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2051. The Category of Each Member in the Store
Description
Table: Members
+-------------+---------+ | Column Name | Type | +-------------+---------+ | member_id | int | | name | varchar | +-------------+---------+ member_id is the primary key column for this table. Each row of this table indicates the name and the ID of a member.
Table: Visits
+-------------+------+ | Column Name | Type | +-------------+------+ | visit_id | int | | member_id | int | | visit_date | date | +-------------+------+ visit_id is the primary key column for this table. member_id is a foreign key to member_id from the Members table. Each row of this table contains information about the date of a visit to the store and the member who visited it.
Table: Purchases
+----------------+------+ | Column Name | Type | +----------------+------+ | visit_id | int | | charged_amount | int | +----------------+------+ visit_id is the primary key column for this table. visit_id is a foreign key to visit_id from the Visits table. Each row of this table contains information about the amount charged in a visit to the store.
A store wants to categorize its members. There are three tiers:
- "Diamond": if the conversion rate is greater than or equal to
80
. - "Gold": if the conversion rate is greater than or equal to
50
and less than80
. - "Silver": if the conversion rate is less than
50
. - "Bronze": if the member never visited the store.
The conversion rate of a member is (100 * total number of purchases for the member) / total number of visits for the member
.
Write an SQL query to report the id, the name, and the category of each member.
Return the result table in any order.
The query result format is in the following example.
Example 1:
Input: Members table: +-----------+---------+ | member_id | name | +-----------+---------+ | 9 | Alice | | 11 | Bob | | 3 | Winston | | 8 | Hercy | | 1 | Narihan | +-----------+---------+ Visits table: +----------+-----------+------------+ | visit_id | member_id | visit_date | +----------+-----------+------------+ | 22 | 11 | 2021-10-28 | | 16 | 11 | 2021-01-12 | | 18 | 9 | 2021-12-10 | | 19 | 3 | 2021-10-19 | | 12 | 11 | 2021-03-01 | | 17 | 8 | 2021-05-07 | | 21 | 9 | 2021-05-12 | +----------+-----------+------------+ Purchases table: +----------+----------------+ | visit_id | charged_amount | +----------+----------------+ | 12 | 2000 | | 18 | 9000 | | 17 | 7000 | +----------+----------------+ Output: +-----------+---------+----------+ | member_id | name | category | +-----------+---------+----------+ | 1 | Narihan | Bronze | | 3 | Winston | Silver | | 8 | Hercy | Diamond | | 9 | Alice | Gold | | 11 | Bob | Silver | +-----------+---------+----------+ Explanation: - User Narihan with id = 1 did not make any visits to the store. She gets a Bronze category. - User Winston with id = 3 visited the store one time and did not purchase anything. The conversion rate = (100 * 0) / 1 = 0. He gets a Silver category. - User Hercy with id = 8 visited the store one time and purchased one time. The conversion rate = (100 * 1) / 1 = 1. He gets a Diamond category. - User Alice with id = 9 visited the store two times and purchased one time. The conversion rate = (100 * 1) / 2 = 50. She gets a Gold category. - User Bob with id = 11 visited the store three times and purchased one time. The conversion rate = (100 * 1) / 3 = 33.33. He gets a Silver category.
Solutions
-
# Write your MySQL query statement below SELECT m.member_id, name, CASE WHEN count(v.visit_id) = 0 THEN 'Bronze' WHEN 100 * count(charged_amount) / count( v.visit_id ) >= 80 THEN 'Diamond' WHEN 100 * count(charged_amount) / count(v.visit_id) >= 50 THEN 'Gold' ELSE 'Silver' END AS category FROM Members AS m LEFT JOIN Visits AS v ON m.member_id = v.member_id LEFT JOIN Purchases AS p ON v.visit_id = p.visit_id GROUP BY member_id;