[force deduction 10 days SQL introduction] Day9 control flow

1393. Capital gains and losses on shares

Stocks  surface ：
+---------------+---------+
| Column Name   | Type    |
+---------------+---------+
| stock_name    | varchar |
| operation     | enum    |
| operation_day | int     |
| price         | int     |
+---------------+---------+
(stock_name, day)  It's the primary key of this table 
operation  Column uses an enumeration type , Include ：('Sell','Buy')
 Each row of this table represents a table named  stock_name  A stock in  operation_day  The operating price of this day .
 Guarantee every time the stock 'Sell' Before operation , There are corresponding 'Buy' operation .
 Write a SQL Query to report the capital gains and losses of each stock .

 The capital gains and losses of stocks are all the gains or losses after one or more purchases and sales of stocks .
 Just return the results in any order .

Stocks  surface :
+---------------+-----------+---------------+--------+
| stock_name    | operation | operation_day | price  |
+---------------+-----------+---------------+--------+
| Leetcode      | Buy       | 1             | 1000   |
| Corona Masks  | Buy       | 2             | 10     |
| Leetcode      | Sell      | 5             | 9000   |
| Handbags      | Buy       | 17            | 30000  |
| Corona Masks  | Sell      | 3             | 1010   |
| Corona Masks  | Buy       | 4             | 1000   |
| Corona Masks  | Sell      | 5             | 500    |
| Corona Masks  | Buy       | 6             | 1000   |
| Handbags      | Sell      | 29            | 7000   |
| Corona Masks  | Sell      | 10            | 10000  |
+---------------+-----------+---------------+--------+
Result  surface :
+---------------+-------------------+
| stock_name    | capital_gain_loss |
+---------------+-------------------+
| Corona Masks  | 9500              |
| Leetcode      | 8000              |
| Handbags      | -23000            |
+---------------+-------------------+

Analysis of the answer

Group by stock name , The operation is to take the negative of buying , Correct the sold , Sum up

SELECT stock_name, sum(IF(operation = 'Buy', -price, price)) capital_gain_loss
FROM Stocks
GROUP BY stock_name

1407. Top ranked travelers

 surface ：Users
+---------------+---------+
| Column Name   | Type    |
+---------------+---------+
| id            | int     |
| name          | varchar |
+---------------+---------+
id  Is the primary key of the form .name  It's the user's name .

 surface ：Rides
+---------------+---------+
| Column Name   | Type    |
+---------------+---------+
| id            | int     |
| user_id       | int     |
| distance      | int     |
+---------------+---------+
id  Is the primary key of the form .user_id  It's from the users of this trip  id,  The travel distance of this user is  distance .

 Write a paragraph  SQL ,  Report the travel distance of each user .
 The returned result form , With  travelled_distance  Descending order  , If two or more users travel the same distance ,  Then again  name  Ascending order  .

Users  surface ：
+------+-----------+
| id   | name      |
+------+-----------+
| 1    | Alice     |
| 2    | Bob       |
| 3    | Alex      |
| 4    | Donald    |
| 7    | Lee       |
| 13   | Jonathan  |
| 19   | Elvis     |
+------+-----------+

Rides  surface ：
+------+----------+----------+
| id   | user_id  | distance |
+------+----------+----------+
| 1    | 1        | 120      |
| 2    | 2        | 317      |
| 3    | 3        | 222      |
| 4    | 7        | 100      |
| 5    | 13       | 312      |
| 6    | 19       | 50       |
| 7    | 7        | 120      |
| 8    | 19       | 400      |
| 9    | 7        | 230      |
+------+----------+----------+

Result  surface ：
+----------+--------------------+
| name     | travelled_distance |
+----------+--------------------+
| Elvis    | 450                |
| Lee      | 450                |
| Bob      | 317                |
| Jonathan | 312                |
| Alex     | 222                |
| Alice    | 120                |
| Donald   | 0                  |
+----------+--------------------+

Analysis of the answer

Right link , Press id grouping , Then in descending order of distance , Name ascending

SELECT A.name, sum(IFNULL(B.distance, 0)) travelled_distance 
FROM Users A LEFT JOIN Rides B ON A.id = B.user_id
GROUP BY A.id
ORDER BY travelled_distance DESC, A.name ASC

1158. Market analysis I

Table: Users
+----------------+---------+
| Column Name    | Type    |
+----------------+---------+
| user_id        | int     |
| join_date      | date    |
| favorite_brand | varchar |
+----------------+---------+
 The primary key of this table is  user_id.
 The table describes the user information of the shopping website , Users can buy and sell goods on this website .
 
Table: Orders
+---------------+---------+
| Column Name   | Type    |
+---------------+---------+
| order_id      | int     |
| order_date    | date    |
| item_id       | int     |
| buyer_id      | int     |
| seller_id     | int     |
+---------------+---------+
 The primary key of this table is  order_id. The foreign key is  item_id  and （buyer_id,seller_id）.
 
Table: Items
+---------------+---------+
| Column Name   | Type    |
+---------------+---------+
| item_id       | int     |
| item_brand    | varchar |
+---------------+---------+
 The primary key of this table is  item_id.
 Please write a SQL Statement to query the registration date and date of each user  2019  Total number of orders as buyers in .
 With   In any order   Return result table .

 Input ：
Users  surface :
+---------+------------+----------------+
| user_id | join_date  | favorite_brand |
+---------+------------+----------------+
| 1       | 2018-01-01 | Lenovo         |
| 2       | 2018-02-09 | Samsung        |
| 3       | 2018-01-19 | LG             |
| 4       | 2018-05-21 | HP             |
+---------+------------+----------------+
Orders  surface :
+----------+------------+---------+----------+-----------+
| order_id | order_date | item_id | buyer_id | seller_id |
+----------+------------+---------+----------+-----------+
| 1        | 2019-08-01 | 4       | 1        | 2         |
| 2        | 2018-08-02 | 2       | 1        | 3         |
| 3        | 2019-08-03 | 3       | 2        | 3         |
| 4        | 2018-08-04 | 1       | 4        | 2         |
| 5        | 2018-08-04 | 1       | 3        | 4         |
| 6        | 2019-08-05 | 2       | 2        | 4         |
+----------+------------+---------+----------+-----------+
Items  surface :
+---------+------------+
| item_id | item_brand |
+---------+------------+
| 1       | Samsung    |
| 2       | Lenovo     |
| 3       | LG         |
| 4       | HP         |
+---------+------------+
 Output ：
+-----------+------------+----------------+
| buyer_id  | join_date  | orders_in_2019 |
+-----------+------------+----------------+
| 1         | 2018-01-01 | 1              |
| 2         | 2018-02-09 | 2              |
| 3         | 2018-01-19 | 0              |
| 4         | 2018-05-21 | 0              |
+-----------+------------+----------------+

Analysis of the answer

Users Table and Orders Table left connection , Press userId grouping ,2019 The sum of

SELECT A.user_id buyer_id, join_date, sum(IF(YEAR(B.order_date) = 2019, 1, 0)) orders_in_2019 
FROM users A LEFT JOIN orders B ON A.user_id = B.buyer_id
GROUP BY A.user_id