﻿ SQL Challenges-1: Compare average purchase quantiry of a products - w3resource

# SQL Challenges-1: Compare the purchasing status of the average purchase quantity of products of a category to the average pruchase quantity of the distributor

## SQL Challenges-1: Exercise-52 with Solution

From the following tables write a query in SQL to compare the purchasing status of the average purchase quantity of products of a category to the average pruchase quantity of the distributor. Return purchase month, category_id and purchase status.

Input:

Table: product

Structure:

FieldTypeNullKeyDefaultExtra
product_idintNOPRI
category_idintNO

Data:

product_idcategory_id
8001150
8002160
8003160
8004150
8005160

Table: purchase

Structure:

FieldTypeNullKeyDefaultExtra
purchase_nointNOPRI
item_codeintNOMUL
purchase_qtyintYES
purchase_datedateYES

Data:

purchase_noitem_codepurchase_qtypurchase_date
100180012402019-12-17
100280021502019-12-17
100380031752020-11-15
100480041502019-12-17
100580051452019-12-05
100680011502020-01-05
100780022002020-01-15
100880031502020-12-17
100980012002020-01-28
101080021802020-02-07
101180013002020-02-25
101280051002020-01-27

Sample Solution:

SQL Code(MySQL):

``````CREATE TABLE  product(
product_id INTEGER(5) NOT NULL unique,
category_id   INTEGER(4) NOT NULL);

insert into product values(8001,150);
insert into product values(8002,160);
insert into product values(8003,160);
insert into product values(8004,150);
insert into product values(8005,160);

CREATE TABLE purchase (
purchase_no INTEGER(5) NOT NULL unique,
item_code   INTEGER(4) NOT NULL,
purchase_qty  integer(5),
purchase_date  date,
foreign key (item_code) references product(product_id));

insert into purchase values(1001,8001,240,'2019-12-17');
insert into purchase values(1002,8002,150,'2019-12-17');
insert into purchase values(1003,8003,175,'2020-11-15');
insert into purchase values(1004,8004,150,'2019-12-17');
insert into purchase values(1005,8005,145,'2019-12-05');
insert into purchase values(1006,8001,150,'2020-01-05');
insert into purchase values(1007,8002,200,'2020-01-15');
insert into purchase values(1008,8003,150,'2020-12-17');
insert into purchase values(1009,8001,200,'2020-01-28');
insert into purchase values(1010,8002,180,'2020-02-07');
insert into purchase values(1011,8001,300,'2020-02-25');
insert into purchase values(1012,8005,100,'2020-01-27');

SELECT pur.month purchase_month,category_id,
CASE WHEN category_average > distributor_average then 'increase'
WHEN category_average < distributor_average then 'decrease'
WHEN category_average = distributor_average then 'remain same'
END AS purchase_status
FROM
(SELECT SUBSTR(purchase_date,1,7) month,category_id,avg(purchase_qty) category_average
FROM purchase JOIN product ON purchase.item_code = product.product_id
group by 1,2) pur JOIN
(SELECT SUBSTR(purchase_date,1,7) month,avg(purchase_qty) distributor_average
FROM purchase group by 1) dis
ON pur.month = dis.month;
```
```

Sample Output:

```purchase_month|category_id|purchase_status|
--------------+-----------+---------------+
2019-12       |        150|increase       |
2020-01       |        150|increase       |
2020-02       |        150|increase       |
2019-12       |        160|decrease       |
2020-01       |        160|decrease       |
2020-02       |        160|decrease       |
2020-11       |        160|remain same    |
2020-12       |        160|remain same    |
```

SQL Code Editor: