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# Lets See how the movies are classified from nltk.corpus import movie_reviews all_cats =  for w in movie_reviews.categories(): all_cats.append(w.lower()) print(all_cats)
from nltk.corpus import movie_reviews from nltk.tokenize import sent_tokenize fields = movie_reviews.fileids() sample = movie_reviews.raw("pos/cv944_13521.txt") token = sent_tokenize(sample) for lines in range(4): print(token[lines])
meteor threat set to blow away all volcanoes & twisters ! summer is here again ! this season could probably be the most ambitious = season this decade with hollywood churning out films like deep impact , = godzilla , the x-files , armageddon , the truman show , all of which has but = one main aim , to rock the box office . leading the pack this summer is = deep impact , one of the first few film releases from the = spielberg-katzenberg-geffen's dreamworks production company .
import nltk from nltk.corpus import movie_reviews fields = movie_reviews.fileids() all_words =  for w in movie_reviews.words(): all_words.append(w.lower()) all_words = nltk.FreqDist(all_words) print(all_words.most_common(10))
[(,', 77717), (the', 76529), (.', 65876), (a', 38106), (and', 35576), (of', 34123), (to', 31937), (u"'", 30585), (is', 25195), (in', 21822)]