import nltk
#import re
#from nltk.draw.tree import draw_trees
import string
import io
import StringIO
import counter
from nltk.corpus import state_union
from nltk.tokenize import word_tokenize
from nltk.tokenize import PunktSentenceTokenizer
from nltk.tag import pos_tag
text=state_union.raw("/home/hduser/mail_file")
cust_tonizer=PunktSentenceTokenizer(text)
tokenized=cust_tonizer.tokenize(text)
words=word_tokenize(text)
tags=pos_tag(words)
for t in tags:
    if t[1] == "JJ" or t[1] == "JJR":
       data = t[0]
       #matches=value.append(t[0])
       #fdist = nltk.FreqDist(value)
       #most_common = fdist.max()
       #top_three = fdist.keys()[:3]
       print data
       #print top_three
    else:
         continue

val=data.split('n')
counter={}
for line in val:
    print line
    counter[line] = counter.get(line, 0) + 1
    cnt=sorted([ (freq,word) for word, freq in counter.items() ], reverse=True)[:3]
    print cnt

fhand = open('results.txt')     # I assume the results (good, better, etc.) are in a text file
marks = dict()                        # Empty dictionary, will include the frequency of all results

for line in fhand:                    # Going through the marks in the text file (all words are lowercased)
    if len(line) > 1:
        line = line.lower().strip()
        marks[line] = marks.get(line, 0) + 1

max_value = 0                     # This pair of variables will store the most frequent word 
max_key = ''                         # '' is an empty string

for key, value in marks.items():
    if value > max_value:
        max_value = value
        max_key = key

print(max_key, max_value)            #Hope this is what you are looking for.
fhand.close()