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i have table like below and requirement is,
need to calculate the CategoryID for each Id whose ActiveFlag =1 and latest statflag is 0 and old statflag is 1
ID | CategoryID | Activeflag | statflag | calenderDate | Count |
a123 | 1 | 1 | 0 | 4/14/2021 | 1 |
a123 | 2 | 1 | 1 | 4/14/2021 | 0 |
a123 | 3 | 1 | 1 | 4/14/2021 | 0 |
a123 | 4 | 1 | 1 | 4/14/2021 | 0 |
b233 | 1 | 1 | 0 | 1/1/2021 | 0 |
b233 | 2 | 1 | 0 | 1/1/2021 | 1 |
b233 | 3 | 1 | 1 | 1/1/2021 | 0 |
c233 | 1 | 1 | 1 | 1/1/2021 | 0 |
e343 | 2 | 1 | 1 | 2/6/2021 | 0 |
f234 | 2 | 1 | 0 | 2/6/2021 | 0 |
a123 | 1 | 1 | 1 | 2/6/2021 | 0 |
b233 | 2 | 1 | 1 | 2/6/2021 | 0 |
Solved! Go to Solution.
@Naresh91 , Try new column like
New column =
var _date = sumx(filter(Table, [ID] = earlier([ID]) && [CategoryID] =earlier([CategoryID]) && [calenderDate] <earlier([calenderDate])),[calenderDate])
var _statflag = sumx(filter(Table, [ID] = earlier([ID]) && [CategoryID] =earlier([CategoryID]) && [calenderDate] =_date),[statflag])
return
if([statflag] =0 && _statflag= 1, 1,0)
@Naresh91 , Not very clear, can explain the output with examples
Hi @amitchandak ,
from the above data "a123" have statflag =1 for CategoryID 1 on "2/6/2021"
and "a123" have statflag =0 for CategoryID 1 on "4/14/2021"
so it will consider as Lost ID and so count will be 1
similar way for "b233" have statflag =1 for CategoryID 2 on "2/6/2021"
and "b233" have statflag =0 for CategoryID 2 on "1/1/2021"
so here also count is 1
so like this for the above data Lost count will be 2 as "a123" and "b233" lost their one CatogeryId
@Naresh91 , Try new column like
New column =
var _date = sumx(filter(Table, [ID] = earlier([ID]) && [CategoryID] =earlier([CategoryID]) && [calenderDate] <earlier([calenderDate])),[calenderDate])
var _statflag = sumx(filter(Table, [ID] = earlier([ID]) && [CategoryID] =earlier([CategoryID]) && [calenderDate] =_date),[statflag])
return
if([statflag] =0 && _statflag= 1, 1,0)
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