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Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# 👨‍💼 HR Employee Data Analysis \u0026 Visualization in Python\n\n## 📌 Overview\nThis project analyzes an **HR Employee Dataset** containing employee demographics, salaries, performance metrics, satisfaction scores, and attrition data.  \nThe main objective is to identify patterns and insights that can help HR teams improve **employee retention, engagement, and workforce diversity**.\n\n---\n\n## 🛠️ Technologies Used\n- **Python**\n- Libraries: `pandas`, `numpy`, `matplotlib`, `seaborn`\n- Data: HR Employee Dataset (CSV/Excel)\n\n---\n\n## 📊 Key Areas of Analysis\n- Demographics (gender, marital status, diversity representation)  \n- Salary \u0026 Department Analysis  \n- Performance \u0026 Engagement levels  \n- Attrition \u0026 Termination reasons  \n- Absences \u0026 Productivity impact  \n\n---\n\n## 📊 Visualizations\n\n[![HR Visualization 1](https://github.com/samiksha29-patil/HR-Employee-Data-Analysis-Visualization-in-Python/blob/main/HR1.png)](https://github.com/samiksha29-patil/HR-Employee-Data-Analysis-Visualization-in-Python/blob/main/HR1.png)\n\n[![HR Visualization 2](https://github.com/samiksha29-patil/HR-Employee-Data-Analysis-Visualization-in-Python/blob/main/HR2.png)](https://github.com/samiksha29-patil/HR-Employee-Data-Analysis-Visualization-in-Python/blob/main/HR2.png)\n\n[![HR Visualization 3](https://github.com/samiksha29-patil/HR-Employee-Data-Analysis-Visualization-in-Python/blob/main/HR3.png)](https://github.com/samiksha29-patil/HR-Employee-Data-Analysis-Visualization-in-Python/blob/main/HR3.png)\n\n[![HR Visualization 4](https://github.com/samiksha29-patil/HR-Employee-Data-Analysis-Visualization-in-Python/blob/main/HR4.png)](https://github.com/samiksha29-patil/HR-Employee-Data-Analysis-Visualization-in-Python/blob/main/HR4.png)\n\n[![HR Visualization 5](https://github.com/samiksha29-patil/HR-Employee-Data-Analysis-Visualization-in-Python/blob/main/HR5.png)](https://github.com/samiksha29-patil/HR-Employee-Data-Analysis-Visualization-in-Python/blob/main/HR5.png)\n\n---\n\n## ✅ Key Insights\n- **Production Department** has the highest employee count as well as turnover.  \n- **Voluntary attrition** is more common than involuntary.  \n- Employees with **higher engagement** show fewer absences.  \n- **Salary gaps** exist across departments.  \n- Satisfaction and performance scores are strongly linked.  \n\n---\n\n## 🚀 Conclusion\nThis analysis provides actionable insights for HR departments to:  \n- Reduce turnover by addressing key attrition factors.  \n- Align salaries across roles to improve fairness.  \n- Improve engagement and satisfaction through targeted HR initiatives.  \n\n---\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsamiksha29-patil%2Fhr-employee-data-analysis-visualization-in-python","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsamiksha29-patil%2Fhr-employee-data-analysis-visualization-in-python","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsamiksha29-patil%2Fhr-employee-data-analysis-visualization-in-python/lists"}