The goal of this project is to provide information that will assist developers to better understand client needs and, in turn, help the product become more well-known. The Play Store data contains 10,000 applications for studying the Android market. This dataset includes information about several applications and user evaluations. The Play Store applications data set(PlayStoreData.csv) offers a lot of promise to help app-making enterprises succeed. Each row in this collection contains values for its category, rating, size, and other attributes. Customer reviews of the Android apps are included in another dataset.(UserReviews.csv) Apps are being developed at an increasing rate since they are simple to make and can be profitable. In this notebook, here we compare more than 10,000 apps from different categories in the Google Play store to conduct a thorough analysis of the Android app industry. There is a vast amount of data in the Google Play Store app dataset that may be leveraged to produce insightful analysis. The success and user engagement are greatly influenced by a number of important aspects. When compared to the current Google Play store App market, our issue statement is almost inevitable. Following extensive study, it was discovered that the Google Play store library is growing rapidly every day. As a result, a range of insights may be drawn for company improvements.
Apps are being developed at an increasing rate since they are simple to make and can be profitable. In this notebook, here we compare more than 10,000 apps from different categories in the Google Play store to conduct a thorough analysis of the Android app industry. There is a vast amount of data in the Google Play Store app dataset that may be leveraged to produce insightful analysis. The success and user engagement are greatly influenced by a number of important aspects. When compared to the current Google Play store App market, our issue statement is almost inevitable. Following extensive study, it was discovered that the Google Play store library is growing rapidly every day. As a result, a range of insights may be drawn for company improvements.
We will mostly be dealing with 2 data sets for this project. :
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PlayStoreData.csv : contains information regarding Applications
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UserReviews.csv : contains information regarding Reviews and Sentiments of users
App :- Name of the App.
Category :- The classification that the App belongs in.
Rating :- App's rating on playstore.
Reviews :- Number of reviews of the App.
Size :- Size of the App.
Install :- Number of Installs of the App.
Type :- Whether the App is free or paid.
Price :- Price of the app.
Content Rating :- Audience that the app should be targeting.
Genres:- Genre under which the App falls.
Last Updated :- Date when the App was last updated.
Current Ver :- Current Version of the Application.
Android Ver :- Minimum Android Version required to run the App.
App : Name of the App.
Translated_Review : Opinions of people regarding a specific application
Sentiment : Weather the opinion/review of user is negative/positive/neutral
Sentiment_Polarity: Defines the orientation of the expressed sentiment(between -1(negative) to 1(positive) or 0(neutral))
Sentiment_Subjectivity : Refers to the degree to which a person's review is related to the App (lies between 0 to 1)
After analysing the data, we were able to determine the answers to a number of significant and intriguing questions that any Android user would find fascinating. We carried out numerous operations to obtain insights such as Rating Distribution, the Top 20 Most Expensive Apps, the Most Downloaded Categories according to Their Type, the Top 10 Most Installed Apps in the COMMUNICATION category, and many more. Overall, learning about the App industry was enjoyable and greatly aided my understanding of it.