Done Sql5

Sql5.sql

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+# 1 Problem 1 : Report Contiguos Dates (https://leetcode.com/problems/report-contiguous-dates/ )
+
+# Solution
+with cte1 as
+(
+    select fail_date as tasked_date, 'failed' as period_state,
+        rank() over(order by fail_date) as ranks
+    from Failed
+    where fail_date between '2019-01-01' and '2019-12-31'
+union
+    select success_date as tasked_date, 'succeeded' as period_state,
+        rank() over(order by success_date) as ranks
+    from Succeeded
+    where success_date between '2019-01-01' and '2019-12-31'
+), cte2 as
+(
+    select *, rank() over(order by tasked_date) as grp_rank, rank() over(order by tasked_date) - ranks as diff
+    from cte1
+)
+select period_state, min(tasked_date ) as start_date, max(tasked_date) as end_date
+from cte2
+group by diff, period_state
+
+# 2 Problem 2 : Student Report By Geography (https://leetcode.com/problems/students-report-by-geography/ )
+
+# Solution
+with cte as
+(
+    select 
+        case when continent = 'America' then name else null end as 'America',
+        case when continent = 'Asia' then name else null end as 'Asia',
+        case when continent = 'Europe' then name else null end as 'Europe',
+        row_number() over(partition by continent order by name) as row_num
+    from Student
+)
+select min(America) as America, min(Asia) as Asia, min(Europe) as Europe
+from cte
+group by row_num
+
+# 3 Problem 3 : Average Salary Department vs Company (https://leetcode.com/problems/average-salary-departments-vs-company/solution/ )
+
+# Solution1
+with cte1 as
+(
+    select date_format(s.pay_date, '%Y-%m') as pay_month, e.department_id, avg(s.amount) as avg_dept_salary
+    from Salary s
+    join Employee e
+    on s.employee_id = e.employee_id
+    group by pay_month, e.department_id
+), 
+cte2 as
+(
+    select date_format(pay_date, '%Y-%m') as pay_month, avg(amount) as avg_company_salary
+    from Salary
+    group by date_format(pay_date, '%Y-%m')
+)
+select c1.pay_month, c1.department_id,
+    case 
+        when c1.avg_dept_salary < c2.avg_company_salary then 'lower'
+        when c1.avg_dept_salary = c2.avg_company_salary then 'same'
+        else 'higher'
+    end as comparison
+from cte1 c1
+join cte2 c2
+on c1.pay_month = c2.pay_month
+
+# Solution2
+with cte as
+(
+    select date_format(s.pay_date, '%Y-%m') as pay_month, e.department_id, 
+    avg(s.amount) over(partition by date_format(s.pay_date, '%Y-%m')) as avg_company_salary,
+    avg(s.amount) over(partition by e.department_id, date_format(s.pay_date, '%Y-%m')) as avg_dept_salary
+    from Salary s
+    join Employee e
+    on s.employee_id = e.employee_id
+)
+select pay_month, department_id,
+    case 
+        when avg_dept_salary < avg_company_salary then 'lower'
+        when avg_dept_salary = avg_company_salary then 'same'
+        else 'higher'
+    end as comparison
+from cte
+group by department_id, pay_month 
+order by pay_month desc
+
+# 4 Problem 4 : Game Play Analysis I (https://leetcode.com/problems/game-play-analysis-i/ )
+
+# Solution 1
+select player_id, min(event_date) as first_login
+from Activity
+group by player_id
+
+# Solution2
+select distinct player_id, min(event_date) over(partition by player_id) as first_login
+from Activity
+
+# Solution3 (Row_number() and Rank() can be used as well instead of Dense_rank())
+with cte as
+(
+    select player_id, event_date as first_login, 
+    dense_rank() over(partition by player_id order by event_date) as ranks
+    from Activity 
+)
+select player_id, first_login
+from cte
+where ranks = 1
+
+# Solution4 (Row_number() and Rank() can be used as well instead of Dense_rank())
+select a.player_id, a.event_date as first_login 
+from (select b.player_id, b.event_date, 
+    dense_rank() over(partition by b.player_id order by b.event_date) as ranks
+    from Activity b) as a
+where a.ranks = 1
+
+# Solution5
+select distinct(player_id), first_value(event_date) over(partition by player_id order by event_date) as first_login
+from Activity
+
+# Solution6
+select distinct(player_id), 
+last_value(event_date) over(partition by player_id order by event_date desc range between unbounded preceding and unbounded following) as first_login
+from Activity
+
+# Solution7
+select distinct(player_id), 
+last_value(event_date) over(partition by player_id order by event_date desc rows between unbounded preceding and unbounded following) as first_login
+from Activity