## 5 Data Collection
### Checking the Categorical and Numerical Features Pair Plots, Count Plots of the Data  
To evaluate the data, many distribution plots are constructed to confirm attribute values and look at the data's skewness (the asymmetry of a distribution). To offer an overview of the data, a number of graphs are presented. Figures 5 and 6 depict the results of analyzing the distributions of age and sex, chest pain, and testbps, cholesterol and fasting blood, ECG resting electrode and thalach, exang and old peak, slope and ca, and thal and goal. The numerical feature pair graphs are shown in Figures 7 and 8. A five-point biserial correlation and a point-biserial correlation are used to assess the strength and direction of a relationship between two continuous variables and one dichotomous variable. [PERSON]'s correlation of numerical variables, the correlation between two points, is a point-biserial correlation that is used to determine the strength and direction of a relationship between two continuous variables and one dichotomous variable. It is a variant of [PERSON]'s product-moment correlation, which is used to compare two continuous variables. The Cramer's V statistic is a statistical measure of the connection between two nominal variables that range from 0 to 1. [PERSON]'s chi-squared statistic provides the foundation for it. It is clear from the distribution plots that the data are overfitted or underfitted. It is shown in Figure 5 that the target variable distribution is 50.8% for abnormal heart disease and 49.2% for normal heart disease. The majority of abnormal heart patients are aged 55-65. This also seems to be a balance in disease patients who have experienced cholesterol and max-heart rate achieved. **Chest Pain (cp)** is described in Figures 6 and 7. Heart disease is more common in those with a cp of 1, 2, or 3 compared to those with a cp of 0. **Resting electrocardiographic:** People with value 1 are more likely to have abnormal cardiac disease, which can manifest as anything from minor symptoms to serious complications. **Exercise-induced angina:** People with a value of 0 (no exercise-induced angina) have heart disease more than people with a value of 1 (exercise-induced angina positive)  
**Slope (the slope of the peak exercise ST-segment):** People with a slope value equal to 2 (down sloping: signs of an unhealthy heart) are more likely to have heart disease  
Figure 5: Heart disease target variable distribution. than people with a slope value equal to 0 (upsloping: better heart rate with exercise) or 1 (Flatsloping: minimal change (typical healthy heart)). **Thalassemia {thalium stress result}:** People with a thal value equal to 2 (fixed defect: used to be defective but OK now) are more likely to have heart disease. **Trestbps:** Resting blood pressure (in mm Hg on admission to the hospital). Anything above 130-140 is typically a cause for heart disease. **Chol {serum cholesterol in mg/dl}:** The value of **Chol** above 200 is a cause for heart disease. **Thalach {maximum heart rate achieved}:** People who achieved a **thalach** value higher than 150-160 are more likely to have heart disease. Oldpeak ST depression induced by exercise relative to rest looks at the stress of the heart during exercise. An unhealthy heart will stress more. **CA {number of major vessels (0-3) colour by fluoroscopy}:** The high movement of the blood in the blood vessels is the reason for good health, and people with the lowest value of CA, which is equal to 0, are more likely to have heart disease. Figure 6: Continuous feature Kernel Density Estimate Plot. Figure 7: Categorical features count plots of the Data. It is shown in the given Figures 8-10 that as the goal varies, chest pain or angina (cp), fluctuates. Angina is a serious chest pain condition caused by the heart muscles not receiving enough oxygen-rich blood. Pain in the shoulders, arms, and neck is also caused by angina. While negative patients have lower levels, positive patients have an elevated median for ST depression.