Data Science
K-Means Clustering: Finding Hidden Groups
Senior Data Analyst
May 12, 2026
5 min read
The Code
from sklearn.cluster import KMeans
kmeans = KMeans(n_clusters=3, random_state=42)
df['cluster'] = kmeans.fit_predict(df[['feature1', 'feature2']])
# Visualize
sns.scatterplot(x='feature1', y='feature2', hue='cluster', data=df)
Finding the Right K
Use the Elbow Method: plot inertia for different K values.
*Day 133: Cross-Validation.*