Import:
- pandas as pd.
- fcluster from scipy.cluster.hierarchy.
Perform a flat hierarchical clustering by using the fcluster() function on mergings. Specify a maximum height of 6 and the keyword argument criterion='distance'.
Create a DataFrame df with two columns named 'labels' and 'varieties', using labels and varieties, respectively, for the column values. This has been done for you.
Create a cross-tabulation ct between df['labels'] and df['varieties'] to count the number of times each grain variety coincides with each cluster label.