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Datasets:
odedf2001
/
heart2

Tasks:
Tabular Classification
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health
medical
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age
int64
sex
int64
cp
int64
trestbps
int64
chol
int64
fbs
int64
restecg
int64
thalach
int64
exang
int64
oldpeak
float64
slope
int64
ca
int64
thal
int64
target
int64
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111
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1
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120
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162
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1
48
1
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130
245
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180
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0
2
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1
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152
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2
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150
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157
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1.6
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1
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130
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59
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53
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2
130
197
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0
152
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0
2
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42
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1
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1
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37
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2
120
215
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1
170
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2
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2
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62
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160
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145
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6.2
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3
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59
1
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170
326
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140
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3.4
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56
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2
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187
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1
End of preview. Expand in Data Studio

❤️ Heart Disease — Exploratory Data Analysis

👤 Author

Oded Fuchs

🎯 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.

🔍 Research Question

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

📦 Dataset

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

Target

target

  • 1 = Heart disease
  • 0 = No heart disease

🏷 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

🔧 Data Preparation

✅ Cleaning Steps

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

📊 Exploratory Data Analysis (EDA)

Target Distribution

image

✅ Key Features & Insights

1) Age

Patients with heart disease are slightly younger on average.

image

2) Chest Pain (cp)

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

image

3) Max Heart Rate (thalach)

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

image

4) ST Depression (oldpeak)

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

image

5) Exercise-Induced Angina (exang)

Most patients do not experience chest pain during exercise.

image

6) Thal

Moderate difference between groups, still noticeable.

image

📑 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

✅ 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

✅ 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.

🎬 Video Presentation

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

🧾 Files Included

File Description
Assignment_1_oded_fuchs.ipynb Analysis & visuals
README.md Project summary
heart.csv Original dataset
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Size of downloaded dataset files:
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Number of rows:
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