Hierarchical clustering: complete method

For the third and final time, let us use the same footfall dataset and check if any changes are seen if we use a different method for clustering.

The data is stored in a pandas DataFrame, comic_con. x_scaled and y_scaled are the column names of the standardized X and Y coordinates of people at a given point in time.

This exercise is part of the course

Cluster Analysis in Python

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Exercise instructions

  • Import fcluster and linkage from scipy.cluster.hierarchy.
  • Use the complete method in the .linkage() function.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Import the fcluster and linkage functions
____

# Use the linkage() function
distance_matrix = ____(____, ____, ____)

# Assign cluster labels
comic_con['cluster_labels'] = ____

# Plot clusters
sns.scatterplot(x='x_scaled', y='y_scaled', 
                hue='cluster_labels', data = comic_con)
plt.show()