https://github.com/prithvikings/zomato_data_anaysis
This analysis provides insights into customer preferences and restaurant performance on Zomato. The visualizations and findings can help Zomato make informed decisions to improve customer experience and tailor their offerings.
https://github.com/prithvikings/zomato_data_anaysis
matplotlib numpy pandas python seaborn
Last synced: 2 months ago
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This analysis provides insights into customer preferences and restaurant performance on Zomato. The visualizations and findings can help Zomato make informed decisions to improve customer experience and tailor their offerings.
- Host: GitHub
- URL: https://github.com/prithvikings/zomato_data_anaysis
- Owner: prithvikings
- Created: 2024-08-02T09:44:53.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2024-12-20T18:13:31.000Z (over 1 year ago)
- Last Synced: 2025-02-06T02:14:02.546Z (over 1 year ago)
- Topics: matplotlib, numpy, pandas, python, seaborn
- Language: Jupyter Notebook
- Homepage:
- Size: 105 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: Readme.md
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README
# Zomato Data Analysis Project
## Overview
This project involves analyzing Zomato data to understand various aspects of restaurant performance and customer preferences. The analysis aims to answer key business questions about restaurant types, customer ratings, and order behaviors using Python and its libraries.
## Technologies Used
- **Python**: Programming language used for data analysis.
- **Pandas**: Library for data manipulation and analysis.
- **NumPy**: Library for numerical operations.
- **Matplotlib.pyplot**: Library for creating static, animated, and interactive visualizations.
- **Seaborn**: Library for statistical data visualization.
## Objectives
1. **Understand the Business Problems**:
1. What type of restaurant do the majority of customers order from?
2. How many votes has each type of restaurant received from customers?
3. What are the ratings that the majority of restaurants have received?
4. Zomato has observed that most couples order most of their food online. What is their average spending on each order?
5. Which mode (online or offline) has received the maximum rating?
6. Which type of restaurant received more offline orders, so Zomato can provide those customers with some good offers?
7.
## Conclusion
This analysis provides insights into customer preferences and restaurant performance on Zomato. The visualizations and findings can help Zomato make informed decisions to improve customer experience and tailor their offerings.
## Setup and Installation
1. Clone the repository:
```bash
git clone https://github.com/yourusername/zomato-data-analysis.git
```
2. Navigate to the project directory:
```bash
cd zomato-data-analysis
```
3. Install the required libraries::
```bash
pip install pandas numpy matplotlib seaborn
```
4. Place your dataset (Zomato_data.csv) in the project directory.
5. Run the analysis script: