Data
Sample---Employees-Monthly-Salary

Sample---Employees-Monthly-Salary

active ARFF CC0: Public Domain Visibility: public Uploaded 23-03-2022 by Onur Yildirim
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Context This is a sample dataset to explore key insights, EDA, and to perform statistical simulations. Content This Dataset contains Gross and Net salary of each Employee with Tax deduction Inspiration Do male employees earn significantly more than female employees? Are there any departments paying significantly low salaries in the organization? What is the relation between gender and leadership roles in the organization? What is the relation between age and leadership roles in the organization? Are Data Scientists getting paid significantly more than others in this company? Does the salary depend on Age?

12 features

EmpID (ignore)numeric1802 unique values
0 missing
Namestring1802 unique values
0 missing
Genderstring2 unique values
0 missing
Date_of_Birthstring1571 unique values
0 missing
Agenumeric34 unique values
0 missing
Join_Datestring705 unique values
0 missing
Tenure_in_org_in_monthsnumeric156 unique values
0 missing
GROSSnumeric1694 unique values
0 missing
Net_Paynumeric1792 unique values
0 missing
Deductionnumeric1770 unique values
0 missing
Deduction_percentagenumeric1461 unique values
0 missing
Designationstring390 unique values
0 missing
Departmentstring154 unique values
0 missing

19 properties

1802
Number of instances (rows) of the dataset.
12
Number of attributes (columns) of the dataset.
Number of distinct values of the target attribute (if it is nominal).
0
Number of missing values in the dataset.
0
Number of instances with at least one value missing.
6
Number of numeric attributes.
0
Number of nominal attributes.
0.01
Number of attributes divided by the number of instances.
50
Percentage of numeric attributes.
Percentage of instances belonging to the most frequent class.
0
Percentage of nominal attributes.
Number of instances belonging to the most frequent class.
Percentage of instances belonging to the least frequent class.
Number of instances belonging to the least frequent class.
0
Number of binary attributes.
0
Percentage of binary attributes.
0
Percentage of instances having missing values.
Average class difference between consecutive instances.
0
Percentage of missing values.

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