# import librares & load dataset 

from sklearn.datasets import load_iris
from sklearn.cluster import KMeans
import matplotlib.pyplot as plt

iris = load_iris()
X = iris.data  # unlabeled features

# selecting features
# Use petal length and petal width (features 2 and 3)
X_selected = X[:, 2:4]


# apply k-means
kmeans = KMeans(n_clusters=3, random_state=42)
labels = kmeans.fit_predict(X_selected)
centroids = kmeans.cluster_centers_

# visualizing clusters
plt.figure(figsize=(8, 6))

plt.scatter(
    X_selected[:, 0],
    X_selected[:, 1],
    c=labels,
    alpha=0.7
)

plt.scatter(
    centroids[:, 0],
    centroids[:, 1],
    marker='X',
    s=250
)

plt.xlabel("Petal Length")
plt.ylabel("Petal Width")
plt.title("K-Means Clustering (Petal Features Only)")
plt.show()

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