How to create a wordcloud and what is it helpful for Explain with an example?
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How to create a wordcloud and what is it helpful for Explain with an example?

How to create a wordcloud and what is it helpful for Explain with an example?

This recipe helps you create a wordcloud and what is it helpful for Explain with an example

Recipe Objective

How to create a wordcloud and what is it helpful for?

Wordcloud is nothing but a data visualization technique mainly used for text representation it is also called a tag cloud. In this, the size of each word indicates its frequency or importance of that word. It displays a list of words, the importance of each is shown by font color or size.

What is it useful for: Analyzing text data from social media websites. Significant textual points can be highlighted using a word cloud. In a Customer service process useful to analyze customer feedback. Identifying new SEO(Search engine optimization) Keyword to target. And Many More...

Step 1 - Install Wordcloud

!pip install wordcloud

Step 2 - Import the necessary libraries

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

Step 3 - Take a sample data set

df_sample = pd.read_csv('/content/Youtube_Comments_data.csv', encoding ="latin-1") df_sample.head()

For sample data we are using youtube comments data on videos of famous artist.

Step 4 - Store comments in a simple string and stopwords in a variable

words_comments = '' My_stopwords = set(STOPWORDS)

Step 5 - Iterate through the Sample data.

for elements in df_sample.CONTENT: elements = str(elements) tokenization = elements.split() for i in range(len(tokenization)): tokenization[i] = tokenization[i].lower() words_comments = words_comments + " ".join(tokenization)+" "

Here in the above in first for loop we are firstly typecasting the each element into string then splitting the values. After that in the second for loop we are converting each value into lower case.

Step 5 - Create wordcloud for visualization

My_wordcloud = WordCloud(width = 800, height = 800, background_color ='white', stopwords = My_stopwords, min_font_size = 10).generate(words_comments)

Step 6 - Plot the cloud Image

plt.figure(figsize = (8, 8), facecolor = None) plt.imshow(My_wordcloud) plt.axis("off") plt.tight_layout(pad = 0) plt.show()

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