Generate Word Clouds Of Any Shape In Python

In this article, we will discuss how to create word clouds of any shape in Python. 

The term WordCloud refers to a data visualization technique for showing text data in which the size of each word indicates its frequency or relevance. To create a word cloud of any shape, use Python’s Matplotlib, word cloud, NumPy, and PIL packages.

Stepwise Implementation

Let’s have a look at the step-by-step implementation –

Step 1: Install the following modules as listed below-

pip install matplotlib
pip install wordcloud 

Step 2: Import the following modules as listed below-

import matplotlib.pyplot as plt
from wordcloud import WordCloud, STOPWORDS
import numpy as np
from PIL import Image

Step 3: Follow the steps below-

• Give the full path to the text file you intend to use.
• In read mode, open the text file.
• Finally, encode and read it.
• In this article following text file will be used- Text

text = open(r'C:\Users\Dell\Desktop\Wordcloud\Text.txt',
            mode='r', encoding='utf-8').read()

Step 4: Follow the steps below-

• Give the entire image path that we will use to get our output in the same shape.
• Then, using the image.open function, open the image.
• After that, use NumPy to create the image’s array.
• The below image will be used in this article for the desired shape

mask = np.array(Image.open(r'C:\Users\Dell|Downloads\Garbage\GFG.png'))

Step 5: Create a wordcloud by integrating a stopword, a mask, a background color, the maximum number of words in the wordcloud, the height of the mask, and the width of the mask.

• stopwords- It is used to avoid unnecessary characters such as ‘./-[{)*&^%~@!#%^&].
• mask- Mask is the shape to which we will convert our wordcloud.
• background_color- We can use whatever background color we like, such as black, green, and so on.
• max_words- It is the maximum number of words that a wordcloud can contain.
• max_font- It’s maximum font size.
• The width and height of the wordcloud are represented by Width and Height.

wc = WordCloud(stopwords = STOPWORDS,
               mask = mask, background_color = "white",
               max_words = 2000, max_font_size = 500,
               random_state = 42, width = mask.shape[1],
               height = mask.shape[0])

Step 6: 

• Now, using the generate function, we will create a wordcloud from the provided text.
• To display image data, use the imshow function.
• We will try to off the x and y-axis.
• Finally, we will display the generated wordcloud using the show function defined within matplotlib.

wc.generate(text)
plt.imshow(wc, interpolation="None")
plt.axis('off')
plt.show()

Below is the complete implementation.

Python3

# Python3 program to implement
# the above approach
# Import the following modules

# pip install matplotlib
import matplotlib.pyplot as plt

# pip install wordcloud
from wordcloud import WordCloud, STOPWORDS
import numpy as np
from PIL import Image

# Give the whole path of the text file,
# open it, read it, and encode it.
text = open(r'C:\Users\Dell\Desktop\Wordcloud\Text.txt',
            mode = 'r', encoding = 'utf-8').read()

# The Image shape in which you wanna convert it to.
mask = np.array(Image.open(
                r'C:\Users\Dell\Downloads\Garbage\GFG.png'))

# Now inside the WordCloud, provide some functions:
# stopwords - For stopping the unuseful words
# like [,?/\"]
# font_path - provide the font path to which you
# wanna convert it to.
# max_words - Maximum number of words in the
# output image. Also provide height and width
# of the mask
wc = WordCloud(stopwords = STOPWORDS,
               mask = mask,
               background_color = "white",
               max_words = 2000,
               max_font_size = 500,
               random_state = 42,
               width = mask.shape[1],
               height = mask.shape[0])

# Finally generate the wordcloud of the given text
wc.generate(text)
plt.imshow(wc, interpolation = "None")

# Off the x and y axis
plt.axis('off')

# Now show the output cloud
plt.show()

Output:

Change Font Size

Follow the steps below to change the font size of the words in the word cloud-

• First, select a font from this collection.
• Download the font file—you see that it is in .zip format.
• Open the zip file and extract the TTF or otf file from it.
• Now just provide the full path of the TTF or otf file.

path = r'C:\Users\Dell\Downloads\Garbage\Candy Beans.otf'

Complete Code:

Python3

# Python3 program to implement
# the above approach
# Import the following modules

# pip install matplotlib
import matplotlib.pyplot as plt

# pip install wordcloud
from wordcloud import WordCloud, STOPWORDS
import numpy as np
from PIL import Image

# Give the whole path of the text file,
# open it, read it, and encode it.
text = open(r'C:\Users\Dell\Desktop\Wordcloud\Text.txt',
            mode = 'r', encoding = 'utf-8').read()

# For changing the fonts of wordcloud fonts
path = r'C:\Users\Dell\Downloads\Garbage\Candy Beans.otf'

# The Image shape in which you wanna convert it to.
mask = np.array(Image.open(
                r'C:\Users\Dell\Downloads\Garbage\GFG.png'))

# Now inside the WordCloud, provide some functions:
# stopwords - For stopping the unuseful words
# like [,?/\"]
# font_path - provide the font path to which
# you wanna convert it to.
# max_words - Maximum number of words in
# the output image.
# Also provide height and width of the mask
wc = WordCloud(stopwords = STOPWORDS,
               font_path = path,
               mask = mask,
               background_color = "white",
               max_words = 2000,
               max_font_size = 500,
               random_state = 42,
               width = mask.shape[1],
               height = mask.shape[0])

# Finally generate the wordcloud of the given text
wc.generate(text)
plt.imshow(wc, interpolation = "None")

# Off the x and y axis
plt.axis('off')

# Now show the output cloud
plt.show()

Output:

Change the Font Color

Follow the steps below to change the font color of the text in a word cloud-

• Create a function to change the font color.
• Because the HSL of each color is unique, just pass the HSL and return it.

Complete Code:

Python3

# Python3 program to implement
# the above approach
# Import the following modules

# pip install matplotlib
import matplotlib.pyplot as plt

# pip install wordcloud
from wordcloud import WordCloud, STOPWORDS
import numpy as np
from PIL import Image

# Function for changing the color of the text
def one_color_func(word = None, font_size = None,
                   position = None, orientation = None,
                   font_path = None, random_state = None):

   # This HSL is for the green color
    h = 99
    s = 62
    l = 45
    return "hsl({}, {}%, {}%)".format(h, s, l)

# Give the whole path of the text file,
# open it, read it, and encode it.
text = open(r'C:\Users\Dell\Desktop\Text.txt',
            mode = 'r', encoding = 'utf-8').read()

# For changing the fonts of wordcloud fonts
path = r'C:\Users\Dell\Downloads\Garbage\Candy Beans.otf'

# The Image shape in which you wanna convert it to.
mask = np.array(Image.open(
                r'C:\Users\Dell\Downloads\Garbage\GFG!.png'))

# Now inside the WordCloud, provide some functions:
# stopwords - For stopping the unuseful words
# like [,?/\"]
# font_path - provide the font path to which
# you wanna convert it to.
# max_words - Maximum number of words in
# the output image.
# Also provide height and width of the mask
wc = WordCloud(stopwords = STOPWORDS,
               font_path = path,
               mask = mask,
               background_color = "white",
               max_words = 2000,
               max_font_size = 500,
               random_state = 42,
               width = mask.shape[1],
               height = mask.shape[0],
               color_func = one_color_func)

# Finally generate the wordcloud of
# the given text
wc.generate(text)
plt.imshow(wc, interpolation = "None")

# Off the x and y axis
plt.axis('off')

# Now show the output cloud
plt.show()

Output: