This GitHub repository contains the code and data for a data analysis project aimed at understanding the demand for different restaurants in New York City to assist a food aggregator company in improving its business operations. By analyzing the data, the company can make informed decisions and optimize its services to meet customer demands effectively.

The main objective of this project is to analyze restaurant demand patterns in New York City and provide valuable insights to the food aggregator company. The insights obtained from the analysis will help the company in enhancing its services, optimizing delivery routes, and making strategic decisions to improve overall business performance.

The data used in this analysis is sourced from various reliable and publicly available datasets, including restaurant reviews, location data, cuisine types, customer ratings, and order histories. The datasets are preprocessed and anonymized to ensure the privacy and confidentiality of the restaurants and customers involved.

The analysis is conducted using the following technologies:

• Python: Utilizing the power of Python programming language for data manipulation, visualization, and statistical analysis.
• Pandas: Employing the Pandas library for data handling and preprocessing.
• Matplotlib and Seaborn: Utilizing these visualization libraries to create insightful graphs and plots.
• Jupyter Notebook: Providing an interactive environment for code execution and result presentation.

The repository is organized as follows:

• data/: Contains the anonymized datasets used in the analysis.
• notebooks/: Contains Jupyter Notebooks detailing the step-by-step analysis process.
• scripts/: Includes any custom Python scripts used during data preprocessing or analysis.
• results/: Contains the final analysis outputs, including visualizations and insights.
• README.md: The file you are currently reading, providing an overview of the project.

This project is licensed under the MIT License, allowing users to modify and distribute the codebase freely.