📱 Google Play Store App Analysis

This project is a data cleaning and visualization notebook using the Google Play Store Apps Dataset. It was developed as part of the "Veri Bilimi ve Makine Öğrenmesi 2025: 100 Günlük Kamp" Udemy course by Atıl Samancıoğlu.

🔍 Project Objectives

Clean and preprocess the Google Play Store dataset.

Handle missing and duplicate data.

Analyze key trends like:

Most installed and highest rated apps

Relationship between app category and rating

Distribution of app sizes, prices, and reviews

📊 Tools & Libraries

Python (pandas, matplotlib, seaborn)

Jupyter Notebook (ipynb format)

Data Source: Kaggle Google Play Store Dataset

💡 Key Features

Cleaned 10,000+ app entries by:

Removing nulls and duplicates

Converting strings to numeric types (e.g., Size, Installs, Price)

Created visualizations such as:

Boxplots for outlier detection

Category-wise ratings

Heatmaps for correlation analysis