Skip to content

shivamdubey023/Summer-Bootcamp-Training-Project

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

89 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

❤️ Heart Disease Analysis Project

Summer Bootcamp Training Project
SRMCEM, Lucknow

This project is a comprehensive data science analysis focused on understanding patterns and risk factors related to heart attacks. Our team explored multiple patient data sources and developed visualizations and reports using Python, SQL, Power BI, and Jupyter Notebooks.


🫀 About the Project

The core objective of the project was to identify causes, patterns, and contributing factors related to heart attacks, using real-world clinical datasets. We aimed to derive insights that can aid in early detection, better diagnosis, and healthcare planning.

🧩 Project Goals
  • Understand patient demographics and medical history
  • Identify key diagnostic markers and abnormal lab results
  • Explore the relationship between medications and diagnoses
  • Analyze visit patterns and hospitalization frequency
  • Integrate and visualize data through dashboards
📚 Datasets Used
  • patients.csv – Patient demographics and IDs
  • visits.csv – Details of hospital visits and admissions
  • diagnosis.csv – Medical diagnoses related to cardiovascular conditions
  • lab_record.csv – Lab test results (e.g., cholesterol, ECG, blood pressure)
  • medication.csv – Prescribed drugs and treatment histories
🔬 Key Analysis Areas
  • Patient-level profiling
  • Temporal patterns in visits and treatments
  • Correlation between diagnoses and lab findings
  • Effectiveness and frequency of specific medications
  • Data integration across files for comprehensive case analysis

The project involved SQL-based data extraction, Python-based analysis using libraries such as Pandas, Matplotlib, and Seaborn, as well as the development of a Power BI dashboard for executive-level visual insights.


📁 Project Structure

📁 Summer-Bootcamp-Training-Project/

├── 📁 CSV/

│ ├── diagnoses+lab_results.csv

│ ├── diagnoses_updated.csv

│ ├── medications.csv

│ ├── patient+visit.csv

│ ├── patients+visits.csv

│ ├── updated_lab_results.csv

│ └── updated_patients.csv

│ └── visits.csv

├── 📁 Code/

│ ├──Heart_Disease_(Lab_result+Medication+Diagnoses).ipynb/

│ ├── diagnoses+lab_result.ipynb

│ ├── paitents_.analysis.ipynb

│ ├── patients+visits.ipynb

│ └── visit_analysis.ipynb

├── 📁 SQL/

│ ├── heart_disease.sql

│ └── SQL_Report.pdf

├── 📁 PDF/

│ ├── Heart Disease Analysis Project.pdf

│ ├── Heart Disease.pdf

│ ├── Heart_Disease_Report.pdf

│ ├── Paitent_View.pdf

│ └── lab_diagnosis_analysis.pdf

├── 📁 PowerBI/

│ └── Heart Disease Analysis Project.pbix

└── README.md


📊 Heart Disease Analysis Project

This project includes a detailed exploration of heart disease data using Power BI and SQL.

🖼️ PDF Preview

Heart Disease Report Preview


📊 Project Highlights

  • Data Source: Data was gathered from various online health datasets.
  • Data Files: 5 key CSVs including:
    • diagnoses_updated.csv
    • medications.csv
    • updated_lab_results.csv
    • updated_patients.csv
    • visits.csv
  • Analysis Tools:
    • Python libraries: pandas, numpy, seaborn, matplotlib, fpdf, warnings
    • SQL for querying structured data
    • Jupyter Notebooks for visual exploratory analysis
    • Power BI for interactive dashboards and stakeholder reporting

🧠 Key Insights

  • Identification of critical lab results and diagnosis combinations that correlate with heart attacks.
  • Frequency and type of medications administered.
  • Patient visit trends and relationships between comorbidities and heart disease.
  • Interactive dashboards summarizing findings visually.

📌 Technologies Used

Tool/Library Purpose
Python (Pandas, NumPy, Matplotlib, Seaborn) Data manipulation & visualization
SQL Data querying & exploration
Jupyter Notebook Interactive data analysis
Power BI Dashboard creation
FPDF PDF report generation

👩‍💻 Team Members

Name GitHub Username
Aditi Agnihotri aditi549
Aditi Pandey Aditi14319
Anshika Dubey Anshika-Dubey
Ishita Aggarwal ishita009A
Nirnay Awasthi NirnayAwasthi
Shashank Mishra ShashankMishra9696
Shivam Kumar Dubey kuro-shiv
Suryakant Mishra mishrasuryakant
Vanshika Gupta vanshikagpt1204

🙏 Acknowledgement

Special thanks to our mentor Saurabh Aggarwal Sir for his valuable guidance throughout the project.


📜 Reflection

"This bootcamp was a highly enriching and insightful experience. Working on a real-world case study helped us enhance both technical and analytical skills, and taught us how to collaborate on industry-level data science workflows."

— Team Feedback

This project is for academic and educational purposes only.


📎 Clone the repository

git clone https://github.com/kuro-shiv/Summer-Bootcamp-Training-Project

---

Tada here


About

The project was to identify causes, patterns, and contributing factors related to heart attacks, using real-world clinical datasets. We aimed to derive insights that can aid in early detection, better diagnosis, and healthcare planning.

Topics

Resources

Stars

Watchers

Forks

Contributors