python
def quick_sort(arr):
if len(arr) <= 1:
return arr
pivot = arr[len(arr) // 2]
left = [x for x in arr if x < pivot]
middle = [x for x in arr if x == pivot]
right = [x for x in arr if x > pivot]
return quick_sort(left) + middle + quick_sort(right)
arr = [3, 2, 8, 1, 5, 4, 7, 6]
sorted_arr = quick_sort(arr)
print(sorted_arr)
python
import networkx as nx
G = nx.Graph()
G.add_node(1)
G.add_node(2)
G.add_edge(1, 2)
python
from sklearn.cluster import KMeans
X = [[1, 2], [1, 4], [1, 0],
[10, 2], [10, 4], [10, 0]]
kmeans = KMeans(n_clusters=2, random_state=0).fit(X)
labels = kmeans.labels_
print(labels)
