user1610950 user1610950 - 11 months ago 131
Python Question

Python nltk counting word and phrase frequency

I am using NLTK and trying to get the word phrase count up to a certain length for a particular document as well as the frequency of each phrase. I tokenize the string to get the data list.

from nltk.util import ngrams
from nltk.tokenize import sent_tokenize, word_tokenize
from nltk.collocations import *

data = ["this", "is", "not", "a", "test", "this", "is", "real", "not", "a", "test", "this", "is", "this", "is", "real", "not", "a", "test"]

bigrams = ngrams(data, 2)

bigrams_c = {}
for b in bigrams:
if b not in bigrams_c:
bigrams_c[b] = 1
bigrams_c[b] += 1

the above code gives and output like this:

(('is', 'this'), 1)
(('test', 'this'), 2)
(('a', 'test'), 3)
(('this', 'is'), 4)
(('is', 'not'), 1)
(('real', 'not'), 2)
(('is', 'real'), 2)
(('not', 'a'), 3)

which is partially what I am looking for.

My question is, is there a more convenient way to do this for say up to phrases that are 4 or 5 in length without duplicating this code only to change the count variable?

Answer Source

Yeah don't run this loop, use collections.Counter(bigrams) or pandas.Series(bigrams).value_counts() to compute the counts in a one-liner.