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Hello Qlik Community, I have a query please help,
my data is -
name - a,b,c,c,a,d,s,a,c,d,b,a,e,r,s,c,b,d
months - jan, feb, mar, apr, may, jun, jul, aug, sep, oct, nov, dec
I want to show those names which are appearing for more than 2 months
please help
You have multiple options. With only this data you could create a table in frontend with dimension "name" and measure count(distinct months). The names will be listed, and the number will show how many months they are listed in.
Yes, with concat(distinct months, ', ')
Sure, with a calculated dimension. Something like this:
if(match(months,1,2,3), 'Q1', if(match(months, 4,5,6), 'Q2', 'H2'))
Or you could combine pick and match pick(match(months, 'jan','feb','mar','apr',...), 'Q1', 'Q1', 'Q1', 'Q2',...)
You have multiple options. With only this data you could create a table in frontend with dimension "name" and measure count(distinct months). The names will be listed, and the number will show how many months they are listed in.
just an add on -
so can we add a column and can we show which the name of the months, like
a | 3 | jan, mar, sep
b | 2 | oct, dec
how can we show this?
please help
your solutions are really helpful
Yes, with concat(distinct months, ', ')
Thanks a lot sir, just one more requirement (sorry to extend the chat) -
can we create bucket of months in x axis like 1-2, 2-3, ... and then we can show counts of name like 10, 23, 4... in y axis? and so on..
just like we create buckets for age group
Sure, with a calculated dimension. Something like this:
if(match(months,1,2,3), 'Q1', if(match(months, 4,5,6), 'Q2', 'H2'))
Or you could combine pick and match pick(match(months, 'jan','feb','mar','apr',...), 'Q1', 'Q1', 'Q1', 'Q2',...)
Thanks sir I tried it worked,
is there any possibility to show which names are repeatedly showing up for the months? I am not able to think a way, could you please help me sir, I am not that expert in qlik sense, just started my journey.
I don’t understand your last question, please give an example of what the result should look like.