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I have a simple dataset like below:
type | month | year | value |
A | Jan | 2017 | 20 |
A | Feb | 2017 | 2 |
A | Mar | 2017 | 14 |
A | Jan | 2018 | 9 |
A | Feb | 2018 | 30 |
A | Mar | 2018 | 3 |
A | Jan | 2019 | 17 |
A | Feb | 2019 | 15 |
A | Mar | 2019 | 30 |
B | Jan | 2017 | 9 |
B | Feb | 2017 | 9 |
B | Mar | 2017 | 19 |
B | Jan | 2018 | 24 |
B | Feb | 2018 | 17 |
B | Mar | 2018 | 17 |
B | Jan | 2019 | 20 |
B | Feb | 2019 | 9 |
B | Mar | 2019 | 19 |
C | Jan | 2017 | 26 |
C | Feb | 2017 | 24 |
C | Mar | 2017 | 28 |
C | Jan | 2018 | 29 |
C | Feb | 2018 | 10 |
C | Mar | 2018 | 18 |
C | Jan | 2019 | 29 |
C | Feb | 2019 | 16 |
C | Mar | 2019 | 14 |
Goal is to create two MIN/MAX measures that capture the MIN/MAX of sum of any combination (determined by slicer) of the types (A, B and C) for each month across the years so that i can create a seasonal chart like below (sum of A & B), with the MIN/MAX measures set as Upper bound & Lower bound in Error Bars:
Thanks very much in advance!
New question arises.... how do I hide e.g. 2017 from legends and yet still display the same MIN/MAX like the below?
sum_value = CALCULATE ( SUM( table[value] ), ALLSELECTED( table[type] ) )
max_of_sum = MAXX( ALLSELECTED( table[type], table[year] ), table[sum_value] )
min_of_sum = MINX( ALLSELECTED( table[type], table[year] ), table[sum_value] )
Have played around a bit, the above seems to work - would love some confirmation here?
Thanks vm
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