https://github.com/devrihan/eda-zomato
https://github.com/devrihan/eda-zomato
Last synced: about 1 year ago
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- Host: GitHub
- URL: https://github.com/devrihan/eda-zomato
- Owner: devrihan
- Created: 2024-08-18T19:50:30.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2024-08-18T19:55:09.000Z (almost 2 years ago)
- Last Synced: 2025-02-03T04:28:57.513Z (over 1 year ago)
- Language: Jupyter Notebook
- Size: 587 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Zomato Bengaluru Restaurant Data Analysis
This repository contains an Exploratory Data Analysis (EDA) on a dataset of restaurants in Bengaluru, the IT capital of India. With over 12,000 restaurants serving a wide variety of cuisines from around the world, Bengaluru presents a unique opportunity to analyze factors that affect restaurant success, food preferences in different localities, and the challenges faced by new establishments.
## Project Overview
The primary goal of this analysis is to gain insights into the restaurant industry in Bengaluru, focusing on:
- **Aggregate Ratings**: Understanding the factors that influence the ratings of each restaurant.
- **Types of Establishments**: Exploring the distribution of different types of restaurants across the city.
- **Demographic Influence**: Analyzing the impact of locality demographics on food preferences, such as the popularity of vegetarian food in certain areas.
### Motivation
Bengaluru's restaurant industry is booming, with new establishments opening daily to meet the growing demand. However, despite the increasing demand, new restaurants face stiff competition from established players. Many of these new entrants offer similar cuisines, making it challenging to stand out.
By studying various factors like location, cuisine type, and customer preferences, this analysis aims to provide valuable insights for restaurant owners, marketers, and entrepreneurs looking to succeed in this competitive environment.
## Data Source
The dataset used for this analysis was sourced from kaggle. It includes information on over 56,000 restaurants in Bengaluru, with details such as:
- Restaurant name
- Location
- Cuisines served
- Aggregate rating
- Price range
- Type of establishment (e.g., casual dining, café, fine dining)
- Customer reviews
## Analysis Questions
1. **What factors affect the aggregate rating of a restaurant?**
2. **Which types of restaurants are most common in different parts of Bengaluru?**
3. **How does the demographic composition of a locality influence the popularity of certain types of food (e.g., vegetarian vs. non-vegetarian)?**
4. **What are the key challenges faced by new restaurants trying to compete with established ones?**
## Tools and Libraries
The following tools and libraries were used for the analysis:
- **Python**: The primary programming language used.
- **Pandas**: For data manipulation and analysis.
- **Matplotlib & Seaborn**: For data visualization.
- **Jupyter Notebook**: For interactive analysis and visualization.
## Conclusion
This analysis provides a comprehensive view of the restaurant landscape in Bengaluru. By understanding the factors that contribute to a restaurant's success and the preferences of different localities, restaurant owners and entrepreneurs can make more informed decisions about where to open new establishments and how to tailor their offerings to meet the needs of their target audience.
## How to Run the Analysis
1. Clone the repository:
```bash
git clone https://github.com/yourusername/bengaluru-restaurant-eda.git
```
2. Install the required libraries:
```bash
pip install -r requirements.txt
```
3. Open the Jupyter Notebook and run the cells to see the analysis:
```bash
jupyter notebook bengaluru_restaurant_eda.ipynb
```
## Contributing
Contributions are welcome! If you have any suggestions or improvements, please feel free to open an issue or submit a pull request.