What's missing: import pandas as pd

from scipy.cluster.hierarchy import linkage

from scipy.spatial.distance import pdist

from sklearn.preprocessing import StandardScaler

wine $=$ pd$.$read$\_$csv$(\text{'}$wine$1.$csv$\text{'})$

# Calculate a distance matrix with selected variables

X $=$ wine$[[\text{'}$alcohol$\text{'},$ 'total$\_$sulfur$\_$dioxide'$]]$

scaler $=$ StandardScaler$()$

X $=$ pd$.$DataFrame$($scaler$.$fit$\_$transform$($X$))$

# pdist$()$ calculates pairs of distances between each instance in the dataset

dist $=$ pdist$($X$)$

# Your code goes here

print$($clusterModel$)$