Frequency Distribution in Python

When processing text, you often need to count the frequency of a word in a text. You can count words by using the word_tokenize() function and appending the results to a list, as shown in the following program.

from nltk.tokenize import word_tokenize
from nltk.corpus import gutenberg

sample = gutenberg.raw("blake-poems.txt")

token = word_tokenize(sample)
wlist = []

for i in range(50):
wlist.append(token[i])

wordfreq = [wlist.count(w) for w in wlist]
print("Pairsn" + str(zip(token, wordfreq)))

When we run the above program, we get the following output:

[([', 1), (Poems', 1), (by', 1), (William', 1), (Blake', 1), (1789', 1), (]', 1), (SONGS', 2), (OF', 3), (INNOCENCE', 2), (AND', 1), (OF', 3), (EXPERIENCE', 1), (and', 1), (THE', 1), (BOOK', 1), (of', 2), (THEL', 1), (SONGS', 2), (OF', 3), (INNOCENCE', 2), (INTRODUCTION', 1), (Piping', 2), (down', 1), (the', 1), (valleys', 1), (wild', 1), (,', 3), (Piping', 2), (songs', 1), (of', 2), (pleasant', 1), (glee', 1), (,', 3), (On', 1), (a', 2), (cloud', 1), (I', 1), (saw', 1), (a', 2), (child', 1), (,', 3), (And', 1), (he', 1), (laughing', 1), (said', 1), (to', 1), (me', 1), (:', 1), (``', 1)]

Conditional Frequency Distribution

Conditional frequency distribution is used when we want to count the number of words that meet a certain condition in a set of text.

import nltk
#from nltk.tokenize import word_tokenize
from nltk.corpus import brown

cfd = nltk.ConditionalFreqDist(
(genre, word)
for genre in brown.categories()
for word in brown.words(categories=genre))
categories = ['hobbies', 'romance', 'humor']
searchwords = [ 'may', 'might', 'must', 'will']
cfd.tabulate(conditions=categories, samples=searchwords)

When we run the above program, we get the following output −

may might must will
hobbies 131 22 83 264
romance 11    51 45 43
  humor 8 8 9 13