🔍 Zomato Bangalore Restaurants EDA | Data Cleaning & Visualization | Python Pandas & Seaborn 📊

Resources and Code:
Find the full code here:
https://www.kaggle.com/code/codingloa...

Download the dataset here:
https://www.kaggle.com/datasets/himan...

In this project, I performed Exploratory Data Analysis (EDA) on the Zomato Bangalore Restaurants dataset to uncover insights about restaurants, cuisines, ratings, and pricing trends in Bangalore. I cleaned the data by removing duplicates and handling missing values, followed by detailed analysis and visualizations to extract meaningful patterns.

🔥 Project Highlights:
✅ Dataset: Zomato Bangalore Restaurants
✅ Data Cleaning: Removed duplicate rows & handled missing values
✅ EDA: Uncovered insights on restaurant types, cuisine distribution, pricing, and ratings
✅ Visualizations: Used Matplotlib & Seaborn for compelling insights
✅ Findings: Key trends in restaurant ratings, popular cuisines, and cost analysis

📌 Technologies Used:
🔹 Python | Pandas | NumPy | Matplotlib | Seaborn | Plotly

📊 Key Insights:
📍 Which cuisines are most popular in Bangalore?
📍 How do restaurant ratings vary across locations?
📍 What is the price range distribution of restaurants?
📍 Are there any correlations between restaurant types and customer ratings?

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Let me know if you need any changes! 🚀