Step-by-Step EDA Analysis of Google Play Store Data | Data Science Project скачать в хорошем качестве

Step-by-Step EDA Analysis of Google Play Store Data | Data Science Project

Dive deep into a comprehensive Exploratory Data Analysis (EDA) of Google Play Store data to uncover hidden trends, insights, and patterns in app development and user engagement. This video provides a step-by-step guide to understanding and analyzing key aspects of the dataset, including ratings, categories, reviews, installs, and more, all using Python's powerful data analysis libraries. 📌 What You’ll Learn in This Video: Data Cleaning & Preprocessing: Learn how to handle missing values, remove duplicates, and ensure data consistency. App Category Analysis: Discover which app categories dominate the Google Play Store and their average ratings and reviews. User Rating Insights: Analyze the relationship between app size, pricing, and user ratings to identify patterns that matter. Installs & Popularity Trends: Understand how app installs vary across categories and what drives higher user engagement. Data Visualization: Create stunning visualizations using Matplotlib and Seaborn to communicate your findings effectively. This video is perfect for beginners in *data science* or *machine learning* who want to learn hands-on techniques for working with real-world datasets. By the end of this video, you’ll have the knowledge and tools to approach EDA for your own projects with confidence. 💡 Tools Used: Python Pandas Matplotlib Seaborn 👉 Don’t forget to like, share, and subscribe to the channel for more tutorials and data science project walkthroughs. #GooglePlayStoreEDA #DataScienceProject #ExploratoryDataAnalysis #PythonProgramming #DataVisualization #DataScienceForBeginners #SeabornTutorial #PandasTutorial #BigDataAnalysis #AppDevelopmentInsights #GooglePlayStoreAnalysis #TechDataAnalysis