Word Frequency Statistics and Word Cloud Generation with Python

This article demonstrates how to perform word‑frequency statistics in Python using the collections.Counter class and how to visualize the frequencies with the WordCloud library.

Three methods for obtaining text are presented: (1) a predefined list of words, (2) randomly generated characters, and (3) reading a text file. Each method includes a short code example.

Example of counting frequencies in a fixed list:

from collections import Counter
cnt = Counter()
for word in ['red', 'blue', 'red', 'green', 'blue', 'blue']:
    cnt[word] += 1
print(cnt.most_common())

Example of generating a random character list and counting its frequencies:

import random
import collections
import string
# Combine uppercase and lowercase letters
str1 = string.ascii_letters
strlist = [random.choice(str1) for i in range(100)]
strcount = collections.Counter(strlist)
# Print the top 10 most common letters
for key, value in strcount.most_common(10):
    print(key, value)

The article then introduces the WordCloud library for creating word‑cloud images, referencing an external blog for further details. It shows several example images and explains how to adjust parameters such as font_path (e.g., msyh.ttf , msyhbd.ttf , simsun.ttc , simhei.ttf ) and colormap , which controls the color scheme of the cloud.

Common colormap options are listed with brief descriptions, for example: autumn transitions from red to orange to yellow, cool moves from cyan‑green to magenta, jet goes from blue through green, yellow, orange to red, and many others such as gray , hot , pink , prism , etc.

These settings allow users to customize the appearance of the generated word cloud to match their visual preferences or branding requirements.