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Click sample masks ⏩ Reference 🔎Ĭontributions are always welcomed. To get accurate shape use large datasets like lyrics of songs or wikipedia paragraphs.Īlso You can generate data directly by importing wikipedia and then scraping from wikipedia page. But you’d often have to generate word clouds dynamically or in large batches. You can use the Monkeylearn word cloud generator tool for offline use cases. Also, some websites use word clouds to show the most popular topics on the site. You can used any dataset consisting of words or numbers. Word clouds are great for finding out customer sentiment from reviews. wc WordCloud() wc.generate(article.text) plt. After that, we call the word cloud function and display the word cloud. The wordcloud library is used to generate the word cloud, while matplotlib is used to display the results of the word cloud. width - height - background color - contour color - mask - collocations Step7: Plot the Wordcloud Step8: Save Image Here we use the wordcloud library and matplotlib. Step1: Import Required libraries Step2: Generate Data for wordcloud Step3: Clean Data - Use stopwords to remove words like 'is', 'but', 'and', etc - Remove spaces as well Step4: write function to plot wordcloud using matplotlib Step5: Import a shaped image to np array Step6: Generate wordcloud using WordCloud.
