数据保证订单数最多的顾客恰好只有一位。

表 orders 定义如下:
Column Type
order_number (PK) int
customer_number int
order_date date
required_date date
shipped_date date
status char(15)
comment char(200)
order_number customer_number order_date required_date shipped_date status comment
1 1 2017-04-09 2017-04-13 2017-04-12 Closed
2 2 2017-04-15 2017-04-20 2017-04-18 Closed
3 3 2017-04-16 2017-04-25 2017-04-20 Closed
4 3 2017-04-18 2017-04-28 2017-04-25 Closed
customer_number
3

不考虑并列:
直接按照用户分组, count(1)订单, desc排序, limit 1 输出
考虑并列:
先查询到最多的订单数量, 在通过having count(*)=最多的订单数量

不考虑并列:
# Write your MySQL query statement below
select customer_number from orders
group by customer_number
order by count(1) desc
limit 1
考虑到并列的情况:
select customer_number from orders group by customer_number 
having count(*)=(
select count(*) as c from orders
group by customer_number order by c desc limit 1)
                    在表 orders 中找到订单数最多客户对应的 customer_number 。数据保证订单数最多的顾客恰好只有一位。表 orders 定义如下:ColumnTypeorder_number (PK)intcustomer_numberintorder_datedaterequired_datedateshipped_datedate...
+-----------------+----------+
| Column Name     | Type     |
+-----------------+----------+
| order_number    | int      |
| customer_number | int      |
+-----------------+----------+
Order_number是该表的主
+-----------------+----------+
| Column Name     | Type     |
+-----------------+----------+
| order_number    | int      |
| customer_number | int      |
+-----------------+----------+
				
以下查询语句返回 customer表中 city重复次数(count) 最多的20条记录: SELECT city, count( * ) AS count FROM customer GROUP BY city ORDER BY count DESC LIMIT 20 以下查询语句返回 article_keyword 表中 keyword 的重复次数(count) 排名前 6 的数值。通过添加 DISTINCT 返回唯一记录: SELECT DISTINCT count( * ) AS count
好的,我可以回答这个问题。假设我们有一个客户数据表,其中包含客户的姓名、年龄、性别、所在城市、购买记录等信息。我们可以使用 SQL 查询语句来进行客户数据分析,例如: 1. 统计不同城市的客户数量: SELECT 所在城市, COUNT(*) AS 客户数量 FROM 客户数据表 GROUP BY 所在城市; 2. 统计不同年龄段的客户数量: SELECT CASE WHEN 年龄 < 18 THEN '18岁以下' WHEN 年龄 >= 18 AND 年龄 < 30 THEN '18-30岁' WHEN 年龄 >= 30 AND 年龄 < 40 THEN '30-40岁' ELSE '40岁以上' END AS 年龄段, COUNT(*) AS 客户数量 FROM 客户数据表 GROUP BY 年龄段; 3. 统计男女客户比例: SELECT 性别, COUNT(*) AS 客户数量 FROM 客户数据表 GROUP BY 性别; 4. 统计购买记录最多客户: SELECT 姓名, SUM(购买记录) AS 购买总金额 FROM 客户数据表 GROUP BY 姓名 ORDER BY 购买总金额 DESC LIMIT 1; 以上是一些简单的客户数据分析案例,可以根据具体需求进行更复杂的查询和分析。