A public library keeps a directory of registered members and a separate record of every book loan. The engagement team wants to identify how many members did not borrow anything during a particular week.
Table: library_members
+-------------+--------------+
| Column Name | Type |
+-------------+--------------+
| member_id | integer |
| branch | varchar(255) |
+-------------+--------------+
+-------------+--------------+
| Column Name | Type |
+-------------+--------------+
| member_id | integer |
| branch | varchar(255) |
+-------------+--------------+
member_id is the primary key. Each row represents one registered library member.
Table: book_loans
+-------------+---------+
| Column Name | Type |
+-------------+---------+
| loan_id | integer |
| member_id | integer |
| book_id | integer |
| loan_date | date |
+-------------+---------+
+-------------+---------+
| Column Name | Type |
+-------------+---------+
| loan_id | integer |
| member_id | integer |
| book_id | integer |
| loan_date | date |
+-------------+---------+
loan_id is the primary key. member_id references library_members.member_id. Each row records one book borrowed by a member.
Count the registered members who borrowed zero books from 2026-04-06 through 2026-04-12, inclusive.
Start from the complete library_members population. A member who has never borrowed a book must be counted, as must a member whose loans all fall outside the specified seven-day window. Multiple loans inside the window still make a member active only once.
Return one row with the result in a column named inactive_member_count.
Example
Input:
library_members table:
+-----------+--------+
| member_id | branch |
+-----------+--------+
| 1 | North |
| 2 | South |
| 3 | East |
+-----------+--------+
library_members table:
+-----------+--------+
| member_id | branch |
+-----------+--------+
| 1 | North |
| 2 | South |
| 3 | East |
+-----------+--------+
