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_2']
In [2]:
cursor = results_db.find({'acc_rate_pvalue': {'$lt': 0.05}},
{u'_id': False, u'community':True, 'acc_rate_pvalue':True,
'acc_rate_difference_median':True, 'category': True,
'acc_rate_difference_mean':True, 'acc_rate_pvalue_greater':True})
df = pandas.DataFrame(list(cursor))
In [3]:
df
Out[3]:
In [4]:
cursor = results_db.find({'mean_utility_pvalue': {'$lt': 0.05}},
{u'_id': False, u'community':True, 'mean_utility_pvalue':True,
'mean_utility_difference_median':True, 'category': True,
'mean_utility_difference_mean':True, 'mean_utility_pvalue_greater':True})
df = pandas.DataFrame(list(cursor))
In [5]:
df
Out[5]:
In [6]:
cursor = results_db.find({'questions_avg_pvalue': {'$lt': 0.05}},
{u'_id': False, u'community':True, 'questions_avg_pvalue':True,
'questions_avg_difference_median':True, 'category': True,
'questions_avg_difference_mean':True, 'questions_avg_pvalue_greater':True})
df = pandas.DataFrame(list(cursor))
In [7]:
df
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