cloud_generator.py

from wordcloud import WordCloud, STOPWORDS
import matplotlib.pyplot as plt
import pandas as pd

# Python program to generate WordCloud

# importing all necessary modules
from wordcloud import WordCloud, STOPWORDS
import matplotlib.pyplot as plt
import pandas as pd
import re
import csv
import tensorflow

path = tensorflow.keras.utils.get_file('shakespeare.txt',
                                       'https://storage.googleapis.com/download.tensorflow.org/data/shakespeare.txt')
text = open(path, 'rb').read().decode(encoding='utf-8').lower()

text = text.split()
comment_words = ''
stopwords = set(STOPWORDS)

# iterate through the csv file
for val in text:

    # typecaste each val to string
    val = str(val)

    # split the value
    tokens = val.split()

    # Converts each token into lowercase
    for i in range(len(tokens)):
        tokens[i] = tokens[i].lower()

    comment_words += " ".join(tokens) + " "

wordcloud = WordCloud(width=1200, height=400,
                      background_color='white',
                      stopwords=stopwords,
                      min_font_size=10).generate(comment_words)

# plot the WordCloud image
plt.figure(figsize=(8, 8), facecolor=None)
plt.imshow(wordcloud)
plt.axis("off")
plt.tight_layout(pad=0)

plt.show()