NOTE: Before running this notebook, be sure to place your copy of RomeoAndJuliet.txt in the same folder as the notebook.

12.3.2 Visualizing Word Frequencies with Word Clouds

• Open source wordcloud module’s WordCloud class
• Uses matplotlib under the hood

Installing the wordcloud Module

• conda install -c conda-forge wordcloud
  • Windows users should run the Anaconda Prompt as an Administrator

Loading the Text

from pathlib import Path

text = Path('RomeoAndJuliet.txt').read_text()

Loading the Mask Image that Specifies the Word Cloud’s Shape

• WordCloud fills non-white areas of a mask image with text
• Load the mask using the imread function from the imageio module that comes with Anaconda

import imageio

mask_image = imageio.imread('mask_heart.png')

Configuring the WordCloud Object

• 400-by-200 pixels, unless you specify width and height
• If you specify a mask image without width and height, WordCloud uses the image’s size
• WordCloud assigns random colors from a color map
• Matplotlib’s named color maps
• Complete list of WordCloud’s keyword arguments

from wordcloud import WordCloud   

wordcloud = WordCloud(width=1000, height=1000, 
    colormap='prism', mask=mask_image, background_color='white')

Generating the Word Cloud

• WordCloud’s generate method receives the text to use in the word cloud as an argument and creates the word cloud, which it returns as a WordCloud object

wordcloud = wordcloud.generate(text)

• removes stop words from the text argument, using the wordcloud module’s built-in stop-words list
• calculates the word frequencies for the remaining words
• builds the cloud with a maximum of 200 words by default, but can specify max_words keyword argument

Saving the Word Cloud as an Image File

wordcloud = wordcloud.to_file('RomeoAndJulietHeart.png')

Generating a Word Cloud from a Dictionary

• If you have a dictionary of word counts, WordCloud’s fit_words method can create a word cloud from it, but does not remove the stop words from the dictionary

Displaying the Image with Matplotlib

%matplotlib inline

import matplotlib.pyplot as plt

plt.imshow(wordcloud)

<matplotlib.image.AxesImage at 0x11c5954e0>

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