Question: https://leetcode.com/problems/manager...
SQL Schema:
Create table if not exists Employees ( emp_id int, emp_name varchar(50), dep_id int, position varchar(30))
Truncate table Employees
insert into Employees (emp_id, emp_name, dep_id, position) values ('156', 'Michael', '107', 'Manager')
insert into Employees (emp_id, emp_name, dep_id, position) values ('112', 'Lucas', '107', 'Consultant')
insert into Employees (emp_id, emp_name, dep_id, position) values ('8', 'Isabella', '101', 'Manager')
insert into Employees (emp_id, emp_name, dep_id, position) values ('160', 'Joseph', '100', 'Manager')
insert into Employees (emp_id, emp_name, dep_id, position) values ('80', 'Aiden', '100', 'Engineer')
insert into Employees (emp_id, emp_name, dep_id, position) values ('190', 'Skylar', '100', 'Freelancer')
insert into Employees (emp_id, emp_name, dep_id, position) values ('196', 'Stella', '101', 'Coordinator')
insert into Employees (emp_id, emp_name, dep_id, position) values ('167', 'Audrey', '100', 'Consultant')
insert into Employees (emp_id, emp_name, dep_id, position) values ('97', 'Nathan', '101', 'Supervisor')
insert into Employees (emp_id, emp_name, dep_id, position) values ('128', 'Ian', '101', 'Administrator')
insert into Employees (emp_id, emp_name, dep_id, position) values ('81', 'Ethan', '107', 'Administrator')
Pandas Schema:
data = [[156, 'Michael', 107, 'Manager'], [112, 'Lucas', 107, 'Consultant'], [8, 'Isabella', 101, 'Manager'], [160, 'Joseph', 100, 'Manager'], [80, 'Aiden', 100, 'Engineer'], [190, 'Skylar', 100, 'Freelancer'], [196, 'Stella', 101, 'Coordinator'], [167, 'Audrey', 100, 'Consultant'], [97, 'Nathan', 101, 'Supervisor'], [128, 'Ian', 101, 'Administrator'], [81, 'Ethan', 107, 'Administrator']]
employees = pd.DataFrame(data, columns=['emp_id', 'emp_name', 'dep_id', 'position']).astype({
'emp_id': 'Int64',
'emp_name': 'object',
'dep_id': 'Int64',
'position': 'object'
})
#leetcodesolutions #datascience #sql