This repository contains two Jupyter notebooks that demonstrate the process of importing, updating, and analyzing data from the UK Food Standards Agency. The data includes food hygiene ratings for various establishments in the United Kingdom. The analysis is conducted using MongoDB and Python.
The project is divided into two main parts:
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NoSQL_setup_starter.ipynb: This notebook sets up the database, imports the data, and makes updates to the database according to the requirements of a food magazine.
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NoSQL_analysis_starter.ipynb: This notebook performs exploratory analysis on the data using various queries, aggregations, and data manipulation techniques to answer specific questions related to the hygiene ratings of establishments.
The data for this project is provided in the Resources folder, which contains the establishments.json file.
This project demonstrates the use of MongoDB as a NoSQL database and the power of PyMongo for connecting, querying, and updating data within the database.
To run this project on your local machine, follow these steps:
- Clone this repository to your local machine.
- Make sure you have MongoDB installed and running.
- Install the necessary Python packages (pandas, pymongo, etc.) using the requirements.txt file provided or using your preferred package manager.
- Open the Jupyter notebooks (NoSQL_setup_starter.ipynb and NoSQL_analysis_starter.ipynb) and run the cells in order to perform the analysis.
This project is licensed under the MIT License. See the LICENSE file for more information.