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Clean-And-Analyze-Employee-Exit-Surveys

In this project, we'll work with exit surveys from employees of the Department of Education, Training and Employment (DETE) and the Technical and Further Education (TAFE) institute in Queensland, Australia. You can find the TAFE exit survey here and the survey for the DETE here. We've made some slight modifications to these datasets to make them easier to work with, including changing the encoding to UTF-8 (the original ones are encoded using cp1252.) In this project, we'll play the role of data analyst and pretend our stakeholders want to know the following:

  • Are employees who only worked for the institutes for a short period of time resigning due to some kind of dissatisfaction? What about employees who have been there longer?

Below is a preview of a couple columns we'll work with from the dete_survey.csv:

Syntax Description
ID An id used to identify the participant of the survey
SeparationType The reason why the person's employment ended
Cease Date The year or month the person's employment ended
DETE Start Date The year the person began employment with the DETE

Below is a preview of a couple columns we'll work with from the tafe_survey.csv:

Syntax Description
Record ID An id used to identify the participant of the survey
Reason for ceasing employment The reason why the person's employment ended
Cease Date The year or month the person's employment ended
LengthofServiceOverall. Overall Length of Service at Institute (in years) The length of the person's employment (in years)

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Data cleaning using Pandas.

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