Load the ‘iris’ dataset, compute a correlation matrix. Create a clustermap and ensure that the leaf colors are customized based on the species.
Example Output:
Use sns.clustermap and play with the row_colors parameter to customize the leaf colors.
import seaborn as sns
import matplotlib.pyplot as plt
def plot_iris_cluster():
iris_data = sns.load_dataset('iris')
species_colors = iris_data['species'].map({
'setosa': 'red',
'versicolor': 'blue',
'virginica': 'green'
})
sns.clustermap(iris_data.drop('species', axis=1).corr(), row_colors=species_colors)
plt.show()
plot_iris_cluster()
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