GooglePlayStore-DataAnalysis
Dataset - Google Play Store
Project Description
Mobile apps are everywhere. They are easy to create and can be lucrative. Because of these two factors, more and more apps are being developed. In this project, We will do a comprehensive analysis of the Android app market by comparing over ten thousand apps in Google Play across different categories. We'll look for insights in the data to devise strategies to drive growth and retention. The data for this project was scraped from the Google Play website. While there are many popular datasets for Apple App Store, there aren't many for Google Play apps, which is partially due to the increased difficulty in scraping the latter as compared to the former. The data files are as follows: googleplaystore.csv :contains all the details of the apps on Google Play. These are the features that describe an app like App name, Category, Rating, Reviews, Size, Installs, Type, Price(if any), Content Rating, Genres, Last updated, Current Ver, and Android Ver. googleplaystore_user_reviews.csv :contains 100 reviews for each app, most helpful first. The text in each review has been pre-processed, passed through a sentiment analyzer engine and tagged with its sentiment score. The datafile googleplaystore_user_reviews contains datafields like App name and their respective translated reviews, Sentiment, sentiment_polarity and sentiment_subjectivity. This datafile is ideal for Sentiment Analysis of the user reviews on various apps listed on Play store.
Source: Kaggle
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Inspiration
The Play Store apps data has enormous potential to drive app-making businesses to success. Actionable insights can be drawn for developers to work on and capture the Android market!