Five statistical functions (used alone, of little significance, often used in combination with group by)
max maximum select max(shop_price) from goods;
min minimum select min(shop_price) from goods;
sum Sum select sum(shop_price) from goods;
avg Find average select avg(shop_price) from goods;
count How many rows are there in all value rows
count (*) absolute row number null Also included
In addition to count (column name), calculate the number of non-null rows in this column
count uses
mysql> select * from test8; +------+------+ | id | name | +------+------+ | 1 | lisi | | 2 | NULL | +------+------+ mysql> select count(*) from test8; +----------+ | count(*) | +----------+ | 2 | +----------+ mysql> select count(name) from test8; +-------------+ | count(name) | +-------------+ | 1 | +-------------+
Query inventory type 4
select sum(goods_number) from goods where cat_id=4;
group by
Count the inventory under each type of group
mysql> select cat_id,sum(goods_number) from goods group by cat_id; +--------+-------------------+ | cat_id | sum(goods_number) | +--------+-------------------+ | 2 | 0 | | 3 | 203 | | 4 | 4 | | 5 | 8 | | 8 | 61 | | 11 | 23 | | 13 | 4 | | 14 | 9 | | 15 | 2 | +--------+-------------------+
is not a standard sql statement and cannot be explained logically (each category cat_id contains Many goods_name)
It is not recommended to select goods_name,sum(goods_number) from goods group by cat_id;
Explanation: In select a/b, it must be in group by a/b/c to have no semantic problem
Tips: To understand the query statement, start with the subsequent conditional filtering. First understand the filtering conditions, and then look at the previous execution
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