MySQL学习足迹记录10--汇总数据--MAX(),MIN(),AVG(),SU

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MySQL学习足迹记录10--汇总数据--MAX(),MIN(),AVG(),SU

来源: 作者: 时间:2016-02-18 10:28 【

MySQL学习足迹记录10--汇总数据--MAX(),MIN(),AVG(),SUM(),COUNT() 本文所用到的数据mysql SELECT prod_price FROM products;+------------+| prod_price |+------------+| 5.99 || ...
MySQL学习足迹记录10--汇总数据--MAX(),MIN(),AVG(),SUM(),COUNT()
 
       本文所用到的数据
  
> SELECT prod_price FROM products;
+------------+
| prod_price |
+------------+
|       5.99 |
|       9.99 |
|      14.99 |
|      13.00 |
|      10.00 |
|       2.50 |
|       3.42 |
|      35.00 |
|      55.00 |
|       8.99 |
|      50.00 |
|       4.49 |
|       2.50 |
|      10.00 |
+------------+
14 rows in set (0.00 sec)

 

 
1.聚集函数
   AVG():       返回某列的平均值
   COUNT():     返回会某列的行数
   MAX():       返回会某列的最大值
   MIN():       返回会某列的最小值
   SUM():       返回会某列值之和
 
2.AVG()函数
 
Examples:
mysql> SELECT AVG(prod_price) AS avg_price
         -> FROM products;
+-----------+
| avg_price |
+-----------+
| 16.133571 |
+-----------+
1 row in set (0.01 sec)

*返回特定列或行的平均值
 Examples: 
   mysql> SELECT AVG(prod_price) AS avg_price        #过滤出vend_id为1003的产品,再求平均值
            -> FROM products
           -> WHERE vend_id = 1003;
+-----------+
| avg_price |
+-----------+
| 13.212857 |
+-----------+
1 row in set (0.00 sec)

 

 
 Tips:
   AVG()只能用来求特定数值列的平均值,为了获得多个列的平均值,必须使用多个AVG()函数
   AVG()函数忽略列值为NULL的行
 
3.COUNT()函数
  *COUNT(*)对表中行的数目进行计数,不管列标中包含的是空值(NULL)还是非空值
  *COUNT(column)对特定的列中具有值的行进行计数,忽略NULL值
 Examples:
   mysql> select COUNT(*) AS count_prod from products;
+------------+                            #products表中行的数目进行计数
| count_prod |
+------------+
|         14 |
+------------+
1 row in set (0.00 sec)


先列出cust_email的内容
mysql> SELECT cust_email FROM customers;
+---------------------+
| cust_email          |
+---------------------+
|      |
| NULL                |
|  |
|     |
| NULL                |
+---------------------+
5 rows in set (0.00 sec)

    
对cust_email进行计数
mysql> SELECT COUNT(cust_email) AS num_cust
         -> FROM customers;                   #忽略NULL值
+----------+
| num_cust |
+----------+
|        3 |
+----------+
1 row in set (0.00 sec)

 

 
4.MAX()函数
  返回指定列中的最大值,忽略NULL值
 
Examples:
 mysql> SELECT MAX(prod_price) AS max_price
          -> FROM products;
+-----------+
| max_price |
+-----------+
|     55.00 |
+-----------+
1 row in set (0.00 sec)

 

 
5.MIN()函数
  *返回指定列的最小值
mysql> SELECT MIN(prod_price) AS min_price
         -> FROM products;
+-----------+
| min_price |
+-----------+
|      2.50 |
+-----------+
1 row in set (0.00 sec)

 

 
6.SUM()函数
  *返回指定列值的和
 
mysql> SELECT SUM(prod_price) AS sum_price
          -> FROM products;
+-----------+
| sum_price |
+-----------+
|    225.87 |
+-----------+
1 row in set (0.00 sec)

 

 
 *SUM也可用来合计计算值
  Examples:
  下面先列出要计算的数据
mysql> SELECT item_price,quantity 
         -> FROM orderitems
         -> WHERE order_num = 20005;
+------------+----------+
| item_price | quantity |
+------------+----------+
|       5.99 |       10 |
|       9.99 |        3 |
|      10.00 |        5 |
|      10.00 |        1 |
+------------+----------+
4 rows in set (0.01 sec)

mysql> SELECT SUM(item_price*quantity) AS total_price
         -> FROM orderitems                         #返回订单中所有的物品价钱之和
         -> WHERE order_num = 20005;
+-------------+
| total_price |
+-------------+
|      149.87 |
+-------------+
1 row in set (0.00 sec)

 

 
7.聚集不同的值,关键字DISTINCT
   对于SUM(),MAX(),MIN(),AVG(),COUNT(),默认的参数为ALL,如果要计算只包含不同的值,需指定DISTINCT参数
 
 EXAMPLES:
   mysql> SELECT AVG(DISTINCT prod_price) AS avg_price
            -> FROM products
            -> WHERE vend_id = 1003;
+-----------+
| avg_price |
+-----------+
| 15.998000 |
+-----------+
1 row in set (0.02 sec)

 

 
8.组合聚集函数
  eg:
   mysql> SELECT COUNT(*) AS num_items,
            -> MIN(prod_price) AS price_min,
           -> MAX(prod_price) AS price_min,
           -> AVG(prod_price) AS price_avg
           -> FROM products;
+-----------+-----------+-----------+-----------+
| num_items | price_min | price_min | price_avg |
+-----------+-----------+-----------+-----------+
|        14 |      2.50 |     55.00 | 16.133571 |
+-----------+-----------+-----------+-----------+
1 row in set (0.00 sec)

 

 
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