import pandas as pd
from sklearn.cluster import KMeans

data = [(0.2, 10),
        (0.3, 12),
        (0.24, 14),
        (0.8, 30),
        (0.9, 32),
        (0.85, 33.3),
        (0.91, 31),
        (0.1, 15),
        (-0.23, 45)]

p_df = pd.DataFrame(data)
kmeans = KMeans(init='k-means++', n_clusters=3, n_init=10)
kmeans.fit(p_df)


Result:

>>> kmeans.labels_
array([0, 0, 0, 2, 2, 2, 2, 0, 1], dtype=int32)