PythonExploratoryDataAnalysis

Welcome to my Exploratory Data Analysis (EDA) project on Hospital Discharge Records!
This project aims to analyze trends, patterns, and insights related to hospital discharges using real-world healthcare data.

Objectives

1. Pie Chart — Visualize the percentage of discharges per county.
2. Line Plot — Track the number of discharges over time, categorized by disease.
3. Bar Chart — Identify top 10 counties with the highest discharge volume.
4. Clustering (K-Means) — Group similar disease-county discharge patterns.
5. Scatter Plot — Visualize discharges over years by Major Diagnostic Category (MDC).
6. Pair Plot — Explore relationships between multiple numerical features.
7. Heatmap — Analyze correlations between numerical features.

📊 Tools & Libraries Used

• Python 3.13
• pandas
• numpy
• matplotlib
• seaborn
• scikit-learn
• Jupyter Notebook

📁 Project Structure

.
├── data/
│   ├── raw_data.csv
│   └── cleaned_data.csv
├── notebooks/
│   └── Hospital_Discharge_Analysis.ipynb
├── plots/
│   └── (Contains saved visualizations)
├── README.md

📈 Key Insights
Certain counties contribute significantly higher discharge volumes.

Disease trends show seasonal and regional fluctuations.

Clustering reveals patterns in patient loads across counties and diseases.

Discharges correlate moderately with diagnosis and time in specific cases.

🧠 Learning Outcomes
Applied exploratory data analysis in a real-world healthcare dataset.

Gained experience in data preprocessing, visualization, and clustering.

Understood how to extract insights that can guide healthcare planning and policy.

🙏 Acknowledgment
This project was completed as part of the INT375 course under the guidance of Ms. Ashima Bansal, Assistant Professor at Lovely Professional University.
Her mentorship and support were instrumental throughout the project.

🌐 Connect With Me
GitHub: nikita0109balwada

LinkedIn: https://www.linkedin.com/in/nikita-balwada29/

⭐️ If you found this project interesting, give it a star!
Feel free to fork, share, or contribute.