Word clouds or tag clouds are graphical representations of word frequency that give greater prominence to words that appear more frequently in a source text. The larger the word in the visual the more common the word was in the document(s).
Word Cloud is a data visualization technique used for representing text data in which the size of each word indicates its frequency or importance. Significant textual data points can be highlighted using a word cloud. Word clouds are widely used for analyzing data from social network websites.
For generating word cloud in Python, modules needed are — matplotlib, pandas and wordcloud. To install these packages, run the following commands :
pip install matplotlib pip install pandas pip install wordcloud
The dataset used for generating word cloud is collected from the UCI Machine Learning Repository. It consists of YouTube comments on videos of popular artists.
## Python program to generate WordCloud ## importing all necessery modules from wordcloud import WordCloud, STOPWORDS import matplotlib.pyplot as plt import pandas as pd
Reading the CSV file and encoding it because of different formats in a string of having special characters, colon, comma, etc. Stopwords are English words which does not add much meaning to a sentence.
## Reads 'youtube_comments.csv' file df = pd.read_csv(r"youtube_comments.csv", encoding ="latin-1") comment_words = '' stopwords = set(STOPWORDS)
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