Cleaning and analyzing employee data


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 NaN 36 15
Cindy 654123 2017-05-16 34 14
Dale 963852 2018-01-15 25 4

Company XYZ recently migrated database systems causing some of the date_joined records to be NULL. You're told by an analyst in human resources NULL records for the date_joined field indicates the employees joined prior to 2010. You also find out there are multiple employees with the same name and duplicate records for some employees.

Given this, write code to find the number of employees that joined each month. You can group all of the null values as Dec 1, 2009.

Click here to view this problem in an interactive Colab (Jupyter) notebook.


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