There are 2 repositories under fao topic.
The python module can be used to scrape data and process data from different sources. The python module can output data as either as a dataframe in the country year format or it will output data in excel files This module has primarily been created for processing data for the International Futures (IFs) Project however, it can be used to process data in general. The module can be used to process data from the following sources, 1) World Bank World Development Indicators (WDI) 2) UNESCO Education indicators(UIS) 3) FAO Food Balance Sheets (FAO) 4) IMF Global Finance Statistics (IMF GFS) 5) Health data from the Institute for Health and Metric Evaluation (IHME) 6) Water data from FAO AQUASTAT 7) Energy data from EIA Currently this module can be run as is on Windows. For usage on Macs, the user may have to make changes to the code lines which specify paths.
Code behind the Food Energy Flows Exploratorium + Project Website
Form.io API Server and Form Builder Client Docker Image
Search and download FAOSTAT bulk download files
AquaCropPlotter is an R Shiny app for processing and visualizing FAO AquaCrop model output files.
Data Analysis on Iran FAO datasets
Evapotranspiration for the reference crop in Uzbekistan. Based on UN-FAO's Irrigation and Drainage Paper 56 and Penman-Monteith Equation.
LinkML rendering of FAO domestic-animal-diversity schema EXPERIMENTAL
This repo is a demo to calculate reference ET at hourly time step based on FAO Penman_Monteith Equation
This model is design by FAO and its use for calculating the amount of water that is lost due to evaporation or absorbed by the plant due to transpiration during the cultivation cycle.
This project evaluates trends in food production and consumption over the years, and uses data to tell a story of how the world food shortage problem can be solved.
Extract fish details from food product descriptions
R-Shiny dashboard offering visualisations of species occurrence data extracted from multiple open-access biodiversity information systems ...
A RDF Harvester written in Java
Portfolio Project for CSU MIS500
Jupyter Notebook dedicated to studying Agriculture and AMI analytics
The OpenFisheries.org project seeks to advance the practice of data science in fisheries. The project does this by consolidating global fisheries datasets through an open web platform and viewing this data through a lens of modern analytics.
FAO is dedicated to collecting, analysing, interpreting and disseminating food and agriculture statistics that are relevant for decision-making.
Sample code that uses data from FAO stats to build a RAG over LLM