Forum Discussion
Tricky Aggregation - Matrix like with nulls
Hi Anonymous ,
I would like to get count of non null names per each i.e.
BU1 5 6 3
BU2 4 4 5
BU3
BU4
BU5
Skill 1 Skill 2 Skill 3
But on the graph...
for example one as above on screenshot but with the colour dots representing skill and cound and X axis being BU1...5
I am not very clear about your requirement. Please provide more detailed description about the desired output. What does 5, 6, 3 in the first "BU1" row represent? And What does Skill mentioned here mean?
Since you said "I can analyse 1 BU and see count of names per category. But I can't seem to get them all at one graph.", maybe you could try to Unpivot source table to convert "bu1", "bu2", "bu3", "bu4" and "bu5" from column headers into a single column.
Regards,
Yuliana Gu
3 Replies
Hi
My data is as per the picture below.
5 Columns "BUx" with 3 possible categories (and nulls)
I can analyse 1 BU and see the count of names per category.
But I can't seem to get them all at one graph.
All graphs when adding rows/columns turn on drill function.
I would like to get count of non null names per each i.e.
BU1 5 6 3
BU2 4 4 5
BU3
BU4
BU5
Skill 1 Skill 2 Skill 3
But on the graph...
for example one as above on screenshot but with the colour dots representing skill and count and X-axis being BU1...5
Hope thats clear
Regards
Dom
Hi Anonymous ,
I would like to get count of non null names per each i.e.
BU1 5 6 3
BU2 4 4 5
BU3
BU4
BU5
Skill 1 Skill 2 Skill 3
But on the graph...
for example one as above on screenshot but with the colour dots representing skill and cound and X axis being BU1...5
I am not very clear about your requirement. Please provide more detailed description about the desired output. What does 5, 6, 3 in the first "BU1" row represent? And What does Skill mentioned here mean?
Since you said "I can analyse 1 BU and see count of names per category. But I can't seem to get them all at one graph.", maybe you could try to Unpivot source table to convert "bu1", "bu2", "bu3", "bu4" and "bu5" from column headers into a single column.
Regards,
Yuliana Gu