There are the following columns:

Balance_date - that is the date for which a given attendance type was recorded.

Buckets - this is column that represents a type of attendance code used for an employee for a given balance_date.

ID - employee ID

Employee_start_date - when the employee started to work for you

Supervisor_ID - who is the direct manager of the employee

Hours - amount of hours coded for a given bucket and balance_date

For example: the below data shows that an employee who started work on August 7^th 2018 had an unexcused absence for 10hours on Nov 2^nd 2018.

There are the following bucket types:

Exclude - errors to be removed

excusedAbsence - absence that is considered excused: blood donation, medical checks for work

HOD - Holiday on demand

Holiday - regular holiday

Overtime - people working longer than scheduled

Sickness - employee on a sick leave

Unexcused - unexcused absence - employee did not come to work at a given scheduled day and there is no sick leave note

workingHours - employee came to work on a scheduled day.

Questions to be answered:

1. What is the % share of each of the buckets month over month?
2. How does point 1 look per supervisor?
3. When clicking on unexcused and sickness buckets in point 1 please show the employees with the highest amount of hours in the investigated buckets.
4. What is the average % of unplanned absence dependent on the tenure the employee is at work?

Please show it on a graph - bar or line chart. Tenure between 0 and 50 weeks is enough.