Grouping of column in a table in Qliksense

[sharankv]

Hi All,

I'm looking to group some columns into one section, the other columns into a different section in a straight table in Qliksense online version Apr 2020. The below is my data.

Products is the dimension and the rest of the columns are derived by using calculations.

Products	Total Orders	Total Ordered Qty	Total Sales	Total Profit	Total Customers	Avg. Age of Customers
Shoes	10	15	10000	2000	6	35
Clothes	40	100	15000	3000	23	33
Bags	15	15	9000	1800	15	28
Hat	8	14	4000	1000	6	26
Belts	10	15	7500	950	8	40
Totals	83	159	45500	8750	58	162

Now, I want to group the columns as shown below.

1. Total Orders and Total Ordered Qty under Orders Details

2. Total Sales and Total Profit under Revenue Details

3. Total Customers and Avg. Age of Customers under Customer Details

	Orders Details		Revenue Details		Customer Details
Products	Total Orders	Total Ordered Qty	Total Sales	Total Profit	Total Customers	Avg. Age of Customers
Shoes	10	15	10000	2000	6	35
Clothes	40	100	15000	3000	23	33
Bags	15	15	9000	1800	15	28
Hat	8	14	4000	1000	6	26
Belts	10	15	7500	950	8	40
Totals	83	159	45500	8750	58	162

Please guide me how to achieve this in the Qliksense online version Apr 2020.

Best Regards

[JordyWegman]

Hi,

You need to model your data a little bit different because you need another dimension with the totals.

Try to see if you can model it this way:

Load * Inline [
Products	,	Qty	,	Type	,	TotalType
Shoes	,	10	,	Total Orders	,	Order Details
Shoes	,	15	,	Total Ordered Qty	,	Order Details
Shoes	,	10000	,	Total Sales	,	Revenu Details
Shoes	,	2000	,	Total Profit	,	Revenu Details
Shoes	,	6	,	Total Customers	,	Customer Details
Shoes	,	35	,	Avg. Age of Customers	,	Customer Details
Clothes	,	40	,	Total Orders	,	Order Details
Clothes	,	100	,	Total Ordered Qty	,	Order Details
Clothes	,	15000	,	Total Sales	,	Revenu Details
Clothes	,	3000	,	Total Profit	,	Revenu Details
Clothes	,	23	,	Total Customers	,	Customer Details
Clothes	,	33	,	Avg. Age of Customers	,	Customer Details
Bags	,	15	,	Total Orders	,	Order Details
Bags	,	15	,	Total Ordered Qty	,	Order Details
Bags	,	9000	,	Total Sales	,	Revenu Details
Bags	,	1800	,	Total Profit	,	Revenu Details
Bags	,	15	,	Total Customers	,	Customer Details
Bags	,	28	,	Avg. Age of Customers	,	Customer Details
Hat	,	8	,	Total Orders	,	Order Details
Hat	,	14	,	Total Ordered Qty	,	Order Details
Hat	,	4000	,	Total Sales	,	Revenu Details
Hat	,	1000	,	Total Profit	,	Revenu Details
Hat	,	6	,	Total Customers	,	Customer Details
Hat	,	26	,	Avg. Age of Customers	,	Customer Details
Belts	,	10	,	Total Orders	,	Order Details
Belts	,	15	,	Total Ordered Qty	,	Order Details
Belts	,	7500	,	Total Sales	,	Revenu Details
Belts	,	950	,	Total Profit	,	Revenu Details
Belts	,	8	,	Total Customers	,	Customer Details
Belts	,	40	,	Avg. Age of Customers	,	Customer Details

];

 I've also attached the app for you, so you can check it your self.

Jordy

Climber

[sharankv]

Hi,

Thanks for replying and the solution suggested by you only works for small dataset like the sample I mentioned in this question. I'm talking this case for about millions of records where the grouping cannot be hardcoded in the load editor for each record. Considering the measures derived in the chart, please suggest a different approach for this requirement.

Appreciate your time and effort.

Thanks

Best regards

Sharan

[JordyWegman]

Hi Sharan,

I would need to know how you data structure looks to give a good advice. Could you share an example?

Jordy

Climber