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_1']
In [2]:
cursor = results_db.find({'questions_pvalue': {'$lt': 0.05}},
{u'_id': False, u'community':True, 'questions_pvalue':True,
'questions_difference_median':True, 'category': True,
'questions_difference_mean':True, 'questions_pvalue_greater':True})
df = pandas.DataFrame(list(cursor))
In [3]:
df
Out[3]:
In [4]:
cursor = results_db.find({'answers_pvalue': {'$lt': 0.05}},
{u'_id': False, u'community':True, 'answers_pvalue':True,
'answers_difference_median':True, 'category': True,
'answers_difference_mean':True, 'answers_pvalue_greater':True})
df = pandas.DataFrame(list(cursor))
In [5]:
df
Out[5]:
In [6]:
cursor = results_db.find({'comments_pvalue': {'$lt': 0.05}},
{u'_id': False, u'community':True, 'comments_pvalue':True,
'comments_difference_median':True, 'category': True,
'comments_difference_mean':True, 'comments_pvalue_greater':True})
df = pandas.DataFrame(list(cursor))
In [7]:
df
Out[7]:
In [8]:
cursor = results_db.find({'contributions_pvalue': {'$lt': 0.05}},
{u'_id': False, u'community':True, 'contributions_pvalue':True,
'contributions_difference_median':True, 'category': True,
'contributions_difference_mean':True, 'contributions_pvalue_greater':True})
df = pandas.DataFrame(list(cursor))
In [9]:
df
Out[9]:
In [ ]: