The trick is to join your table back to it self as shown below. myTable as A
will read only the Good
rows and myTable as B
will read only the Bad
rows. Those rows then get joined into a signle row based on date
.
select
a.date
,a.count as Good_count
,b.count as bad_count
,a.count-b.count as diff_count
from myTable as a
inner join myTable as b
on a.date = b.date and b.type = 'Bad'
where a.type = 'Good'
Output returned:
DATE GOOD_COUNT BAD_COUNT DIFF_COUNT
March, 03 2014 00:00:00+0000 100 15 85
March, 04 2014 00:00:00+0000 120 10 110
Another aproach would be to use Group by
instead of the inner join
:
select
a.date
,sum(case when type = 'Good' then a.count else 0 end) as Good_count
,sum(case when type = 'Bad' then a.count else 0 end) as Bad_count
,sum(case when type = 'Good' then a.count else 0 end) -
sum(case when type = 'Bad' then a.count else 0 end) as Diff_count
from myTable as a
group by a.date
order by a.date
Both approaches produce the same result.