🍽️ Zomato Data Analysis

A comprehensive exploratory data analysis (EDA) project on Zomato’s restaurant dataset to uncover key insights about restaurant trends, locations, cuisines, ratings, and pricing. This project demonstrates the use of Python libraries for cleaning, visualizing, and interpreting real-world food industry data.

📊 Key Objectives

• Understand the distribution of restaurants across cities
• Analyze cost trends and rating distributions
• Identify top cuisines and restaurant types
• Discover location-based patterns
• Visualize key metrics with clear and engaging charts

🛠️ Tech Stack

• Language: Python
• Libraries: Pandas, NumPy, Matplotlib, Seaborn, Plotly
• Notebook Environment: Jupyter Notebook / Google Colab
• Dataset: Zomato Restaurant Dataset (CSV)

📁 Project Structure

├── data/
│   └── zomato.csv
├── notebooks/
│   └── Zomato_Analysis.ipynb
├── images/
│   └── visualizations/
├── README.md
└── requirements.txt