In [1]:
from __future__ import division
import pymongo, pandas, random
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
from scipy import stats
%matplotlib inline
client = pymongo.MongoClient('localhost', 27017)
results_db = client['results']['question_3']
In [2]:
cursor = results_db.find({'lifetime_pvalue': {'$lt': 0.05}},
{u'_id': False, u'community':True, 'lifetime_pvalue':True,
'lifetime_difference_median':True, 'category': True})
df = pandas.DataFrame(list(cursor))
In [3]:
df
Out[3]:
In [4]:
cursor = results_db.find({'frequency_pvalue': {'$lt': 0.05}},
{u'_id': False, u'community':True, 'frequency_pvalue':True,
'frequency_difference_median':True, 'category': True,
'frequency_difference_mean':True, 'frequency_pvalue_greater':True})
df = pandas.DataFrame(list(cursor))
In [5]:
df
Out[5]:
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