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Calculated grouping
Hi Experts,
I have year with some measures, and I want to categorize the measures as a header.
input:
Year | Measure_1 | Measure_2 | Measure_3 | Measure_4 | Measure_5 |
---|---|---|---|---|---|
2010 | 100 | 0 | 50 | 110 | 70 |
2011 | 200 | 100 | 112 | 90 | 23 |
2012 | 0 | 115 | 14 | 0 | 323 |
2014 | 30 | 250 | 60 | 0 | 0 |
expecting output:
hi
please help in achieving this.
Accepted Solutions

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No Problem.
For example below data, we have one dimension. That is Year. so that we have used Crosstable (Measure, Sales, 1) LOAD * RESIDENT Data_Temp;
If you have Year,Dim1,dim2,Dim3 , use Crosstable (Measure, Sales, 4) LOAD * RESIDENT Data_Temp;
Hope you got it.
Data_Temp:
LOAD * INLINE [
Year,Measure_1,Measure_2,Measure_3,Measure_4,Measure_5
2010,100,0,50,110,70
2011,200,100,112,90,23
2012,0,115,14,0,323
2014,30,250,60,0,0
];

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Hi,
table:
load
Year,
Measure1,
Measure2,
'IT GROUP' as Group
FROM...
join(table) //Or just Join
load
Year,
Measure3,
Measure4,
Measure5,
'HR GROUP' as Group
FROM...

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Like this?

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yes , sunn. This is what I’m lookin. I got the result. But ehen I export the data to exce, I’m getting group names on top of each measure. Like below
Grouping | HR Group | HR Group | HR Group | IT Group | IT Group | |
---|---|---|---|---|---|---|
Year | Measure | Measure_3 | Measure_4 | Measure_5 | Measure_1 | Measure_2 |
2010 | ||||||
2011 | ||||||
2012 | ||||||
2015 |
I Want to merge this group.

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Hi
You can achieve your requirement like this.
Please check this.
Data_Temp:
LOAD * INLINE [
Year,Measure_1,Measure_2,Measure_3,Measure_4,Measure_5
2010,100,0,50,110,70
2011,200,100,112,90,23
2012,0,115,14,0,323
2014,30,250,60,0,0
];
Data:
Crosstable (Measure, Sales, 1) LOAD * RESIDENT Data_Temp;
Left join
LOAD *,if(WildMatch(Measure,'Measure_1','Measure_2'),'IT Group',
if(WildMatch(Measure,'Measure_3','Measure_4','Measure_5'),'HR Group')) as Group Resident Data;
drop table Data_Temp;

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tthanks for the reply. I can achieve this with sample data. But I have 120 measures under one group.
appreciate if any one provide solution

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No Problem.
For example below data, we have one dimension. That is Year. so that we have used Crosstable (Measure, Sales, 1) LOAD * RESIDENT Data_Temp;
If you have Year,Dim1,dim2,Dim3 , use Crosstable (Measure, Sales, 4) LOAD * RESIDENT Data_Temp;
Hope you got it.
Data_Temp:
LOAD * INLINE [
Year,Measure_1,Measure_2,Measure_3,Measure_4,Measure_5
2010,100,0,50,110,70
2011,200,100,112,90,23
2012,0,115,14,0,323
2014,30,250,60,0,0
];
