![]() ![]() ![]() Import the dataset into a variable of your choice. Selecting the Datasetįor this example, we are using Popular Dataset Top Games on Google Play Storefrom Kaggle.ĭownload the Dataset and save it in your current working directory for hassle-free code implementation. Import the following libraries which are required to create a Word Cloud import pandas as pdįrom wordcloud import WordCloud 2. How To Create Word Cloud in PythonĪ Word Cloud in Python can be created in the following steps: 1. For example, Amul comes up with a creative advertisement based on the current issue or trend. Trending TopicsĪdvertising Agencies would often need to know what is trending to create the next advertisement in context with trending topics. Elections, the word Clouds of both the Republican Party and Democratic Party candidate speeches were readily available by analysts to let people decide. Analysts often create a Word Cloud of candidate’s speeches from different parties to analyze and produce results to let people know which candidate is focusing on what areas of improvisation. ![]() Thus, the candidate’s support team would analyze the candidate’s speech and create a Word Cloud to select words for the next speech to keep a balance of agenda checklist. Often the candidates of elections keep a checklist of agenda to talk about during the campaigns. For example, A firm ‘ABC’ released a new Television, and based on the feedback received, the firm can make changes accordingly in the next series of Televisions. This would help the firm determine if the feedback is positives or negatives and respective areas of improvement. Thus, Word Cloud would play a key role in getting top keywords among the feedback. It would be very difficult for the stakeholders to read and make note of every feedback. Say the firm received 1000 feedbacks from different users. Assume that a business launches a product and wants to know customer’s feedback. Word Clouds are widely being used in industries by stakeholders to analyze the feedback received from end-users. A few of the popular applications of Word Clouds are: Word Cloud finds its way in numerous applications among several domains. Word Cloud vs Tag Cloud Trend from Google Trends (Source – Personal Computer) And thus, we will be creating our Word Cloud by using the Frequency type. A Word Cloud must always be semantically meaningful and must represent what it is meant for.Īlthough, there are different ways by which Word Clouds can be created but the most widely used type is by using the Frequency of Words in our corpus. More number of words does not always mean a better Word Cloud as it becomes cluttery and difficult to read. The number of words plays an important role while creating a Word Cloud. Word Cloud can be built in varying shapes and sizes based on the creators’ vision. A bigger font size of a word portrays its prominence more relative to other words in the cluster. Thus, this representation helps to determine words of prominence. These words are clustered together to form a Word Cloud.Įach word in this cloud has a variable font size and color tone. These keywords typically are single words that depict the context of the webpage the word cloud is being made from. Word Cloud or Tag Clouds is a visualization technique for texts that are natively used for visualizing the tags or keywords from the websites. In the next few lines, we will learn about the Word Clouds, their Applications, and how to create word cloud in Python. Whether to discover the political agendas of aspiring election candidates of a country or to analyze the customer reviews on the recently launched product, one can get a visual representation by plotting the Word Cloud. Word Clouds came out to be a game-changer visualization technique for understanding and determining patterns and evolving trends. This article was published as a part of the Data Science Blogathon ![]()
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