group by

sym = `C`MS`MS`MS`IBM`IBM`C`C`C$SYMBOL
price= 49.6 29.46 29.52 30.02 174.97 175.23 50.76 50.32 51.29
qty = 2200 1900 2100 3200 6800 5400 1300 2500 8800
timestamp = [09:34:07,09:36:42,09:36:51,09:36:59,09:32:47,09:35:26,09:34:16,09:34:26,09:38:12]
t1 = table(timestamp, sym, qty, price);

t1;

select count(sym) as counts from t1 group by sym;

和 top 子句一起使用：

select top 2:3 count(sym) as counts from t1 group by sym;

select max(price), sym from t1 group by sym, minute(timestamp)

select avg(qty) from t1 group by sym;

select wavg(price, qty) as vwap, sum(qty) from t1 group by sym;

select wsum(price, qty) as dollarVolume, sum(qty) from t1 group by minute(timestamp) as ts;

select sum(qty) from t1 group by sym, timestamp.minute() as minute;

group by和order by配合使用。order by的字段必须是group by结果表中的字段。

select sum(qty) from t1 group by sym, timestamp.minute() as minute order by minute;

在上述例子中，每个分组的函数结果都是标量。在其他情况下，函数可能输出向量或者字典，而不是输出标量。比如，stat 函数输出字典； ols 输出一个系数向量或一个含有参数估计如t-stat, R²的字典等。为了在多列中输出结果，需要将向量或字典输出转换成多个标量值。换而言之，需要将一个合成列转换成多个列。我们可以通过as关键字和一个代表列名的常量字符串向量来完成这项工作。

y=1..15
factor1=3.2 1.2 5.9 6.9 11.1 9.6 1.4 7.3 2.0 0.1 6.1 2.9 6.3 8.4 5.6
factor2=1.7 1.3 4.2 6.8 9.2 1.3 1.4 7.8 7.9 9.9 9.3 4.6 7.8 2.4 8.7
id=take(1 2 3, 15).sort();
t=table(id, y, factor1, factor2);

t;

select ols(y,(factor1,factor2),true,0) as `int`factor1`factor2 from t group by id;

select ols(y,(factor1,factor2),true,2).Coefficient.tstat[1:] as `t1`t2 from t group by id;

若想要忽略函数的一些输出元素，可将列名留空。

select ols(y,(factor1,factor2),true,2).Coefficient.beta as ``factor1`factor2 from t group by id;

若想要自定义输出格式，可以写一个简单的包装函数。下面例子中，输出包含了系数估计和R²：

def myols(y,x) {
  r=ols(y,x,true,2)
  return r.Coefficient.beta join r.RegressionStat.statistics[0]
}

select myols(y,(factor1,factor2)) as `int`factor1`factor2`R2 from t group by id;