Binning employee experience levels in Python (Pandas)
Question
Below is a snippet from a table that contains information about employees that work at Company XYZ:
| employee_name | employee_id | date_joined | age | yrs_of_experience |
|---|---|---|---|---|
| Andy | 123456 | 2015-02-15 | 45 | 24 |
| Beth | 789456 | 2014-02-15 | 36 | 15 |
| Cindy | 654123 | 2017-05-16 | 34 | 14 |
| Dale | 963852 | 2018-01-15 | 25 | 4 |
Company XYZ is looking to create a report that groups the experience of its employees into 3 simple categories, with the following bins (inclusive):
- 0-5 Low
- 6-15 Medium
- 16+ High
Additionally, you can assume the data is clean and there are no employees with negative or non-numerical years of experience.
Write code in Python (using Pandas) to create a new column in the dataframe, called 'experience_binned', that groups employees as requested above.