我们使用一个名为"Products"的表,包含以下列:ProductID、ProductName、CategoryID、UnitPrice、StockQuantity。
-- 建表
CREATE TABLE `products` (`productID` int(11) NOT NULL,`productName` varchar(255) DEFAULT NULL,`categoryID` int(11) DEFAULT NULL,`unitPrice` int(11) DEFAULT NULL,`stockQuantity` int(11) DEFAULT NULL,PRIMARY KEY (`productID`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4;-- 样例数据
INSERT INTO `products` VALUES (1, 'Laptop', 1, 800, 50);
INSERT INTO `products` VALUES (2, 'Smartphone', 1, 500, 100);
INSERT INTO `products` VALUES (3, 'T-shirt', 2, 20, 200);
INSERT INTO `products` VALUES (4, 'Jeans', 2, 40, 150);
INSERT INTO `products` VALUES (5, 'Headphones', 1, 100, 75);
productID | productName | categoryID | unitPrice | stockQuantity |
---|---|---|---|---|
1 | Laptop | 1 | 800 | 50 |
2 | Smartphone | 1 | 500 | 100 |
3 | T-shirt | 2 | 20 | 200 |
4 | Jeans | 2 | 40 | 150 |
5 | Headphones | 1 | 100 | 75 |
SELECTProductName,UnitPrice,
CASEWHEN UnitPrice > 100 THEN'Expensive' ELSE 'Affordable' END AS PriceCategory
FROMProducts;
查询结果:
ProductName | UnitPrice | PriceCategory |
---|---|---|
Laptop | 800 | Expensive |
Smartphone | 500 | Expensive |
T-shirt | 20 | Affordable |
Jeans | 40 | Affordable |
Headphones | 100 | Affordable |
SELECTproductName,stockQuantity,
CASEWHEN stockQuantity > 100 THEN'In Stock' WHEN stockQuantity > 50 THEN'Limited Stock' ELSE 'Out of Stock' END AS StockStatus
FROMproducts;
查询结果:
productName | stockQuantity | StockStatus |
---|---|---|
Laptop | 50 | Out of Stock |
Smartphone | 100 | Limited Stock |
T-shirt | 200 | In Stock |
Jeans | 150 | In Stock |
Headphones | 75 | Limited Stock |
SELECTcategoryID,AVG( unitPrice ) AS AvgPrice,
CASEWHEN AVG( unitPrice ) > 50 THEN'High Price' ELSE 'Low Price' END AS PriceCategory
FROMproducts
GROUP BYcategoryID;
categoryID | AvgPrice | PriceCategory |
---|---|---|
1 | 466.6667 | Hign Price |
2 | 30 | low Price |
SELECTproductName,
CASEWHEN EXTRACT( MONTH FROM CURRENT_DATE ) = 8 THEN( SELECT NOW() ) ELSE 'Other Month' END AS CurrentTime
FROMproducts;
productName | CurrentTime |
---|---|
Laptop | 2023/8/30 19:14 |
Smartphone | 2023/8/30 19:14 |
T-shirt | 2023/8/30 19:14 |
Jeans | 2023/8/30 19:14 |
Headphones | 2023/8/30 19:14 |
SELECTProductName,UnitPrice,CASEWHEN UnitPrice > 50 THEN 'Expensive'ELSE 'Affordable'END AS PriceCategory
FROM Products
ORDER BY UnitPrice DESC;
productName | unitPrice | PriceCategory |
---|---|---|
Laptop | 1902/3/10 0:00 | Expensive |
Smartphone | 1901/5/14 0:00 | Expensive |
Headphones | 1900/4/9 0:00 | Expensive |
Jeans | 1900/2/9 0:00 | Affordable |
T-shirt | 1900/1/20 0:00 | Affordable |
SELECTproductName,unitPrice,( CASE WHEN unitPrice > ( SELECT AVG( unitPrice ) FROM products ) THEN 'Above Avg' ELSE 'Below Avg' END ) AS PriceComparison
FROMproducts;
productName | unitPrice | PriceComparison |
---|---|---|
Laptop | 800 | Above Avg |
Smartphone | 500 | Above Avg |
T-shirt | 20 | Below Avg |
Jeans | 40 | Below Avg |
Headphones | 100 | Below Avg |
SELECTProductName,UnitPrice,StockQuantity,CASEWHEN StockQuantity > 0 THEN UnitPrice / StockQuantityELSE 0END AS PricePerUnit
FROM Products;
productName | unitPrice | stockQuantity | PricePerUnit |
---|---|---|---|
Laptop | 800 | 50 | 16 |
Smartphone | 500 | 100 | 5 |
T-shirt | 20 | 200 | 0.1 |
Jeans | 40 | 150 | 0.2667 |
Headphones | 100 | 75 | 1.3333 |
SELECTproductName,unitPrice,stockQuantity,
CASEWHEN stockQuantity > 150 THEN'High' WHEN stockQuantity > 100 THEN'Medium' ELSE 'Low' END AS StockCategory,
CASEWHEN stockQuantity > 100 THENstockQuantity * 1.1 ELSE stockQuantity * 1.05 END AS AdjustedStock
FROMproducts;
productName | unitPrice | stockQuantity | StockCategory | AdjustedStock |
---|---|---|---|---|
Laptop | 800 | 50 | Low | 52.5 |
Smartphone | 500 | 100 | Low | 105 |
T-shirt | 20 | 200 | High | 220 |
Jeans | 40 | 150 | Medium | 165 |
Headphones | 100 | 75 | Low | 78.75 |
SELECTProductName,UnitPrice,CASEWHEN StockQuantity > 100 THENCASEWHEN UnitPrice > 50 THEN 'High Demand, High Price'ELSE 'High Demand, Affordable'ENDELSE 'Low Demand'END AS ProductStatus
FROM Products;
productName | unitPrice | ProductStatus |
---|---|---|
Laptop | 800 | Low Demand |
Smartphone | 500 | Low Demand |
T-shirt | 20 | High Demand, Affordable |
Jeans | 40 | High Demand, Affordable |
Headphones | 100 | Low Demand |
SELECTProductName,CASEWHEN ProductName LIKE '%Laptop%' THEN 'Electronics'WHEN ProductName LIKE '%T-shirt%' THEN 'Clothing'ELSE 'Other'END AS Category
FROM Products;
productName | Category |
---|---|
Laptop | Electronics |
Smartphone | Other |
T-shirt | Clothing |
Jeans | Other |
Headphones | Other |
SELECTProductName,UnitPrice,CASEWHEN UnitPrice > 50 AND StockQuantity > 50 THEN 'High Price, High Stock'WHEN UnitPrice > 50 OR StockQuantity > 50 THEN 'High Price or High Stock'ELSE 'Low Price and Low Stock'END AS ProductStatus
FROM Products;
productName | unitPrice | ProductStatus |
---|---|---|
Laptop | 800 | High Price or High Stock |
Smartphone | 500 | High Price, High Stock |
T-shirt | 20 | High Price or High Stock |
Jeans | 40 | High Price or High Stock |
Headphones | 100 | High Price, High Stock |
SELECTProductName,UnitPrice,StockQuantity,CASEWHEN StockQuantity > 50 AND UnitPrice <30 THEN 'Popular and Affordable'WHEN StockQuantity <= 50 AND UnitPrice < 30 THEN 'Limited Stock, Affordable'WHEN StockQuantity > 50 AND UnitPrice >= 30 THEN 'Popular and Expensive'ELSE 'Limited Stock, Expensive'END AS ProductCategory
FROM Products;
productName | unitPrice | stockQuantity | ProductCategory |
---|---|---|---|
Laptop | 800 | 50 | Limited Stock, Expensive |
Smartphone | 500 | 100 | Popular and Expensive |
T-shirt | 20 | 200 | Popular and Affordable |
Jeans | 40 | 150 | Popular and Expensive |
Headphones | 100 | 75 | Popular and Expensive |
SELECTProductName,UnitPrice,StockQuantity,CASEWHEN StockQuantity > AVG(StockQuantity) OVER () THEN 'Above Avg Stock'ELSE 'Below Avg Stock'END AS StockComparison
FROM Products;
productName | unitPrice | stockQuantity | StockComparison |
---|---|---|---|
T-shirt | 20 | 200 | Above Avg Stock |
Laptop | 800 | 50 | Below Avg Stock |
Jeans | 40 | 150 | Above Avg Stock |
Smartphone | 500 | 100 | Below Avg Stock |
Headphones | 100 | 75 | Below Avg Stock |
样例SQL:
SELECTp.ProductID,p.ProductName,s.SaleDate,s.QuantitySold,CASEWHEN s.QuantitySold > LAG(s.QuantitySold) OVER (PARTITION BY p.ProductID ORDER BY s.SaleDate) THEN 'Increased'WHEN s.QuantitySold < LAG(s.QuantitySold) OVER (PARTITION BY p.ProductID ORDER BY s.SaleDate) THEN 'Decreased'ELSE 'Stable'END AS Trend
FROM Products p
JOIN SalesHistory s ON p.ProductID = s.ProductID;
样例SQL:
SELECTo.OrderID,o.OrderDate,SUM(CASE WHEN p.CategoryID = 1 THEN o.Quantity ELSE 0 END) AS ElectronicsQuantity,SUM(CASE WHEN p.CategoryID = 2 THEN o.Quantity ELSE 0 END) AS ClothingQuantity,SUM(CASE WHEN p.CategoryID = 3 THEN o.Quantity ELSE 0 END) AS OtherQuantity
FROM Orders o
JOIN Products p ON o.ProductID = p.ProductID
GROUP BY o.OrderID, o.OrderDate;
样例SQL:
SELECTEmployeeID,FirstName,LastName,Salary,CASEWHEN Salary > 70000 THEN 'High'WHEN Salary > 60000 THEN 'Medium'WHEN Salary > 50000 THEN 'Low'ELSE 'Very Low'END AS SalaryLevel,CASEWHEN Salary > 60000 THEN 'Above Average'ELSE 'Below Average'END AS SalaryComparison
FROM Employees;
样例SQL:
SELECTCustomerID,Age,Gender,CASEWHEN Age < 30 THEN 'Young'WHEN Age >= 30 AND Age < 40 THEN 'Middle-aged'ELSE 'Senior'END AS AgeGroup,CASEWHEN Gender = 'Male' THEN 'Male'WHEN Gender = 'Female' THEN 'Female'ELSE 'Other'END AS GenderCategory
FROM Customers;
样例SQL:
SELECTOrderID,OrderDate,SUM(CASE WHEN Quantity * Price > 500 THEN Quantity ELSE 0 END) AS HighValueItems,SUM(CASE WHEN Quantity * Price > 100 AND Quantity * Price <= 500 THEN Quantity ELSE 0 END) AS MediumValueItems,SUM(CASE WHEN Quantity * Price <= 100 THEN Quantity ELSE 0 END) AS LowValueItems
FROM Orders
GROUP BY OrderID, OrderDate;
您可以使用CASE WHEN来对现有数据进行重新编码,例如将文本值转换为数字编码或将某些字符串转换为更易于处理的标识符。
SELECTcustomerName,CASEWHEN customerType = 'Individual' THEN 1WHEN customerType = 'Corporate' THEN 2ELSE 0END AS CustomerTypeCode
FROM Customers;
使用CASE WHEN可以在查询结果中创建不同的数据分组,而无需在实际数据中创建新的列。
SELECTproductName,SUM(quantity) AS totalQuantity,CASEWHEN SUM(quantity) > 100 THEN 'High'WHEN SUM(quantity) > 50 THEN 'Medium'ELSE 'Low'END AS QuantityGroup
FROM Sales
GROUP BY productName;
通过在ORDER BY子句中使用CASE WHEN,您可以根据不同条件动态调整查询结果的排序规则。
SELECTproductName,unitPrice
FROM Products
ORDER BYCASEWHEN category = 'Electronics' THEN unitPriceWHEN category = 'Clothing' THEN unitPrice * 0.9ELSE unitPrice * 1.1END;
使用CASE WHEN可以在查询结果中对数据进行分位数分析,识别哪些数据点位于不同的分位数区间。
SELECTproductName,unitPrice,CASEWHEN unitPrice <= PERCENTILE_CONT(0.25) WITHIN GROUP (ORDER BY unitPrice) THEN 'Q1'WHEN unitPrice <= PERCENTILE_CONT(0.5) WITHIN GROUP (ORDER BY unitPrice) THEN 'Q2'WHEN unitPrice <= PERCENTILE_CONT(0.75) WITHIN GROUP (ORDER BY unitPrice) THEN 'Q3'ELSE 'Q4'END AS PriceQuartile
FROM Products;
使用CASE WHEN可以根据条件将缺失的数据点填充为特定值,从而更好地处理数据缺失情况。
SELECTorderID,orderDate,CASEWHEN orderAmount IS NULL THEN 0ELSE orderAmountEND AS FilledOrderAmount
FROM Orders;
使用CASE WHEN可以对日期进行区间分析,例如判断每个日期属于哪个季节、哪个月份等。
SELECTorderDate,CASEWHEN EXTRACT(MONTH FROM orderDate) IN (12, 1, 2) THEN 'Winter'WHEN EXTRACT(MONTH FROM orderDate) IN (3, 4, 5) THEN 'Spring'WHEN EXTRACT(MONTH FROM orderDate) IN (6, 7, 8) THEN 'Summer'ELSE 'Fall'END AS Season
FROM Orders;
使用CASE WHEN可以根据特定业务规则判断数据所处的不同阶段,如用户生命周期阶段、订单处理阶段等。
SELECTuserID,registrationDate,CASEWHEN NOW() - registrationDate < INTERVAL '30 days' THEN 'New User'WHEN NOW() - registrationDate < INTERVAL '90 days' THEN 'Regular User'ELSE 'Inactive User'END AS UserStage
FROM Users;
使用CASE WHEN可以在查询结果中根据条件选择不同的列,从而根据业务需求定制查询结果。
SELECTorderID,orderDate,CASEWHEN displayPrice = 'Gross' THEN grossPriceELSE netPriceEND AS SelectedPrice
FROM Orders;
使用CASE WHEN可以根据条件识别和标记异常数据点,帮助进行数据质量分析。
SELECTcustomerID,orderDate,orderAmount,CASEWHEN orderAmount < 0 THEN 'Negative'WHEN orderAmount > 10000 THEN 'High Amount'ELSE 'Normal'END AS DataQuality
FROM Orders;
使用CASE WHEN可以在不同的数据格式之间进行转换,例如将布尔值转换为文本标签。
SELECTproductID,productName,inStock,CASEWHEN inStock THEN 'Available'ELSE 'Out of Stock'END AS StockStatus
FROM Products;
本文发布于:2024-02-02 02:16:47,感谢您对本站的认可!
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