21. Show orders where the Total_Amount is within the top 25% of all orders.
Code In Sql
-- Table Name : Orders
-- | Order_ID | Customer_Name | Product | Quantity | Order_Date | Total_Amount | CATEGORY |
-- |----------|---------------|---------------|----------|------------|--------------|--------------|
-- | 101 | Ananya | Laptop | 1 | 2023-06-15 | 55000.00 | Electronics |
-- | 102 | Bharat | Mobile Phone | 2 | 2023-06-18 | 60000.00 | Electronics |
-- | 103 | Chitra | Office Chair | 4 | 2023-07-01 | 28000.00 | Furniture |
-- | 104 | Dev | Coffee Maker | 1 | 2023-07-04 | 4000.00 | Furniture |
-- | 105 | Esha | Dining Table | 1 | 2023-07-10 | 15000.00 | Furniture |
-- | 106 | Ananya | Headphones | 1 | 2023-06-16 | 2000.00 | Electronics |
-- | 107 | Bharat | Charger | 1 | 2023-06-20 | 500.00 | Electronics |
-- | 108 | Harsh | Headphones | 1 | 2023-07-16 | 2000.00 | Electronics |
-- | 109 | Ishita | Headphones | 2 | 2023-07-17 | 4000.00 | Electronics |
-- | 110 | Jai | Headphones | 2 | 2023-07-18 | 4000.00 | Electronics |
-- | 111 | Kavita | Headphones | 6 | 2023-07-19 | 12000.00 | Electronics |
-- Your Query Here
Output
Click Run Button to view compiled output
22. Retrieve the percentage contribution of each order to the total revenue.
Code In Sql
-- Table Name : Orders
-- | Order_ID | Customer_Name | Product | Quantity | Order_Date | Total_Amount | CATEGORY |
-- |----------|---------------|---------------|----------|------------|--------------|--------------|
-- | 101 | Ananya | Laptop | 1 | 2023-06-15 | 55000.00 | Electronics |
-- | 102 | Bharat | Mobile Phone | 2 | 2023-06-18 | 60000.00 | Electronics |
-- | 103 | Chitra | Office Chair | 4 | 2023-07-01 | 28000.00 | Furniture |
-- | 104 | Dev | Coffee Maker | 1 | 2023-07-04 | 4000.00 | Furniture |
-- | 105 | Esha | Dining Table | 1 | 2023-07-10 | 15000.00 | Furniture |
-- | 106 | Ananya | Headphones | 1 | 2023-06-16 | 2000.00 | Electronics |
-- | 107 | Bharat | Charger | 1 | 2023-06-20 | 500.00 | Electronics |
-- | 108 | Harsh | Headphones | 1 | 2023-07-16 | 2000.00 | Electronics |
-- | 109 | Ishita | Headphones | 2 | 2023-07-17 | 4000.00 | Electronics |
-- | 110 | Jai | Headphones | 2 | 2023-07-18 | 4000.00 | Electronics |
-- | 111 | Kavita | Headphones | 6 | 2023-07-19 | 12000.00 | Electronics |
-- Your Query Here
Output
Click Run Button to view compiled output
23. Identify orders that generated more revenue than the average revenue for their respective product.
Code In Sql
-- Table Name : Orders
-- | Order_ID | Customer_Name | Product | Quantity | Order_Date | Total_Amount | CATEGORY |
-- |----------|---------------|---------------|----------|------------|--------------|--------------|
-- | 101 | Ananya | Laptop | 1 | 2023-06-15 | 55000.00 | Electronics |
-- | 102 | Bharat | Mobile Phone | 2 | 2023-06-18 | 60000.00 | Electronics |
-- | 103 | Chitra | Office Chair | 4 | 2023-07-01 | 28000.00 | Furniture |
-- | 104 | Dev | Coffee Maker | 1 | 2023-07-04 | 4000.00 | Furniture |
-- | 105 | Esha | Dining Table | 1 | 2023-07-10 | 15000.00 | Furniture |
-- | 106 | Ananya | Headphones | 1 | 2023-06-16 | 2000.00 | Electronics |
-- | 107 | Bharat | Charger | 1 | 2023-06-20 | 500.00 | Electronics |
-- | 108 | Harsh | Headphones | 1 | 2023-07-16 | 2000.00 | Electronics |
-- | 109 | Ishita | Headphones | 2 | 2023-07-17 | 4000.00 | Electronics |
-- | 110 | Jai | Headphones | 2 | 2023-07-18 | 4000.00 | Electronics |
-- | 111 | Kavita | Headphones | 6 | 2023-07-19 | 12000.00 | Electronics |
-- Your Query Here
Output
Click Run Button to view compiled output
24. List orders that were placed on a Monday.
Code In Sql
-- Table Name : Orders
-- | Order_ID | Customer_Name | Product | Quantity | Order_Date | Total_Amount | CATEGORY |
-- |----------|---------------|---------------|----------|------------|--------------|--------------|
-- | 101 | Ananya | Laptop | 1 | 2023-06-15 | 55000.00 | Electronics |
-- | 102 | Bharat | Mobile Phone | 2 | 2023-06-18 | 60000.00 | Electronics |
-- | 103 | Chitra | Office Chair | 4 | 2023-07-01 | 28000.00 | Furniture |
-- | 104 | Dev | Coffee Maker | 1 | 2023-07-04 | 4000.00 | Furniture |
-- | 105 | Esha | Dining Table | 1 | 2023-07-10 | 15000.00 | Furniture |
-- | 106 | Ananya | Headphones | 1 | 2023-06-16 | 2000.00 | Electronics |
-- | 107 | Bharat | Charger | 1 | 2023-06-20 | 500.00 | Electronics |
-- | 108 | Harsh | Headphones | 1 | 2023-07-16 | 2000.00 | Electronics |
-- | 109 | Ishita | Headphones | 2 | 2023-07-17 | 4000.00 | Electronics |
-- | 110 | Jai | Headphones | 2 | 2023-07-18 | 4000.00 | Electronics |
-- | 111 | Kavita | Headphones | 6 | 2023-07-19 | 12000.00 | Electronics |
-- Your Query Here
Output
Click Run Button to view compiled output
25. Find orders where the Total_Amount is at least twice the median Total_Amount.
Code In Sql
-- Table Name : Orders
-- | Order_ID | Customer_Name | Product | Quantity | Order_Date | Total_Amount | CATEGORY |
-- |----------|---------------|---------------|----------|------------|--------------|--------------|
-- | 101 | Ananya | Laptop | 1 | 2023-06-15 | 55000.00 | Electronics |
-- | 102 | Bharat | Mobile Phone | 2 | 2023-06-18 | 60000.00 | Electronics |
-- | 103 | Chitra | Office Chair | 4 | 2023-07-01 | 28000.00 | Furniture |
-- | 104 | Dev | Coffee Maker | 1 | 2023-07-04 | 4000.00 | Furniture |
-- | 105 | Esha | Dining Table | 1 | 2023-07-10 | 15000.00 | Furniture |
-- | 106 | Ananya | Headphones | 1 | 2023-06-16 | 2000.00 | Electronics |
-- | 107 | Bharat | Charger | 1 | 2023-06-20 | 500.00 | Electronics |
-- | 108 | Harsh | Headphones | 1 | 2023-07-16 | 2000.00 | Electronics |
-- | 109 | Ishita | Headphones | 2 | 2023-07-17 | 4000.00 | Electronics |
-- | 110 | Jai | Headphones | 2 | 2023-07-18 | 4000.00 | Electronics |
-- | 111 | Kavita | Headphones | 6 | 2023-07-19 | 12000.00 | Electronics |
-- Your Query Here
Output
Click Run Button to view compiled output
26. Calculate the average gap in days between consecutive orders for each customer.
Code In Sql
-- Table Name : Orders
-- | Order_ID | Customer_Name | Product | Quantity | Order_Date | Total_Amount | CATEGORY |
-- |----------|---------------|---------------|----------|------------|--------------|--------------|
-- | 101 | Ananya | Laptop | 1 | 2023-06-15 | 55000.00 | Electronics |
-- | 102 | Bharat | Mobile Phone | 2 | 2023-06-18 | 60000.00 | Electronics |
-- | 103 | Chitra | Office Chair | 4 | 2023-07-01 | 28000.00 | Furniture |
-- | 104 | Dev | Coffee Maker | 1 | 2023-07-04 | 4000.00 | Furniture |
-- | 105 | Esha | Dining Table | 1 | 2023-07-10 | 15000.00 | Furniture |
-- | 106 | Ananya | Headphones | 1 | 2023-06-16 | 2000.00 | Electronics |
-- | 107 | Bharat | Charger | 1 | 2023-06-20 | 500.00 | Electronics |
-- | 108 | Harsh | Headphones | 1 | 2023-07-16 | 2000.00 | Electronics |
-- | 109 | Ishita | Headphones | 2 | 2023-07-17 | 4000.00 | Electronics |
-- | 110 | Jai | Headphones | 2 | 2023-07-18 | 4000.00 | Electronics |
-- | 111 | Kavita | Headphones | 6 | 2023-07-19 | 12000.00 | Electronics |
-- Your Query Here
Output
Click Run Button to view compiled output
27. Show the highest single order Total_Amount for each month and year.
Code In Sql
-- Table Name : Orders
-- | Order_ID | Customer_Name | Product | Quantity | Order_Date | Total_Amount | CATEGORY |
-- |----------|---------------|---------------|----------|------------|--------------|--------------|
-- | 101 | Ananya | Laptop | 1 | 2023-06-15 | 55000.00 | Electronics |
-- | 102 | Bharat | Mobile Phone | 2 | 2023-06-18 | 60000.00 | Electronics |
-- | 103 | Chitra | Office Chair | 4 | 2023-07-01 | 28000.00 | Furniture |
-- | 104 | Dev | Coffee Maker | 1 | 2023-07-04 | 4000.00 | Furniture |
-- | 105 | Esha | Dining Table | 1 | 2023-07-10 | 15000.00 | Furniture |
-- | 106 | Ananya | Headphones | 1 | 2023-06-16 | 2000.00 | Electronics |
-- | 107 | Bharat | Charger | 1 | 2023-06-20 | 500.00 | Electronics |
-- | 108 | Harsh | Headphones | 1 | 2023-07-16 | 2000.00 | Electronics |
-- | 109 | Ishita | Headphones | 2 | 2023-07-17 | 4000.00 | Electronics |
-- | 110 | Jai | Headphones | 2 | 2023-07-18 | 4000.00 | Electronics |
-- | 111 | Kavita | Headphones | 6 | 2023-07-19 | 12000.00 | Electronics |
-- Your Query Here
Output
Click Run Button to view compiled output
28. Identify customers who have a minimum order quantity across all their orders greater than 2.
Code In Sql
-- Table Name : Orders
-- | Order_ID | Customer_Name | Product | Quantity | Order_Date | Total_Amount | CATEGORY |
-- |----------|---------------|---------------|----------|------------|--------------|--------------|
-- | 101 | Ananya | Laptop | 1 | 2023-06-15 | 55000.00 | Electronics |
-- | 102 | Bharat | Mobile Phone | 2 | 2023-06-18 | 60000.00 | Electronics |
-- | 103 | Chitra | Office Chair | 4 | 2023-07-01 | 28000.00 | Furniture |
-- | 104 | Dev | Coffee Maker | 1 | 2023-07-04 | 4000.00 | Furniture |
-- | 105 | Esha | Dining Table | 1 | 2023-07-10 | 15000.00 | Furniture |
-- | 106 | Ananya | Headphones | 1 | 2023-06-16 | 2000.00 | Electronics |
-- | 107 | Bharat | Charger | 1 | 2023-06-20 | 500.00 | Electronics |
-- | 108 | Harsh | Headphones | 1 | 2023-07-16 | 2000.00 | Electronics |
-- | 109 | Ishita | Headphones | 2 | 2023-07-17 | 4000.00 | Electronics |
-- | 110 | Jai | Headphones | 2 | 2023-07-18 | 4000.00 | Electronics |
-- | 111 | Kavita | Headphones | 6 | 2023-07-19 | 12000.00 | Electronics |
-- Your Query Here
Output
Click Run Button to view compiled output
29. Display orders where the Quantity is greater than 2 times the median quantity ordered for that product.
Code In Sql
-- Table Name : Orders
-- | Order_ID | Customer_Name | Product | Quantity | Order_Date | Total_Amount | CATEGORY |
-- |----------|---------------|---------------|----------|------------|--------------|--------------|
-- | 101 | Ananya | Laptop | 1 | 2023-06-15 | 55000.00 | Electronics |
-- | 102 | Bharat | Mobile Phone | 2 | 2023-06-18 | 60000.00 | Electronics |
-- | 103 | Chitra | Office Chair | 4 | 2023-07-01 | 28000.00 | Furniture |
-- | 104 | Dev | Coffee Maker | 1 | 2023-07-04 | 4000.00 | Furniture |
-- | 105 | Esha | Dining Table | 1 | 2023-07-10 | 15000.00 | Furniture |
-- | 106 | Ananya | Headphones | 1 | 2023-06-16 | 2000.00 | Electronics |
-- | 107 | Bharat | Charger | 1 | 2023-06-20 | 500.00 | Electronics |
-- | 108 | Harsh | Headphones | 1 | 2023-07-16 | 2000.00 | Electronics |
-- | 109 | Ishita | Headphones | 2 | 2023-07-17 | 4000.00 | Electronics |
-- | 110 | Jai | Headphones | 2 | 2023-07-18 | 4000.00 | Electronics |
-- | 111 | Kavita | Headphones | 6 | 2023-07-19 | 12000.00 | Electronics |
-- Your Query Here
Output
Click Run Button to view compiled output
30. Retrieve customers who placed orders totaling in the top 10% of all customers' cumulative totals.
Code In Sql
-- Table Name : Orders
-- | Order_ID | Customer_Name | Product | Quantity | Order_Date | Total_Amount | CATEGORY |
-- |----------|---------------|---------------|----------|------------|--------------|--------------|
-- | 101 | Ananya | Laptop | 1 | 2023-06-15 | 55000.00 | Electronics |
-- | 102 | Bharat | Mobile Phone | 2 | 2023-06-18 | 60000.00 | Electronics |
-- | 103 | Chitra | Office Chair | 4 | 2023-07-01 | 28000.00 | Furniture |
-- | 104 | Dev | Coffee Maker | 1 | 2023-07-04 | 4000.00 | Furniture |
-- | 105 | Esha | Dining Table | 1 | 2023-07-10 | 15000.00 | Furniture |
-- | 106 | Ananya | Headphones | 1 | 2023-06-16 | 2000.00 | Electronics |
-- | 107 | Bharat | Charger | 1 | 2023-06-20 | 500.00 | Electronics |
-- | 108 | Harsh | Headphones | 1 | 2023-07-16 | 2000.00 | Electronics |
-- | 109 | Ishita | Headphones | 2 | 2023-07-17 | 4000.00 | Electronics |
-- | 110 | Jai | Headphones | 2 | 2023-07-18 | 4000.00 | Electronics |
-- | 111 | Kavita | Headphones | 6 | 2023-07-19 | 12000.00 | Electronics |
-- Your Query Here
Output
Click Run Button to view compiled output
