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()
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