Python--day46--分组(看了别人博客掌握的)

原文链接:https://www.cnblogs.com/snsdzjlz320/p/5738226.html

 

group by

(1) group by的含义:将查询结果按照1个或多个字段进行分组,字段值相同的为一组
(2) group by可用于单个字段分组,也可用于多个字段分组

select * from employee;
+------+------+--------+------+------+-------------+
| num  | d_id | name   | age  | sex  | homeaddr    |
+------+------+--------+------+------+-------------+
|    1 | 1001 | 张三   |   26 | 男   | beijinghdq  |
|    2 | 1002 | 李四   |   24 | 女   | beijingcpq  |
|    3 | 1003 | 王五   |   25 | 男   | changshaylq |
|    4 | 1004 | Aric   |   15 | 男   | England     |
+------+------+--------+------+------+-------------+

select * from employee group by d_id,sex;
select * from employee group by sex; +------+------+--------+------+------+------------+ | num | d_id | name | age | sex | homeaddr | +------+------+--------+------+------+------------+ | 2 | 1002 | 李四 | 24 | 女 | beijingcpq | | 1 | 1001 | 张三 | 26 | 男 | beijinghdq | +------+------+--------+------+------+------------+ 根据sex字段来分组,sex字段的全部值只有两个('男'和'女'),所以分为了两组 当group by单独使用时,只显示出每组的第一条记录 所以group by单独使用时的实际意义不大

 

group by + group_concat()

(1) group_concat(字段名)可以作为一个输出字段来使用,
(2) 表示分组之后,根据分组结果,使用group_concat()来放置每一组的某字段的值的集合

select sex from employee group by sex;
+------+
| sex  |
+------+
| 女   |
| 男   |
+------+

select sex,group_concat(name) from employee group by sex;
+------+--------------------+
| sex  | group_concat(name) |
+------+--------------------+
| 女   | 李四               |
| 男   | 张三,王五,Aric     |
+------+--------------------+

select sex,group_concat(d_id) from employee group by sex;
+------+--------------------+
| sex  | group_concat(d_id) |
+------+--------------------+
| 女   | 1002               |
| 男   | 1001,1003,1004     |
+------+--------------------+

 

group by + 集合函数

(1) 通过group_concat()的启发,我们既然可以统计出每个分组的某字段的值的集合,那么我们也可以通过集合函数来对这个"值的集合"做一些操作

select sex,group_concat(age) from employee group by sex;
+------+-------------------+
| sex  | group_concat(age) |
+------+-------------------+
| 女   | 24                |
| 男   | 26,25,15          |
+------+-------------------+

分别统计性别为男/女的人年龄平均值 select sex,avg(age) from employee group by sex; +------+----------+ | sex | avg(age) | +------+----------+ | 女 | 24.0000 | | 男 | 22.0000 | +------+----------+
分别统计性别为男/女的人的个数 select sex,count(sex) from employee group by sex; +------+------------+ | sex | count(sex) | +------+------------+ | 女 | 1 | | 男 | 3 | +------+------------+

 

group by + having

(1) having 条件表达式:用来分组查询后指定一些条件来输出查询结果
(2) having作用和where一样,但having只能用于group by

select sex,count(sex) from employee group by sex having count(sex)>2;
+------+------------+
| sex  | count(sex) |
+------+------------+
| 男   |          3 |
+------+------------+

 

group by + with rollup

(1) with rollup的作用是:在最后新增一行,来记录当前列里所有记录的总和

select sex,count(age) from employee group by sex with rollup;
+------+------------+
| sex  | count(age) |
+------+------------+
| 女   |          1 |
| 男   |          3 |
| NULL |          4 |
+------+------------+

select sex,group_concat(age) from employee group by sex with rollup;
+------+-------------------+
| sex  | group_concat(age) |
+------+-------------------+
| 女   | 24                |
| 男   | 26,25,15          |
| NULL | 24,26,25,15       |
+------+-------------------+

 

posted @ 2019-02-15 15:04  莱茵河的雨季  阅读(296)  评论(0编辑  收藏  举报