An interactive enterprise-grade HR Analytics Dashboard built using Python, Streamlit, Pandas, and Plotly. This application enables executives and HR leaders to analyze workforce demographics, compensation structures, experience trends, and payroll allocations through dynamic multi-criteria filtering and interactive visualizations.
- Executive KPI Cards: Real-time tracking of Total Headcount, Average Salary, Total Payroll Budget, and Average Experience with dynamic benchmark deltas.
- Global Cascading Filters: Multi-criteria sidebar filters (Department, City, Salary Range, Experience Range) for granular data analysis.
- 7 Interactive Plotly Visualizations:
- 🏢 Donut Chart: Department Workforce Share (%)
- 🗺️ Treemap Chart: Total Payroll Allocation by Department
- 💰 Violin Plot: Salary Density & Pay Range Distribution
- 📈 Bubble Scatter Chart: Experience vs. Salary Growth (Bubble size = Age)
- 📊 Grouped Bar Chart: Average Salary & Experience Depth Matrix
- 📍 Horizontal Bar Chart: City-wise Employee Headcount Concentration
- 🎂 Histogram: Employee Age Group Demographics
- Automated Executive Insights: Real-time AI-like insight engine highlighting top-paying departments and workforce coverage.
- Cross-Tabulation Pivot Table: Executive matrix showing Headcount, Average Salary, and Total Expense across Departments and Locations.
- Conditional Styled Data Table: Heatmap-style formatting (
Pandas Styler) highlighting min/max salary brackets. - Data Export: One-click export functionality to download filtered views in CSV format.
- Programming Language: Python
- Libraries: Streamlit, Pandas, Plotly Express, OpenPyXL
- Data Analysis: Data Wrangling, Aggregations, Pivot Tables, Conditional Styling
- Business Intelligence: Custom Metric KPIs, Advanced Visualizations
- Clone the Repository:
git clone [https://github.com/kapilverma/employee_data_analysis.git](https://github.com/kapilverma/employee_data_analysis.git) cd employee_data_analysis