A comprehensive Python-based data analysis system for hospital patient management and treatment cost analysis
Features • Installation • Usage • Documentation • Team
The Hospital Patient Data Analysis System is a modular Python application designed to analyze patient demographics, treatment costs, and medical data patterns. Built with a focus on simplicity and educational value, this system demonstrates core data science concepts using real-world healthcare scenarios.
- Analyze treatment cost patterns across different diseases
- Identify high-cost medical treatments and patient demographics
- Classify patients into meaningful age groups for targeted analysis
- Demonstrate pandas data manipulation and analysis techniques
- Disease Cost Analysis: Calculate average treatment costs by disease type
- Expensive Treatment Identification: Find and rank the most costly treatments
- Age Group Classification: Categorize patients using custom classification logic
- Interactive Menu System: User-friendly command-line interface
- About Project: Project details and team information
- Modular Architecture: Separated into focused, reusable components
- Clean Code Structure: Beginner-friendly with clear function separation
- Real Dataset: 15 patient records with authentic Indian demographics
- Pandas Integration: Leverages powerful data manipulation capabilities
Hospital_management/
├── 📄 Hospital_Management.py # Main application entry point
├── 📄 diseases.py # Disease cost analysis module
├── 📄 costs.py # Expensive treatments module
├── 📄 ages.py # Age group classification module
├── 📊 hospital_data.csv # Patient dataset (15 records)
└── 📘 README.md # This file
# 1. Clone the repository
git clone https://github.com/yourusername/hospital-patient-analysis.git
cd hospital-patient-analysis
# 2. Install pandas
pip install pandas
# 3. Run the program
python Hospital_Management.pypython Hospital_Management.pyHOSPITAL MANAGEMENT SYSTEM
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1. View All Data # Display complete patient dataset
2. Disease Analysis # Average costs by disease type
3. Expensive Treatments # Top 5 most costly treatments
4. Age Groups # Patient classification by age
5. About Project # Project and team information
6. Exit # Close application
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TASK 1: DISEASE COST ANALYSIS
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Average Cost by Disease:
Cancer: Rs. 88,500
Heart Disease: Rs. 70,000
Diabetes: Rs. 16,500
Pneumonia: Rs. 13,000
Asthma: Rs. 7,250
Flu: Rs. 2,000
Most Expensive: Cancer
Least Expensive: Flu- Total Records: 15 patients
- Age Range: 8-76 years
- Geographic Focus: Indian patient names and demographics
- Cost Range: ₹1,500 - ₹92,000
| Disease | Avg. Cost | Patients |
|---|---|---|
| Cancer | ₹88,500 | 2 |
| Heart Disease | ₹70,000 | 3 |
| Diabetes | ₹16,500 | 3 |
| Pneumonia | ₹13,000 | 2 |
| Asthma | ₹7,250 | 2 |
| Flu | ₹2,000 | 3 |
- Data Loading: CSV file handling with pandas
- Data Grouping: Using
groupby()for categorical analysis - Data Sorting: Implementing
sort_values()for ranking - Custom Functions: Creating and applying user-defined functions with
apply() - Modular Programming: Separating concerns across multiple files
| Developer | Module | Contributions |
|---|---|---|
| Mangesh Choudhary | Hospital_Management.py | Main program and menu system |
| Ayush Raybhar | diseases.py | Disease analysis and cost calculations |
| Sean Ambrose | costs.py | Expensive treatments identification |
| Riya Singh | ages.py | Age group classification system |
Made with ❤️ by Team Hospital Management