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Synthetic Employee Workforce Data
Synthetic Tabular Data
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About
This dataset contains information about employee salaries within a company, with each row representing a distinct employee. It provides details such as age, gender, education level, job title, years of experience, and annual salary in US dollars. The dataset's creation is solely for educational purposes, and any commercial use is strictly prohibited. It is important to note that this dataset was generated by large language models and not gathered from actual data sources.
Columns
- Age: Represents the age of each employee in years. Values are numeric.
- Gender: Indicates the gender of each employee, either male or female. Values are categorical.
- Education Level: Details the educational attainment of each employee, including options such as high school, bachelor's degree, master's degree, or PhD. Values are categorical.
- Job Title: Specifies the job title of each employee, which can vary widely, e.g., manager, analyst, engineer, or administrator. Values are categorical.
- Years of Experience: Denotes the number of years of work experience each employee possesses. Values are numeric.
- Salary: Represents the annual salary of each employee in US dollars. Values are numeric and can fluctuate based on factors like job title, experience, and education.
Distribution
The dataset is provided in a CSV file format, specifically "Salary Data.csv", with a size of 19.36 kB. It consists of 6 columns and 373 valid records, with 2 records missing across various columns. Each row is structured to represent a distinct employee's data.
Usage
This dataset is ideally suited for educational applications, particularly in areas of data analytics and regression modelling. It can be used to explore relationships between employee attributes and salary, build predictive models for salary estimation, and train machine learning algorithms.
Coverage
The dataset focuses on employee attributes and salaries within a generic company context. Salary values are presented in US dollars. While specific geographic or time ranges are not defined, the data encompasses a range of ages (approximately 23 to 53 years) and includes demographic splits by gender (52% Male, 48% Female, 1% Other) and education level (60% Bachelor's, 26% Master's, 14% Other). It features a diverse set of job titles. It is important to remember that this dataset is synthetically generated by large language models.
License
Attribution 4.0 International (CC BY 4.0)
Who Can Use It
This dataset is particularly useful for:
- Students and Academics: For learning about data analysis, predictive modelling, and machine learning, especially in the context of human resources and economic studies.
- Beginners in Data Science: To practice regression techniques and data exploration on a clean, structured dataset.
- Researchers: For exploring hypothetical scenarios related to salary determinants without relying on real-world sensitive data.
Dataset Name Suggestions
- Employee Salary Prediction Dataset
- Synthetic Employee Workforce Data
- Staff Salary Insights Dataset
- HR Salary Analytics Sample
- Employee Compensation Model Data
Attributes
Original Data Source: Synthetic Employee Workforce Data
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