Venmo Graph Analysis

Venmo Personalized Pagerank

import networkx as nx
import pickle
import pandas as pd

#Load Data
user_df = pickle.load(open('user_data.p','rb'))
transaction_df = pickle.load(open('transaction_data.p','rb'))

G_venmo = nx.MultiGraph()
G_venmo.add_nodes_from(user_df['user_id'])
G_venmo.add_edges_from(list(zip(transaction_df['actor_id'], transaction_df['target_id'])))

def user_rank(users, G, num_friends = 5):
    '''
    Inputs are a list of user_ids and a graph of Venmo transactions. Returns N (set by num_friends) highest ranked users to the given user. 
    '''
    if type(users == str):
        personalization = {users : 1}
    else:
        prob = 1/len(users)
        personalization = {user : prob for user in users}
    page_rank_users = nx.pagerank_scipy(G, personalization = personalization)  
    page_rank_users = {u : v for u,v in sorted(page_rank_users.items(), key=lambda item: item[1], reverse = True)}
    friends = list(page_rank_users)[0:num_friends+1]
    return friends