tallied.append(tally/len(z))
elif tally<0:
final ='NEG'
tallied.append(tally/len(z))
elif tally==0:
final ='NEU'
tallied.append(tally)
score.append(final)
ftally.append(tally)
""" add column to dataframe based on list """
train['New_Rating']=score
train['Tally']=ftally
train['Pct']=tallied
train['Sentiment1']=APIsent
train['Sentiment2']= Indisent
train.to_csv('revised_NYC_comments_train.csv')
""" text collection exploration """
"""
reviewcollection.concordance("very") #word concordance for every review
fdist1 = FreqDist(reviewcollection) #frequency distribution of text, indexed
fdist1.most_common(10) #most frequent 10 words
wdpairs = list(bigrams(reviewcollection)) #all pairs of words that occur together in the text
reviewcollection.collocations() #returns most frequent pairs
reviewcollection.findall(r"<very> <.*>") #find phrases in text with a specific pattern
"""
