Looking for a Google Play apps dataset to analyze mobile app trends? The Google Play Store Apps Dataset delivers ~10,000 app records from the Google Play Store, including key app metadata like app name, category, rating, installs, price, developer details, and more. This dataset is ideal for app market research, mobile analytics, app store optimization studies (ASO), data science projects, and trend analysis.

Collect structured data on apps across genres and niches, so you can build visualizations, train machine-learning models, analyze user engagement, or compare categories like games, productivity, health & fitness, and finance.

Rich App Metadata: Includes app_id, app_name, category, rating, review_count, price, installs, content_rating, genres, last_updated, current_version, android_version, developer_name, developer_email, description, url, screenshots, and timestamps like scraped_at.

• CSV Format – Ready to Use: Instantly downloadable and easy to integrate into dashboards or analytics platforms.
  
• Large-Scale Coverage: Nearly 10,000 apps across multiple categories, helping reveal patterns in user preferences and market dynamics.
  
• Supports Various Projects: Works well for trend forecasting, sentiment analysis, ASO testing, recommendation systems, and academic research.
  

• App Market Research: Analyze the top categories, rating patterns, install trends, and pricing strategies.
  
• Data Science & ML Models: Use the dataset to build predictive models for installs, ratings, or category clustering.
  
• App Store Optimization (ASO): Evaluate keywords, category performance, and rating impacts on visibility.
  
• Competitive Analysis: Compare apps in niche segments to uncover opportunities or trends.
  
• Academic Projects & Teaching: Great for students and educators needing real, structured app store data.
  

• Total Records: ~10,000 Google Play apps.
  
• Data Fields: app_id, app_name, category, rating, review_count, price, installs, content_rating, genres, last_updated, current_version, android_version, developer_name, developer_email, description, url, screenshots, scraped_at.
  
• Format: CSV – ready for analysis with Excel, Python, R, SQL, or BI tools.
  
• Delivery: Instant CSV download upon purchase.
  
• Sample Available: Preview a sample to inspect the field structure before buying.

• App market analysts tracking patterns in Google Play.
  
• Developers & product teams evaluating competitive landscapes.
  
• Data scientists & ML engineers building predictive models and dashboards.
  
• Digital marketers studying rating effects and category performance.
  
• Students & researchers analyzing app store data for projects.
  

• Saves Time: No need to build and maintain scrapers or handle API limitations.
  
• Pre-cleaned & Structured: Ready for exploration right out of the box.
  
• Avoid Rate-Limit & Block Issues: No need to manage rotating IPs or bot detection.
  
• Broad Coverage: A large dataset across categories provides reliable insights.