medical-data-visualizer

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medical-data-visualizer

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Data visualization project using Pandas, Seaborn, and Matplotlib on medical examination data to explore relationships between health indicators and cardiovascular disease.

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# 🩺 Medical Data Visualizer

This project is part of the **freeCodeCamp - Data Analysis with Python** certification.  
It uses real-world medical examination data to analyze and visualize the relationship between cardiovascular disease and various health and lifestyle factors.

## 📊 Features

- ✅ Clean and preprocess real medical data
- ✅ Add custom calculated features (e.g. BMI → Overweight)
- ✅ Normalize categorical data (Good = 0, Bad = 1)
- ✅ Create categorical bar plots to show lifestyle effects
- ✅ Generate a heatmap to visualize correlations between features

## 📁 Dataset

- `medical_examination.csv`: Contains patient data like age, height, weight, blood pressure, cholesterol, glucose, smoking, alcohol intake, activity, and cardio disease status.

## 📈 Visualizations

- **Categorical Plot**:
  Shows comparison of lifestyle choices (e.g., smoking, alcohol) and their relation to heart disease.

- **Heatmap**:
  Correlation matrix showing relationships between numerical features after data cleaning.

## 📦 Libraries Used

- `pandas`
- `matplotlib`
- `seaborn`

## 🧠 What I Learned

- Data cleaning using Pandas
- Visualization using Seaborn & Matplotlib
- Handling categorical data
- Analyzing health-related real-world data

## 📎 Project Link

- [freeCodeCamp Project Page](https://www.freecodecamp.org/learn/data-analysis-with-python/data-analysis-with-python-projects/medical-data-visualizer)

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> Built with 💙 using Python and Jupyter Notebook

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