drewconway

import urllib2

def get_player_profiles(player_list):
# Returns a dict of player profile URLs to be used in the next step
    # Dict will hold player profile pages indexed by player name
    player_profile_urls=dict.fromkeys(player_list)
    for n in player_list:
        names=n.split(' ')
        # Search for the player names at NFL.com to get their individual player profiles, which contain the
        # data we ultimately want.

drewconway

import os
import sys
import csv

def get_players(path):
# Returns a list of player names from CSV file
    reader=csv.reader(open(path,'U'),delimiter=',')
    '''
    players=[]
    row_num=0

drewconway

#!/usr/bin/env python
# encoding: utf-8
"""
Experiments for growing fractal networks

Created by Drew Conway on 2009-05-19.
Copyright (c) 2009. All rights reserved.
"""

import sys

drewconway

#!/usr/bin/env python
# encoding: utf-8
"""
exploded_view_3d.py

The purpose of this script is to create an 'exploded view'
of a network in 3D using hierarchical clustering of geodesic 
distances in NetworkX and UbiGraph.

This script is intended as an illustrative proof of concept

drewconway

#!/usr/bin/env python
# encoding: utf-8
"""
TwitterEgoBuilder.py

Created by Drew Conway on 2009-02-23.
Copyright (c) 2009. All rights reserved.

The purpose of this script is to generate a 
NetworkX DiGraph object based on the snowball

drewconway

counts = dict((k, F.count(k)) for k in set(F))
counts_items=counts.items()
counts_items=[(b,a) for (a,b) in counts_items]
counts_items.sort()
counts_items.reverse()

for i in counts_items:
    print str(i[0])+' of your friends are already following '+i[1]

drewconway

N=K.neighbors('your_twitter_id')
F=[]
for u in N:
    D=K.neighbors(u)
    for i in D:
        if N.count(i)<1 and i is not 'your_twitter_id':
            F.append(i)

drewconway

from networkx import core
kcores=core.find_cores(G)
core_items=kcores.items()
two_core=[(a) for (a,b) in core_items if b>1]
K=subgraph(G,two_core)
info(K)

drewconway

from networkx import *
import os
os.chdir('/Where/You/Stored/TheData/File/')
G=read_edgelist('your_net.edgelist',delimiter='\t',create_using=Graph(),nodetype=str)
info(G)

drewconway

#Store network data as plain text file to be analyzed later
twitter_net._name=seed+'_k'+str(k)  # Name the network after the seed and the number of snowball rounds
NX.write_edgelist(twitter_net,path='your_net.edgelist',delimiter='\t')