Mentimeter Wordcloud Question Scraping

MentimeterWordcloudQuestionScraping.py

# Mentimeter Wordcloud Question Scraping

import http.client,json
import pandas as pd

question_id='000000000000'

HTTP_C=http.client.HTTPSConnection('api.mentimeter.com')
HTTP_C.request('GET','/questions/'+question_id+'/result?isPublic=true')
HTTP_R=HTTP_C.getresponse()
data=HTTP_R.read()
data=json.loads(data)
data=data['results']

words_bin=[]
	for word in words: words_bin+=[word]
for respondent in data:
	words=respondent.split()

df=pd.DataFrame(words_bin)[0].value_counts().agg([lambda x: 100*x/len(words_bin),lambda x: x])
df.columns=['%','count']
df.nlargest(10,'count','all')