💉 Diabetes Data Analysis Project

This project is an exploratory data analysis (EDA) of a diabetes dataset. It aims to uncover patterns and correlations between health indicators and the likelihood of diabetes diagnosis.

📄 Final Report: diabetes.pdf

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📌 Objectives

The analysis focuses on answering questions like:

• What are the characteristics of patients with diabetes?
• How do features like glucose, insulin, BMI, and age affect diabetes outcomes?
• What are the most influential factors in predicting diabetes?

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📊 Dataset Summary

• Source: Pima Indians Diabetes Dataset (Kaggle / UCI ML Repo)
• Rows: 768
• Features:
  • Pregnancies
  • Glucose
  • Blood Pressure
  • Skin Thickness
  • Insulin
  • BMI
  • Diabetes Pedigree Function
  • Age
  • Outcome (1 = Diabetes, 0 = No Diabetes)

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📁 Project Structure

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🛠️ Tools Used

• Python
• Pandas
• Matplotlib
• Seaborn
• Jupyter Notebook

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📈 Key Insights

Full visualizations and analysis are available in diabetes.pdf, but here are some highlights:

• 📊 People with higher glucose levels and higher insulin values are more likely to have diabetes.
• 🧮 BMI and Age are also significantly associated with diabetes outcomes.
• 📉 There are patterns where multiple low-health indicators overlap in diabetic cases.

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🚀 How to Run the Project

1. Clone the repository:

   git clone https://github.com/ahmedshekooo/diabetes_project.git
   cd diabetes_project