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Word Cloud

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Create a Word Cloud

Create a Word Cloud to visualize the most frequent words in a text file. Word Clouds are also known as Tag Clouds and are a useful tool for initial visual exploration of text data in any NLP project. Word Clouds are typically used to depict keyword metadata on websites, or to visualize free form text. Important words are highlighted with a bigger font or stronger color.

%%capture 
!pip install wordcloud
# Load packages
import matplotlib.pyplot as plt
from wordcloud import WordCloud, STOPWORDS
# Upload your data as a .txt file and load it as a data frame 
text = open('End_of_the_World_REM.txt', 
            mode='r', 
            encoding='utf-8') \
            .read().replace('\n',' ')
text[:1000]
# change the value to black
def black_color_func(word, font_size, position,orientation,random_state=None, **kwargs):
    return("hsl(0,100%, 1%)")

wc = WordCloud(background_color="white",           # select background color
               width=3000,                         # set wight
               height=2000,                        # set height
               max_words=1000).generate(text)       # set max amount of words

wc.recolor(color_func = black_color_func)          # set the word color to black
plt.figure(figsize=[15,10])                        # set the figsize
plt.imshow(wc, interpolation="bilinear")           # plot the wordcloud
plt.axis("off")                                    # remove plot axes
plt.savefig('wordcloud.png')                       # save as png
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