Onboarding Dashboard

This project provides an interactive dashboard for analyzing employee onboarding data using Streamlit and Plotly.

Features

Key Metrics and Insights

• Overview Statistics: Total employees, completion rates, and average assessment scores
• Status Tracking: Real-time monitoring of "On Track" vs "Delayed" employees
• Performance Analytics: Detailed assessment score analysis by role

Interactive Visualizations

• Role Performance: Dynamic bar charts showing assessment scores by role
• Status Distribution: Interactive pie charts for onboarding status
• Module Progress: Heat maps showing completion rates across roles
• Filtered Views: Custom filters for role, status, and score ranges

Data Management

• Data Cleaning: Automated preprocessing of onboarding data
• Status Calculation: Smart tracking based on module completion and start date
• Modular Design: Separated logic for better maintenance and scalability

File Structure

• onboarding_dataset.csv — The onboarding data.
• data_cleaning.py — Data loading and cleaning functions.
• status_logic.py — Onboarding status calculation.
• analysis.py — Analysis and aggregation functions.
• dashboard.py — Streamlit dashboard app.

Setup

1. Install dependencies:

   pip install streamlit plotly pandas

2. Run the dashboard:

   streamlit run dashboard.py

3. View in browser:

Launch Onboarding Dashboard

Screenshots:

Usage

• Explore onboarding trends and employee status.
• Filter and sort data interactively.
• Visualize module completion rates and assessment scores.

Customization

• Update onboarding_dataset.csv with your own data.
• Modify analysis or visualization logic in the respective Python files.

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