Johnson-Yeboah/API-Automation-Ghana-Food-Security

The use of API through Python, SQL, and GitHub actions to automate data analytics. # EXPLORING GHANA'S FOOD SECURITY IN CORRELATION TO QUALITATIVE DATA ## Introduction This project aims to quantitatively analyze the production of crops in Ghana over the years in order to corrabate it with my master's thesis topic on the 2024 Northern Ghana Dry Spell in Ghana. In 2024, Ghana suffered it's second most intense dry spell in history since 1983 and I took a qualitative study as part of my master thesis to know the decision making and aid distribution of this dry spell, in efforts to mitigate these dry spell. Therefore, this project is a quantitative study, using data from the FAOSAT website to try and understand the crop production to corrabate the claims of dry spell in 2024. This will be an end-to-end project, where I source the data from `FAOSAT` using API and clean the dataset with `Python`, load the cleaned dataset in `PostgreSQL`, and use `Apache Airflow` for automation and visualizations.