https://github.com/tanishq-ctrl/corporate-stress-analysis
This dashboard provides interactive insights into employee stress levels, workplace dynamics, and organizational patterns through intuitive visualizations and comprehensive analysis tools.
https://github.com/tanishq-ctrl/corporate-stress-analysis
corporate-stress-analysis html-css-javascript matplotlib pandas plotly python seaborn streamlit streamlit-dashboard
Last synced: 2 months ago
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This dashboard provides interactive insights into employee stress levels, workplace dynamics, and organizational patterns through intuitive visualizations and comprehensive analysis tools.
- Host: GitHub
- URL: https://github.com/tanishq-ctrl/corporate-stress-analysis
- Owner: tanishq-ctrl
- Created: 2025-01-18T12:53:54.000Z (4 months ago)
- Default Branch: main
- Last Pushed: 2025-01-19T10:51:35.000Z (4 months ago)
- Last Synced: 2025-01-27T06:35:06.294Z (4 months ago)
- Topics: corporate-stress-analysis, html-css-javascript, matplotlib, pandas, plotly, python, seaborn, streamlit, streamlit-dashboard
- Language: Python
- Homepage: https://github.com/tanishq-ctrl/corporate-stress-analysis
- Size: 27 MB
- Stars: 2
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# 🎯 Corporate Stress Analysis Dashboard
[](https://streamlit.io/apps)
[](https://www.python.org/downloads/)
[](https://opensource.org/licenses/MIT)
A powerful dashboard for analyzing workplace stress factors and their impacts across corporate dimensions.
---
## 📋 Table of Contents
- [Overview](#-overview)
- [Data Insights](#-data-insights)
- [Features](#-features)
- [Installation](#-installation)
- [Usage](#-usage)
- [Architecture](#%EF%B8%8F-architecture)
- [Contributing](#-contributing)
- [License](#-license)
## 🔭 Overview
This dashboard provides interactive insights into employee stress levels, workplace dynamics, and organizational patterns through intuitive visualizations and comprehensive analysis tools.
Why This Dashboard?
- 📊 Real-time stress level monitoring
- 🔄 Interactive data filtering
- 📈 Comprehensive statistical analysis
- 👥 Department-wise comparisons
- ⚖️ Gender equality insights
- 🏢 Workplace dynamics visualization
## 📊 Data Insights
### 🎯 Key Findings
#### 📈 Stress Distribution
- Average level: ~5.0 (moderate)
- Uniform across departments
- Significant high-stress cases (>7)
#### 🏢 Departmental Analysis
- ~2,730 employees per department
- Consistent working hours
- Similar stress patterns
#### ⚖️ Work-Life Balance
- Variable remote work impact
- Correlation with stress levels
- Uniform working hours
#### 👥 Gender Equality
- Equal representation
- Similar stress levels
- Comparable salaries
### 📑 Data Structure
```python
Dataset Variables:
├── Stress_Level (0-10)
├── Gender
├── Department
├── Working_Hours_per_Week
├── Experience_Years
├── Sleep_Hours
├── Work_Life_Balance
├── Monthly_Salary_INR
└── Remote_Work
```
## 🚀 Features
### 🎛️ Interactive Controls
- Department filtering
- Gender selection
- Experience range
- Real-time updates
### 📊 Visualizations
- Distribution plots
- Correlation heatmaps
- Time series analysis
- Comparative charts
### 📈 Analysis Tools
- Statistical metrics
- Trend analysis
- Pattern detection
- Insight generation
## 🛠️ Architecture
```mermaid
graph TD
A[Data Source] --> B[Preprocessing]
B --> C[Analysis Engine]
C --> D[Visualization Layer]
D --> E[Interactive Dashboard]
```
### 📁 Project Structure
```
corporate-stress-analysis/
├── 📂 src/
│ ├── 📱 streamlit_app.py
│ ├── 📊 stress_analysis.py
│ └── ⚙️ config.py
├── 📂 data/
│ └── 📄 corporate_stress_dataset.csv
├── 📝 requirements.txt
└── 📖 README.md
```
## 📦 Installation
```bash
# Clone repository
git clone https://github.com/yourusername/corporate-stress-analysis.git
# Navigate to directory
cd corporate-stress-analysis
# Install dependencies
pip install -r requirements.txt
# Run dashboard
streamlit run src/streamlit_app.py
```
## 🔧 Tech Stack
### 🐍 Core
### 📊 Visualization
## 🤝 Contributing
1. Fork the Project
2. Create your Feature Branch (`git checkout -b feature/AmazingFeature`)
3. Commit your Changes (`git commit -m 'Add some AmazingFeature'`)
4. Push to the Branch (`git push origin feature/AmazingFeature`)
5. Open a Pull Request
## 📄 License
Distributed under the MIT License. See `LICENSE` for more information.