README.md

metadata

task_categories:
  - tabular-classification
language:
  - en
tags:
  - health
  - medical
size_categories:
  - 1K<n<10K

❤️ Heart Disease — Exploratory Data Analysis

👤 Author

Oded Fuchs

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🎯 Project Goal

The goal of this project is to explore which factors are most strongly related to heart disease,
using statistical analysis and data visualization.

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🔍 Research Question

Which factors have the strongest impact on the likelihood of heart disease?

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📦 Dataset

• Source: Kaggle
• Format: CSV
• ~302 samples
• Contains various clinical features

Target

target

• 1 = Heart disease
• 0 = No heart disease

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🏷 Feature Overview

Feature	Description
age	Age
sex	0 = female, 1 = male
cp	Chest pain type
trestbps	Resting blood pressure
chol	Cholesterol
fbs	Fasting blood sugar
restecg	Resting ECG results
thalach	Maximum heart rate
exang	Exercise-induced angina
oldpeak	ST depression
slope	Slope of ST
ca	Number of major vessels
thal	Thallium test result
target	Heart disease indicator

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🔧 Data Preparation

✅ Cleaning Steps

• Checked for missing values — none found
• Checked for duplicate records
• Verified valid ranges
• Adjusted and simplified column names

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📊 Exploratory Data Analysis (EDA)

Target Distribution

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✅ Key Features & Insights

1) Age

Patients with heart disease are slightly younger on average.

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2) Chest Pain (cp)

One of the strongest predictors:
Higher chest pain type is strongly linked to heart disease.

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3) Max Heart Rate (thalach)

Patients with heart disease tend to have a higher maximum heart rate.

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4) ST Depression (oldpeak)

Lower oldpeak values are more common among heart-disease patients.

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5) Exercise-Induced Angina (exang)

Most patients do not experience chest pain during exercise.

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6) Thal

Moderate difference between groups, still noticeable.

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📑 Summary Table

Feature	No Disease (0)	Disease (1)	Insight
cp	0.48	1.38	Strong relationship
thalach	139	159	Higher among disease
oldpeak	1.60	0.57	Lower among disease
exang	0.55	0.14	Less common in disease
age	56.6	52.4	Slightly younger
chol	251	241	Small difference
ca	1.16	0.37	⚠️ Opposite trend
trestbps	134	129	Weak effect
thal	2.54	2.12	Moderate effect

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✅ Main Insights

📌 Strong indicators of heart disease:

1. Chest Pain (cp)
2. Max Heart Rate (thalach)
3. ST Depression (oldpeak)
4. Exercise-Induced Angina (exang)

📌 Additional observations:

• Exercise-induced angina (exang) is less common among patients with heart disease
• Cholesterol and blood pressure show weaker relationships
• ca shows an unexpected pattern → may indicate data/coding issues

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✅ Conclusions

Several clinical measurements appear strongly connected to heart disease, including chest pain type, maximum heart rate, and ST-related metrics.
Other features, such as cholesterol and resting blood pressure, show weaker influence.

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🎬 Video Presentation

🔗 https://www.loom.com/share/d5891c3d0c20490ba79884fc701f4bc7

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🧾 Files Included

File	Description
Assignment_1_oded_fuchs.ipynb	Analysis & visuals
README.md	Project summary
heart.csv	Original dataset

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