# Generate an artificial network of 25 nodes
G = nx.barabasi_albert_graph(25,4, seed=42)

# Apply the PageRank algorithm and store the scores in a pd dataframe
pagerank_results = nx.pagerank(G, alpha=0.85, max_iter=100, tol=1e-06)
pagerank_results = pd.Series(pagerank_results).sort_values(ascending=False)

# Plot the most importan node scores
fig, ax = plt.subplots()
sns.barplot(x=pagerank_results.iloc[:10].values, y=pagerank_results.iloc[:10].index.astype(str), orient='h', alpha=0.75)
ax.set_xlabel('PageRank Score')
ax.set_ylabel('Node')
ax.spines['top'].set_visible(False)
ax.spines['bottom'].set_visible(False)
ax.spines['right'].set_visible(False)
ax.spines['left'].set_visible(False)
for i in ax.containers:
    ax.bar_label(i,fmt='%.2f')