEFORMAT(Date, 'MMM yyyy')
You can aggregate the data in your dataset, grouped by the reformattedDate values, and apply the LIST function to the Color column. In the same aggregation, you can include a summation function for the Qty column:
pivot value: LIST(Color, 1000) SUM(Qty) group: Date limit:1
Results:| Date | list_Color | sum_Qty |
|---|---|---|
| Jan 2015 | ["green","blue","blue","red","green","red","yellow"] | 28 |
| Apr 2015 | 38 |
If needed, you can unpack the list array data using the following:
unnest col:list_Color
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