EDA-Play-Store-App-Review-Analysis

Play Store App Review Analysis

This project aims to provide insights into the trends and characteristics of apps available on the Google Play Store by analyzing user reviews and app data.

Project Overview

The analysis is based on the exploration of various aspects of app data, including categories, user ratings, installs, and pricing. Through exploratory data analysis (EDA) and visualization, the project uncovers trends and patterns in the Play Store ecosystem.

Key Findings

• Trending Categories: Games, Communication, and Tools are among the most trending categories in terms of user installs, indicating a focus on entertainment and utility.
• Quality Over Quantity: Despite fewer apps in categories like Games and Communication, they tend to have higher user engagement, suggesting a focus on quality over quantity by developers.
• Rating and User Engagement: Apps with high ratings (above 4.0) correlate with high numbers of reviews and installs, particularly in categories like Social, Communication, and Games.
• Market Trends: While categories like Games, Social, Communication, and Tools dominate in terms of installs and user engagement, the top 5 most expensive apps are mainly from Finance and Lifestyle categories.
• App Characteristics:
  • Percentage of free apps: ~92%
  • Percentage of apps with no age restrictions: ~82%
  • Most competitive category: Family
  • Category with the highest number of installs: Game
  • Category with the highest average app installs: Communication
  • Percentage of top-rated apps: ~80%
  • Median size of all apps: 12 MB
  • There are 20 free apps with over a billion installs
  • Minecraft is the only paid app with over 10M installs, generating significant revenue.
  • Finance category has the highest average installation fee for paid apps.
  • Facebook is the most popular app based on the number of reviews.

Tools and Skills

• Python: Used for data analysis, manipulation, and visualization.
• Pandas: Employed for data manipulation and analysis.
• Matplotlib and Seaborn: Utilized for data visualization to create insightful plots and graphs.
• Jupyter Notebook: Used as the primary environment for conducting the analysis and documenting the process.

Takeaways

• Understanding Market Trends: Gain insights into the prevailing trends and dynamics of the Google Play Store ecosystem.
• Importance of User Engagement: Recognize the significance of user engagement metrics such as ratings, reviews, and installs in determining app success.
• Quality vs. Quantity: Learn how focusing on quality over quantity can lead to better user engagement and success, even in competitive categories.
• Market Positioning: Understand the importance of market positioning and category selection for app developers aiming to maximize their reach and impact.

Acknowledgments

This project was completed as part of the Data Science Trainee program at AlmaBetter.