This is a project created as a part of a 3-month Data Analytics program at neuefische. This repository contains the culmination of three months of learning and hands-on experience in a data analytics bootcamp. The project focuses on applying data analysis and visualisation skills to solve real-world problems, utilizing various tools and techniques learned during the program.
The data used in this project is available on the website of the Food and Agriculture Organization (FAO).
Objective: This project investigates the relationship between global food production and its corresponding greenhouse gas emissions, with a primary goal of identifying and highlighting high-emission foods. We use the data from the FAO, examining worldwide trends as well as the data specific for Germany.
Tools and Technologies: Python, SQL, Jupyter Notebooks
LICENSE: Project license information.README.md: Project overview, setup instructions, and documentation.data/: Raw datasets downloaded from the Food and Agriculture Organization (FAO) database.images/: Images used in the the final project presentation.2-sql-scripts/: SQL scripts for data wrangling._functions_sql.py: Functions for writing and retrieving Pandas dataframes from a PostgreSQL database._functions_data_files.py: Functions for downloading data from the FAO database.
Note that the notebooks and SQL scripts should preferably be run in a specific order, from 0 to 3.