Humach HR: Attrition Analysis
Analyse attrition drivers while separating predictive association from causal or fair employment decisions.
Download mini_hr.csvUse Python, SQL, Excel or your preferred workflow unless a task specifies otherwise.
Project dataset
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| employee_id | tenure_years | overtime | satisfaction | salary | department | attrition |
|---|---|---|---|---|---|---|
| E001 | 6 | 0 | 3 | 49100 | Tech | 0 |
| E002 | 11 | 0 | 5 | 53200 | Ops | 0 |
| E003 | 4 | 0 | 2 | 57300 | HR | 0 |
| E004 | 9 | 1 | 4 | 61400 | Sales | 0 |
| E005 | 2 | 0 | 1 | 65500 | Tech | 1 |
| E006 | 7 | 0 | 3 | 69600 | Ops | 0 |
| E007 | 12 | 0 | 5 | 73700 | HR | 0 |
| E008 | 5 | 1 | 2 | 77800 | Sales | 1 |
| E009 | 10 | 0 | 4 | 81900 | Tech | 0 |
| E010 | 3 | 0 | 1 | 86000 | Ops | 0 |
| E011 | 8 | 0 | 3 | 90100 | HR | 0 |
| E012 | 1 | 1 | 5 | 94200 | Sales | 1 |
| E013 | 6 | 0 | 2 | 98300 | Tech | 0 |
| E014 | 11 | 0 | 4 | 102400 | Ops | 0 |
| E015 | 4 | 0 | 1 | 106500 | HR | 0 |
| E016 | 9 | 1 | 3 | 110600 | Sales | 0 |
| E017 | 2 | 0 | 5 | 114700 | Tech | 0 |
| E018 | 7 | 0 | 2 | 118800 | Ops | 0 |
| E019 | 12 | 0 | 4 | 122900 | HR | 0 |
| E020 | 5 | 1 | 1 | 127000 | Sales | 1 |
| E021 | 10 | 0 | 3 | 46100 | Tech | 0 |
| E022 | 3 | 0 | 5 | 50200 | Ops | 0 |
| E023 | 8 | 0 | 2 | 54300 | HR | 0 |
| E024 | 1 | 1 | 4 | 58400 | Sales | 1 |
| E025 | 6 | 0 | 1 | 62500 | Tech | 0 |
| E026 | 11 | 0 | 3 | 66600 | Ops | 0 |
| E027 | 4 | 0 | 5 | 70700 | HR | 0 |
| E028 | 9 | 1 | 2 | 74800 | Sales | 1 |
| E029 | 2 | 0 | 4 | 78900 | Tech | 0 |
| E030 | 7 | 0 | 1 | 83000 | Ops | 0 |
| E031 | 12 | 0 | 3 | 87100 | HR | 0 |
| E032 | 5 | 1 | 5 | 91200 | Sales | 0 |
| E033 | 10 | 0 | 2 | 95300 | Tech | 0 |
| E034 | 3 | 0 | 4 | 99400 | Ops | 0 |
| E035 | 8 | 0 | 1 | 103500 | HR | 0 |
| E036 | 1 | 1 | 3 | 107600 | Sales | 1 |
| E037 | 6 | 0 | 5 | 111700 | Tech | 0 |
| E038 | 11 | 0 | 2 | 115800 | Ops | 0 |
| E039 | 4 | 0 | 4 | 119900 | HR | 0 |
| E040 | 9 | 1 | 1 | 124000 | Sales | 1 |
| E041 | 2 | 0 | 3 | 128100 | Tech | 0 |
| E042 | 7 | 0 | 5 | 47200 | Ops | 0 |
| E043 | 12 | 0 | 2 | 51300 | HR | 0 |
| E044 | 5 | 1 | 4 | 55400 | Sales | 0 |
| E045 | 10 | 0 | 1 | 59500 | Tech | 0 |
| E046 | 3 | 0 | 3 | 63600 | Ops | 0 |
| E047 | 8 | 0 | 5 | 67700 | HR | 0 |
| E048 | 1 | 1 | 2 | 71800 | Sales | 1 |
| E049 | 6 | 0 | 4 | 75900 | Tech | 0 |
| E050 | 11 | 0 | 1 | 80000 | Ops | 0 |
Project workspace
Analyse → validate → submit.
Numeric and decision tasks are auto-checked. Written reasoning is checked for completeness and key ideas, then included in your local submission report.
0/5 validated
How many employees have attrition=1?
What is mean satisfaction?
Which statement is safest?
Name one fairness or governance check before using attrition predictions operationally.
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