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像Excel一样使用SQL进行数据分析

像Excel一样使用SQL进行数据分析

作者: 头顶一根发的程序猿 | 来源:发表于2019-11-21 15:38 被阅读0次

    Excel是数据分析中最常用的工具 ,利用Excel可以完成数据清洗,预处理,以及最常见的数据分类,数据筛选,分类汇总,以及数据透视等操作,而这些操作用SQL一样可以实现。SQL不仅可以从数据库中读取数据,还能通过不同的SQL函数语句直接返回所需要的结果,从而大大提高了自己在客户端应用程序中计算的效率。

    1 重复数据处理
    查找重复记录

    SELECT * FROM user 
    Where (nick_name,password) in
    (
    SELECT nick_name,password 
    FROM user 
    group by nick_name,password 
    having count(nick_name)>1
    );
    

    查找去重记录
    查找id最大的记录

    SELECT * FROM user 
    WHERE id in
    (SELECT max(id) FROM user
    group by nick_name,password 
    having count(nick_name)>1
    );
    

    删除重复记录
    只保留id值最小的记录

    DELETE  c1
    FROM  customer c1,customer c2
    WHERE c1.cust_email=c2.cust_email
    AND c1.id>c2.id;
    DELETE FROM user Where (nick_name,password) in
    (SELECT nick_name,password FROM
        (SELECT nick_name,password FROM user 
        group by nick_name,password 
        having count(nick_name)>1) as tmp1
    )
    and id not in
    (SELECT id FROM
        (SELECT min(id) id FROM user 
         group by nick_name,password 
         having count(nick_name)>1) as tmp2
    );
    

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    2 缺失值处理
    查找缺失值记录

    SELECT * FROM customer
    WHERE cust_email IS NULL;
    

    更新列填充空值

    UPDATE sale set city = "未知" 
    WHERE city IS NULL;
    
    UPDATE orderitems set 
    price_new=IFNULL(price_new,5.74);
    

    查询并填充空值列

    SELECT AVG(price_new) FROM orderitems;
    
    SELECT IFNULL(price_new,5.74) AS bus_ifnull
    FROM orderitems;
    

    3 计算列
    更新表添加计算列

    ALTER TABLE orderitems ADD price_new DECIMAL(8,2) NOT NULL;
    
    UPDATE orderitems set price_new= item_price*count;
    

    查询计算列

    SELECT item_price*count as sales FROM orderitems;
    

    4 排序
    多列排序

    SELECT * FROM orderitems
    ORDER BY price_new DESC,quantity;
    

    查询排名前几的记录

    SELECT * FROM orderitems
    ORDER BY price_new DESC LIMIT 5;
    

    查询第10大的值

    SELECT DISTINCT price_new
    FROM orderitems
    ORDER BY price_new DESC LIMIT 9,1;
    

    排名

    数值相同的排名相同且排名连续

    SELECT prod_price,
    (SELECT COUNT(DISTINCT prod_price)
    FROM products
    WHERE prod_price>=a.prod_price
    ) AS rank
    FROM products AS a
    ORDER BY rank ;
    

    5 字符串处理
    字符串替换

    UPDATE data1 SET city=REPLACE(city,'SH','shanghai');
    
    SELECT city FROM data1;
    

    按位置字符串截取
    字符串截取可用于数据分列
    MySQL 字符串截取函数:left(), right(), substring(), substring_index()

    SELECT left('example.com', 3);
    

    从字符串的第 4 个字符位置开始取,直到结束

    SELECT substring('example.com', 4);
    

    从字符串的第 4 个字符位置开始取,只取 2 个字符

    SELECT substring('example.com', 4, 2);
    

    按关键字截取字符串
    取第一个分隔符之前的所有字符,结果是www

    SELECT substring_index('www.google.com','.',1);
    

    取倒数第二个分隔符之后的所有字符,结果是google.com;

    SELECT substring_index('www.google.com','.',-2);
    

    6 筛选
    通过操作符实现高级筛选

    使用 AND OR IN NOT 等操作符实现高级筛选过滤

    SELECT prod_name,prod_price FROM Products
    WHERE vend_id IN('DLL01','BRS01');
    SELECT prod_name FROM Products WHERE NOT vend_id='DLL01';
    

    通配符筛选

    常用通配符有% _ [] ^

    SELECT * from customers WHERE country LIKE "CH%";
    

    7 表联结
    SQL表连接可以实现类似于Excel中的Vlookup函数的功能

    SELECT vend_id,prod_name,prod_price
    FROM Vendors INNER JOIN Products
    ON Vendors.vend_id=Products.vend_id;
    
    SELECT prod_name,vend_name,prod_price,quantity
    FROM OderItems,Products,Vendors
    WHERE Products.vend_id=Vendors.vend_id
    AND OrderItems.prod_id=Products.prod_id
    AND order_num=20007;
    

    自联结 在一条SELECT语句中多次使用相同的表

    SELECT c1.cust_od,c1.cust_name,c1.cust_contact
    FROM Customers as c1,Customers as c2
    WHERE c1.cust_name=c2.cust_name
    AND c2.cust_contact='Jim Jones';
    

    8 数据透视
    数据分组可以实现Excel中数据透视表的功能

    数据分组

    group by 用于数据分组 having 用于分组后数据的过滤

    SELECT order_num,COUNT(*) as items
    FROM OrderItems
    GROUP BY order_num HAVING COUNT(*)>=3;
    

    交叉表
    通过CASE WHEN函数实现

    SELECT data1.city,
    CASE WHEN colour = "A" THEN price END AS A,
    CASE WHEN colour = "B" THEN price END AS B,
    CASE WHEN colour = "C" THEN price END AS C,
    CASE WHEN colour = "F" THEN price END AS F
    FROM data1
    

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