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Asked: 2026-06-07T21:41:18+00:00

I have a table like this: | prodID | date | perm ——————————— |200

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I have a table like this:

| prodID  | date     |  perm
---------------------------------   
|200      |8/7/2011  | 81.742 
|200      |8/7/2011  | 81.644
|200      |8/7/2011  | 81.302
|200      |8/7/2011  | 81.057
|201      |8/7/2011  | 80.932
|201      |8/7/2011  | 80.839
|201      |8/7/2011  | 80.622
|201      |8/7/2011  | 80.557
|201      |8/7/2011  | 80.541

(except a bit bigger)
Breakdown of what happens: I want to take the average of the top 10 values (and bottom 10 values) where a prodid = somevalue in this case 200.

Code:

declare @myid int
set @myid = 200

;with high as  --top ten average
(
 select prodid, CONVERT(CHAR(10),  DATEADD(DAY, AVG(DATEDIFF(DAY, 0, CONVERT    
(SMALLDATETIME, [date]))), 0),     101) as date, max(perm)as max_perm, avg(perm) 
as   
high_perm from   
( select prodid, date, perm, 
 row_number() over(partition by date order by perm desc) as nt    
 from live_pilot_plant
 where prodid = @myid) as T 
 where nt <= 10
 group by prodid
),
low as   -- bottom ten average
(
select prodid, CONVERT(CHAR(10),  DATEADD(DAY, AVG(DATEDIFF(DAY, 0, CONVERT    
(SMALLDATETIME, [date]))), 0),101) as date, min(perm) as min_perm, avg(perm) 
as low_perm  from   
( select prodid, date, perm,  
  row_number() over(partition by date order by perm asc) as nt    
  from live_pilot_plant
  where prodid = @myid) as T 
  where nt <= 10
  group by prodid
)

select l.prodid, l.date, l.low_perm as low_avg, m.high_perm as high_avg,
(m.high_perm -    l.low_perm) as delta
from low l
left outer join high m
on l.prodid = m.prodid

Which produces something like this:

|  prodID  |   date     |  low_avg   |  high_avg  |  delta   |
|   200    | 08/07/2011 |   68.752   |  79.1976   |  10.444  |

THESE NUMBERS ARE NOT ACCURATE —

This is all good and dandy – except not very versitle. I mean there are a lot of prodID, and to do one this based on prodID is too slow. How can I get the low_avg and the high_avg based on date (group by prodID)

Something like this:

| date       | prodID  | low_avg  | high_avg  |  delta  |
| 08/07/2011 | 200     |  60      |  80       |  20     |
| 08/07/2011 | 201     |  70      |  100      | 100     |

NOTE: You might have noticed a crazy convert infront of date. The reason is that some prodID overlap dates ie. 200 on 8/7/2011, and 8/8/2011, and I need to average the date (which is a varchar). So something like if there were 100 rows with 8/7/2011, and then 9 rows with 8/8/2011, the final query would produce the date being as /8/7/2011

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1 Answer

  1. Editorial Team

    The following query does it for all products at once:

    select lpp.prod_id, lpp.date,
       AVG(case when seqnum_asc <= 10 then perm end) as avg_bottom10,
       AVG(case when seqnum_desc <= 10 then perm end) as avg_top10,
       (AVG(case when seqnum_desc <= 10 then perm end) - AVG(case when seqnum_asc <= 10 then perm end)) as delta
from (select lpp.*,
             ROW_NUMBER() over (partition by prodid, date order by perm) as seqnum_asc,
             ROW_NUMBER() over (partition by prodid, date order by perm desc) as seqnum_desc
      from live_pilot_plan lpp
     ) lpp
group by lpp.prod_id, lpp.ate
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