Extract Phrases Counts from Corpus taken from http://www.markhneedham.com/blog/2015/01/19/pythonnltk-finding-the-most-common-phrases-in-how-i-met-your-mother/

phrases.py

import nltk
import string
from collections import Counter

def untokenize(ngram):
    tokens = list(ngram)
    return "".join([" "+i if not i.startswith("'") and \
                             i not in string.punctuation and \
                             i != "n't"
                          else i for i in tokens]).strip()
                          

def extract_phrases(text, phrase_counter, length):
    for sent in nltk.sent_tokenize(text):
        words = nltk.word_tokenize(sent)
        for phrase in nltk.util.ngrams(words, length):
            if all(word not in string.punctuation for word in phrase):
                phrase_counter[untokenize(phrase)] += 1
                

if __name__ == "__main__":
  phrase_counter = Counter()
  sent = ["This is good", "This is awesome", "Weather is good"]
  for s in sent:
    extract_phrases(s,phrase_counter, 2)
  print phrase_counter.most_common(5)