food-waste-analysis

about

In this analysis, we delve into the multifaceted issue of food waste worldwide. Our focus pits food waste against three dimensions: food insecurity, economic wealth, and population density. In the interest of time, the scope of this analysis will be limited to the year 2020, providing us a snapshot of the complex interplay between these concepts that is likely close to what it would look like on December 1, 2023.

datasets used

• Food waste by country (.CSV from Kaggle): https://www.kaggle.com/datasets/joebeachcapital/food-waste/data

• GDP per capita (wealth) by country (.CSV from Data.WorldBank.Org): https://data.worldbank.org/indicator/NY.GDP.PCAP.CD

• Population density by country (.CSV from Data.WorldBank.Org): https://data.worldbank.org/indicator/EN.POP.DNST

• Prevalence of moderate-to-severe food insecurity in the population by country (.CSV from Data.WorldBank.Org): https://data.worldbank.org/indicator/SN.ITK.MSFI.ZS?view=chart

before you begin

Check to see if your machine has met the following requirements:

• Installed Python. This project was developed using Python 3.11.6. If you don't have Python installed or if you need to upgrade your current version, you can download it from the official Python website.
• Installed Git, which is necessary to clone the repository. If you don't have Git installed, you can download it from the official Git website.

Follow these steps to run the project on your local machine:

1. cloning the repository

   Navigate to the directory where you want the cloned repository to be placed by using the cd command in your terminal followed by the path of the directory.

   Then you can clone this repository by running the following command in your terminal:

   git clone https://github.com/wturner94/food-waste-analysis.git
   

2. navigating to the cloned directory

   Change your current directory to the cloned repository's directory food-waste-analysis.

3. establishing a virtual environment

   It's recommended to create a virtual environment to keep the project's dependencies isolated from your system's Python environment. You can create a virtual environment using the following command:

   On Windows:

   python -m venv venv
   

   On macOS and Linux:

   python3 -m venv venv
   

   This will create a new virtual environment named venv in your current directory.

4. activating the virtual environment

   Activate the virtual environment using the following command:

   On Windows:

   .\venv\Scripts\activate
   

   On macOS and Linux:

   source venv/bin/activate
   

   Your prompt should change to indicate that you are now operating within a Python virtual environment.

5. installing the required packages

   Install the required packages by running the following command:

   pip install -r requirements.txt
   

   You're now ready to run the project!

6. running the food-waste-analysis.ipynb file:

   • If you have Jupyter Notebook installed, enter jupyter notebook and open the .ipynb file.
   • If you are using Visual Studio Code, open the .ipynb file and select "Install" when asked "Do you want to install the recommended 'Python' extension from Microsoft for the Python Language?"
   • Attempt to "Run" the first code block by selecting the Run/Play button at the top left of the code block. This will prompt you to "Install/Enable the suggested extensions "Python" + "Jupyter"
   • Continue to run the cells using the Run/Play button that appears at the top left of each cell.

To deactivate the virtual environment when you're done, simply type deactivate in your terminal.