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from pymongo import Connection | |
import datetime | |
import time | |
#connect to mongodb | |
connection = Connection(‘newitfarmer.com’, 27017) |
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from pymongo import Connection | |
import datetime | |
import time | |
#connect to mongodb | |
connection = Connection(‘newitfarmer.com’, 27017) |
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given a text file containing stopwords, return a python list of its contents. | |
this list is optimized for twitter/social media and filters out stuff | |
like RT, nowplaying, lastfm, 4sq etc. | |
def get_stopwords(file='stopwords.txt'): | |
words = open(file,'r') | |
stopwords = [word.strip() for word in words] | |
return set(stopwords) |
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""" | |
tiny script to convert a pandas data frame into a JSON object | |
""" | |
import ujson as json | |
import pandas | |
import numpy as np | |
df = pandas.DataFrame({ | |
"time" : [1,2,3,4,5], |
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# a messy hack written by Edd Dumbill. http://twitter.com/edd | |
# You may need to rerun this script if you hit a Twitter Error because you | |
# use up API rate limiting. That's why we pickle the results, so we can resume | |
# where we left off. | |
# get the twitter module using 'easy_install twitter' | |
from twitter.api import Twitter, TwitterError | |
from twitter.oauth import OAuth |
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import numpy as np, numpy.linalg as linalg | |
def fast_svd(M, k): | |
p = k+5 | |
Y = np.dot(M, np.random.normal(size=(M.shape[1],p))) | |
Q,r = linalg.qr(Y) | |
B = np.dot(Q.T,M) | |
Uhat, s, v = linalg.svd(B, full_matrices=False) | |
U = np.dot(Q, Uhat) | |
return U.T[:k].T, s[:k], v[:k] |
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""" | |
(C) Mathieu Blondel - 2010 | |
Implementation of the collapsed Gibbs sampler for | |
Latent Dirichlet Allocation, as described in | |
Finding scientifc topics (Griffiths and Steyvers) | |
""" | |
import numpy as np |
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