Load the ‘car_crashes’ dataset and visualize a heatmap of the correlation matrix. Highlight cells with a correlation higher than 0.8 in a different color.
Example Output:
Utilize sns.heatmap
, and fetch the car_crashes dataset using sns.load_dataset('car_crashes')
.
import seaborn as sns import matplotlib.pyplot as plt def plot_car_crashes_correlation(): crashes_data = sns.load_dataset('car_crashes') correlation = crashes_data.corr() mask = correlation > 0.8 sns.heatmap(correlation, annot=True, mask=~mask, cmap="coolwarm") plt.title('Correlation Matrix of Car Crashes') plt.show() plot_car_crashes_correlation()