📱 Google Play Store Apps Analysis

This project provides an end-to-end exploratory data analysis (EDA) of mobile applications listed on the Google Play Store. Using a dataset containing various features such as app category, rating, installs, size, and price, we draw insights on trends and behaviors in the mobile app ecosystem.

📊 Key Objectives

• Clean and preprocess the dataset
• Analyze the distribution of app categories and content ratings
• Examine relationships between ratings, size, installs, and pricing
• Visualize sentiment distribution of user reviews
• Identify patterns in the top app categories and popular apps

🧰 Tools & Libraries Used

• Python 🐍
• Pandas & NumPy
• Matplotlib & Seaborn
• Plotly
• WordCloud
• Jupyter Notebook

📈 Visualizations & Insights

• Category-wise app distribution
• Rating trends across categories and price types
• Install count vs. app size and pricing (bubble chart)
• Word clouds for positive and negative reviews
• Sentiment distribution per rating group (stacked bar chart)
• Top 5 categories by app count with user sentiment breakdown