week_#7_in_machine learning17

474c7d07-6647-497a-8093-b074d077f9a9.py

fig = plt.figure(figsize=(20,15))
ax = fig.add_subplot(111, projection='3d')

ax.scatter(df2['Age'][df2['Label']==0], df2['Annual Income (k$)'][df2['Label']==0], 
           df2['Spending Score (1-100)'][df2['Label']==0], c='green', s=50)
ax.scatter(df2['Age'][df2['Label']==1], df2['Annual Income (k$)'][df2['Label']==1], 
           df2['Spending Score (1-100)'][df2['Label']==1], c='blue', s=50)
ax.scatter(df2['Age'][df2['Label']==2], df2['Annual Income (k$)'][df2['Label']==2], 
           df2['Spending Score (1-100)'][df2['Label']==2], c='black', s=50)
ax.scatter(df2['Age'][df2['Label']==3], df2['Annual Income (k$)'][df2['Label']==3], 
           df2['Spending Score (1-100)'][df2['Label']==3], c='red', s=50)
ax.scatter(df2['Age'][df2['Label']==4], df2['Annual Income (k$)'][df2['Label']==4], 
           df2['Spending Score (1-100)'][df2['Label']==4], c='purple', s=50)
ax.view_init(30, 190)
ax.set_xlabel('Age')
ax.set_ylabel('Annual Income')
ax.set_zlabel('Spending Score')
plt.show()