3

 import pandas as pd

import seaborn as sns

import matplotlib.pyplot as plt


# Sample dataset

data = {

'EngineSize_L': [1.2, 1.6, 2.0, 2.5, 3.0, 1.8, 2.2, 3.5, 4.0, 2.8],

'FuelEfficiency_MPG': [40, 35, 30, 28, 24, 33, 29, 20, 18, 26],

'Price_USD': [18000, 20000, 24000, 28000, 35000, 22000, 26000, 40000, 45000, 33000]

}

df = pd.DataFrame(data)


# Pair plot

sns.pairplot(df)

plt.suptitle("Pair Plot: Engine Size, Fuel Efficiency, Price", y=1.02)

plt.tight_layout()

plt.show()


# Correlation matrix

corr_matrix = df.corr(numeric_only=True)

print("Correlation Matrix:\n", corr_matrix)


# Heatmap of correlations

plt.figure(figsize=(6, 4))

sns.heatmap(corr_matrix, annot=True, cmap='coolwarm', fmt=".2f")

plt.title('Correlation Matrix: Car Features')

plt.tight_layout()

plt.show()

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