--分組統計
select a.emp_id,b.emp_name,a.dept_no,a.bb_no,a.xh,a.idno,a.emp_no,a.beg_date,a.over_date,a.basesal
from hrsys.dbo.empbasesal a left join hrsys.dbo.employee b on a.emp_id=b.emp_id
where basesal>4000
order by a.emp_id,basesal
--第一種top n 分組統計
select a.emp_id,b.emp_name,a.dept_no,a.bb_no,a.xh,a.idno,a.emp_no,a.beg_date,a.over_date,a.basesal
from hrsys.dbo.empbasesal a left join hrsys.dbo.employee b on a.emp_id=b.emp_id
where (select count(1) from hrsys.dbo.empbasesal
where emp_id=a.emp_id and basesal>=a.basesal)<=3
and basesal>4000
order by a.emp_id,basesal desc
--第二種 top ｎ 分組統計
select a.emp_id,b.emp_name,a.dept_no,a.bb_no,a.xh,a.idno,a.emp_no,a.beg_date,a.over_date,a.basesal
from hrsys.dbo.empbasesal a left join hrsys.dbo.employee b on a.emp_id=b.emp_id
where basesal in (select top 3 basesal from hrsys.dbo.empbasesal
where emp_id=a.emp_id order by basesal desc )
and basesal>4000
order by a.emp_id,basesal
--分組統計
select a.emp_id,b.emp_name,a.dept_no,a.bb_no,a.xh,a.idno,a.emp_no,a.beg_date,a.over_date,a.basesal
from hrsys.dbo.empbasesal a left join hrsys.dbo.employee b on a.emp_id=b.emp_id
where basesal>4000
order by a.emp_id,basesal
--第一種top n 分組統計
select a.emp_id,b.emp_name,a.dept_no,a.bb_no,a.xh,a.idno,a.emp_no,a.beg_date,a.over_date,a.basesal
from hrsys.dbo.empbasesal a left join hrsys.dbo.employee b on a.emp_id=b.emp_id
where (select count(1) from hrsys.dbo.empbasesal
where emp_id=a.emp_id and basesal>=a.basesal)<=3
and basesal>4000
order by a.emp_id,basesal desc
--第二種 top ｎ 分組統計
select a.emp_id,b.emp_name,a.dept_no,a.bb_no,a.xh,a.idno,a.emp_no,a.beg_date,a.over_date,a.basesal
from hrsys.dbo.empbasesal a left join hrsys.dbo.employee b on a.emp_id=b.emp_id
where basesal in (select top 3 basesal from hrsys.dbo.empbasesal
where emp_id=a.emp_id order by basesal desc )
and basesal>4000
order by a.emp_id,basesal
linq 分組統計
好久不寫東東了，最近做linq分組統計的時候有點麻煩，用了一天時間才都到自己想要的效果，以下是entity framework的分組統計 iqueryablemm null entity.class1 ma new entity.class1 mm from t in context.subject...
ListMultimap分組統計
背景 分時段統計賬單報表，時間間隔為 30分鐘，1小時，2小時，4小時 對應時段為 00 00 00 30,00 30 01 00,01 00 01 30 00 00 01 00,01 00 02 00,02 00 03 00 00 00 02 00,02 00 04 00,04 00 06 00 ...
pandas groupby, agg分組統計
分組統計是資料分析中較為複雜的一種操作，但是使用起來非常有用，能避開大量的迴圈等等。dataframe.groupby by none axis 0 level none as index true sort true group keys true squeeze false kwargs 對da...