Tools: Python, Pandas, NumPy, Matplotlib, Seaborn, Jupyter Notebook
Dataset: Zomato Bangalore Restaurant Dataset (7,105 records, 12 features)

To perform end-to-end Exploratory Data Analysis on the Zomato Bangalore dataset and extract actionable insights on restaurant ratings, cuisine trends, pricing patterns, and location-based distribution.

zomato-eda/
│
├── Zomato_Restaurants_Dataset.csv   # Dataset
├── zomato_eda.ipynb                 # Main EDA notebook
├── README.md                        # Project documentation

• Loaded dataset with 7,105 rows and 12 columns
• Inspected data types, shape, and column descriptions

• Renamed columns for easier access
• Dropped unnamed/irrelevant columns
• Cleaned location column (extracted primary area from combined strings)
• Extracted primary cuisine and primary restaurant type from combined values
• Removed duplicate rows
• Detected outliers in votes column using IQR method

1. Ratings - Most restaurants (78.7%) are rated between 3.0 and 4.2. The average rating is 3.48, suggesting moderate satisfaction overall across Bangalore.

2. Online Ordering - Restaurants that accept online orders have a slightly higher average rating (3.55) compared to those that don't (3.41). About 52.5% of restaurants offer online ordering.

3. Location - Byresandra, Bannerghatta Road and Brookefield have the highest number of restaurants, indicating strong dining demand in these areas.

4. Cuisines - North Indian cuisine is by far the most popular (1,943 restaurants), followed by South Indian and Chinese. This reflects Bangalore's diverse food culture.

5. Pricing - Average cost for two people is ₹536, with median at ₹400. About 68% of restaurants fall in the ₹200–₹600 range, showing budget-friendly dining dominates.

6. Votes vs Rating - There is a moderate positive correlation (0.32) between votes and rating, and also between cost and rating (0.33). Higher-priced restaurants tend to get better ratings and more engagement.

# Clone the repo
git clone https://github.com/kavishrathod/zomato-eda.git
cd zomato-eda

# Install dependencies
pip install pandas numpy matplotlib seaborn

# Open notebook
jupyter notebook zomato_eda.ipynb

Kavish Rathod
📧 [email protected]
🔗 LinkedIn | GitHub