In [65]:

    

import pandas as pd 
import networkx as nx 
import pickle


    

In [14]:

    

df_n = pd.read_csv('stars_main_nodes.csv')
df_e = pd.read_csv('stars_main_edges.csv')


    

In [30]:

    

# making a simple test graph from stars node/edge csv


    

In [67]:

    

G = nx.from_pandas_dataframe(df_e, 'source', 'target')


    

In [68]:

    

node_attr_list = df_n.to_dict('records')


    

In [69]:

    

n_id = 0
for i in G.nodes_iter(data=True):
    i[1]['label'] = node_attr_list[n_id]['label']
    i[1]['node_type'] = node_attr_list[n_id]['node_type']
    n_id += 1


    

In [70]:

    

pickle.dump(G,open('stars_test_graph.pkl','wb'))


    

In [74]:

    

df_n['node_type'].unique().tolist()


    

    
Out[74]:





['Author', 'Journal']

In [82]:

    

import random
r = lambda: random.randint(0,255)
print('#%02X%02X%02X' % (r(),r(),r()))


    

    




#2B1FE5

In [85]:

    

gg = nx.Graph()

gg.add_edge(0,1)
gg.add_edge(1,2)
gg.add_edge(1,3)
gg.add_node(0,{'node_type':'A', 'label':'node0'})
gg.add_node(1,{'node_type':'A', 'label':'node1'})
gg.add_node(2,{'node_type': 'B', 'label':'node2'})
gg.add_node(2,{'node_type': 'B', 'label':'node2'})


    

In [87]:

    

gg.nodes(data=True)


    

    
Out[87]:





[(0, {'node_type': 'A'}), (1, {'node_type': 'B'}), (2, {'node_type': 'C'})]

In [101]:

    

df_n.iloc[:1]['node_type'][0] == df_n.iloc[:1]['node_type'][0]


    

    
Out[101]:





True

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