/cl_data_analytics_restaurants

This repository houses a Data Analytics project focused on fast-food restaurant branch expansion in the US market. The goal is to analyze data, derive insights, and provide recommendations for strategic branch expansion.

Primary LanguageJupyter Notebook

Fast-Food Restaurants Branch Expansion Data Analytics Project 🍔📊

Welcome to the Fast-Food Restaurants Branch Expansion Data Analytics Project repository! Here, you'll find the data, Jupyter notebook with the code, final report in HTML format, and a PDF presentation outlining the solution. 📈✨

Table of Contents 📋

Introduction 💡

This repository houses a Data Analytics project focused on fast-food restaurant branch expansion in the US market. The goal is to analyze data, derive insights, and provide recommendations for strategic branch expansion.

Project Overview 🌐

The project comprises the following components:

  1. Data: Raw and processed data related to the fast-food industry and market trends.
  2. Jupyter Notebook: Python code for data cleaning, exploration, and analysis.
  3. Final Report (HTML): A comprehensive report detailing the findings, insights, and recommendations.
  4. Presentation (PDF): A concise presentation summarizing the key aspects of the solution.

Project Components 📊

1. Data

  • data/: Raw and processed datasets.

2. Jupyter Notebook

  • code/Project2.ipynb: Python code for data analysis and exploration.

3. Excel File

  • CL-DA-Project2-1.xlsx: Excel file with data preprocessing and calculations

4. Final Report (HTML)

  • CL-DA-Project2-1.html: A detailed report outlining the analysis, insights, and recommendations.

5. Presentation (PDF)

  • CL-DA-Project2-1.pdf: A concise presentation summarizing the key aspects of the solution.

Getting Started 🚀

  1. Clone the repository: git clone https://github.com/ivanovsdesign/cl_data_analytics_restaurants
  2. Explore the data, Jupyter notebook, final report, and presentation.
cd cl_data_analytics_restaurants

Analysis and Results 📈

The Jupyter notebook (notebook.ipynb) contains the step-by-step analysis, visualizations, and insights derived from the data. For a detailed overview, refer to the Final Report and Presentation (PDF).

Contributing 🤝

Contributions are welcome! If you have suggestions, improvements, or additional analyses, feel free to open issues or submit pull requests.

License 📝

No license provided

Happy analyzing! 🍟📊