# Convert the previously create graph to directed
G_dir = G.to_directed()
for a, b in list(G.edges()):
    G_dir.remove_edge(a, b)

# Compute HITS scores
hits_results = nx.hits(G_dir, max_iter=100, tol=1e-06)
authority_results = pd.Series(hits_results[1]).sort_values(ascending=False)
hubs_results = pd.Series(hits_results[0]).sort_values(ascending=False)

# Plot the results
fig, (ax1, ax2) = plt.subplots(nrows=1, ncols=2)
fig.set_figheight(8)
fig.set_figwidth(16)
sns.barplot(x=authority_results.iloc[:10].values, y=authority_results.iloc[:10].index.astype(str), orient='h', alpha=0.75, ax=ax1)
ax1.set_xlabel('Authority Score')
ax1.set_ylabel('Node')
ax1.spines['top'].set_visible(False)
ax1.spines['bottom'].set_visible(False)
ax1.spines['right'].set_visible(False)
ax1.spines['left'].set_visible(False)
for i in ax1.containers:
    ax1.bar_label(i,fmt='%.2f')

sns.barplot(x=hubs_results.iloc[:10].values, y=hubs_results.iloc[:10].index.astype(str), orient='h', alpha=0.75, ax=ax2)
ax2.set_xlabel('Hub Score')
ax2.set_ylabel('Node')
ax2.spines['top'].set_visible(False)
ax2.spines['bottom'].set_visible(False)
ax2.spines['right'].set_visible(False)
ax2.spines['left'].set_visible(False)
for i in ax2.containers:
    ax2.bar_label(i,fmt='%.2f')