Medical Data Visualizer

Overview

Medical Data Visualizer is a Python project that analyzes and visualizes medical examination data using pandas, matplotlib, and seaborn. It provides insights into patient health metrics through categorical plots and correlation heatmaps.

Project Structure

medical-data-visualizer
├── src
│   ├── medical_data_visualizer.py
│   └── main.py
├── tests
│   └── test_module.py
├── data
│   └── medical_examination.csv
├── requirements.txt
├── .gitignore
└── README.md

File Descriptions

• src/medical_data_visualizer.py: Core logic for importing, processing, and visualizing the medical data. Includes functions for BMI calculation, data normalization, categorical plotting, and heatmap generation.
• src/main.py: Entry point for running the application. Imports and executes the main analysis and visualization functions.
• tests/test_module.py: Unit tests for the main data processing and visualization functions.
• data/medical_examination.csv: The dataset containing patient information such as age, height, weight, blood pressure, cholesterol, glucose, smoking, alcohol intake, physical activity, and cardiovascular disease.
• requirements.txt: Lists all Python dependencies.
• .gitignore: Specifies files and folders to be ignored by git.

Setup Instructions

1. Clone the repository:

   git clone <repository-url>
   cd medical-data-visualizer

2. Create and activate a virtual environment:

   python3 -m venv venv
   source venv/bin/activate

3. Install the required dependencies:

   pip install -r requirements.txt

Usage

To run the application and generate the visualizations:

python [main.py](http://_vscodecontentref_/2)

This will create catplot.png and heatmap.png in your project directory.

Running Tests

To run the unit tests:

python -m unittest tests/test_module.py

Dataset Information

The medical_examination.csv file contains the following columns:

• age: Age in years
• height: Height in cm
• weight: Weight in kg
• ap_hi: Systolic blood pressure
• ap_lo: Diastolic blood pressure
• cholesterol: 1 (normal), 2 (above normal), 3 (well above normal)
• gluc: 1 (normal), 2 (above normal), 3 (well above normal)
• smoke: 0 (no), 1 (yes)
• alco: 0 (no), 1 (yes)
• active: 0 (no), 1 (yes)
• cardio: 0 (no cardiovascular disease), 1 (cardiovascular disease)

Visualizations

• catplot.png: Shows the counts of good and bad outcomes for cholesterol, glucose, alcohol, physical activity, smoking, and overweight status, split by presence or absence of cardiovascular disease.
• heatmap.png: Displays the correlation matrix for all numerical features, helping to identify relationships between health indicators.

License

This project is for educational purposes and does not include a formal license.