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Data Analytics Part 1
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EmployeeID | Age | Department | YearsOfExperience | Salary | PerformanceRating | EducationLevel | Gender | MaritalStatus | OvertimeHours | PromotionReceived | |
---|---|---|---|---|---|---|---|---|---|---|---|
1 | 30 | Engineering | 5 | 60000 | Excellent | Bachelor's | Male | Married | 10 | Yes | |
2 | 35 | Marketing | 8 | 65000 | Good | Master's | Female | Single | 5 | No | |
3 | 45 | Engineering | 15 | 85000 | Excellent | Bachelor's | Male | Married | 15 | No | |
4 | 28 | Finance | 3 | 55000 | Fair | Bachelor's | Female | Married | 3 | Yes | |
5 | 40 | HR | 10 | 70000 | Good | Master's | Male | Single | 8 | Yes | |
6 | 33 | Finance | 6 | 62000 | Fair | Bachelor's | Female | Married | 4 | No | |
7 | 38 | Marketing | 12 | 75000 | Excellent | Master's | Male | Married | 12 | Yes | |
8 | 42 | Engineering | 18 | 90000 | Excellent | PhD | Female | Single | 20 | No | |
9 | 25 | HR | 2 | 50000 | Fair | Bachelor's | Male | Single | 2 | No | |
10 | 37 | Engineering | 14 | 80000 | Good | Master's | Female | Married | 10 | Yes |
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