The goal is to create a networkx graph based on eigenvalue centrality and highlight the top five nodes of highest centrality measure with a different node color. 

Below is my current script. It's working fine and everything's just set to one color for now. 

```
#import packages 
import pandas as pd
import networkx as nx
import matplotlib.pyplot as plt
import collections

#read data into nx graph
G = nx.from_pandas_dataframe(df, 'col1', 'col2')

#get dictionary of centrality measures and order it
eig = nx.eigenvector_centrality(G) 
ordered = collections.OrderedDict(sorted(eig.items(), reverse = True,  key=lambda t: t[1]))

#draw graph
nx.draw_spring(G, k=1, node_color = 'skyblue', 
               node_size = 200, font_size = 6, with_labels = True)
plt.show()

```

Below is what I'm experimenting with for the node coloring. I'm attempting to append the first five ordered dictionary key names to the color\_map, setting them to a different color from the rest. Please let me know if you have any suggestions here or if another method would simpler. If possible, I'd prefer to stick to the packages I'm using. 

```
#adjust color of top three
color_map = []
for key, value in ordered:
    if key < 5:
        color_map.append('blue')
    else: color_map.append('green')

```