faostat

Food and Agriculture Biomass Input-Output Tables

Food and Agriculture Biomass Input-Output Tables

AI skills for analyzing UN FAOSTAT food & agriculture data — country profiles, trade analysis, climate assessments, commodity briefings. Plugin for Claude Code & Codex.

Crop yield prediction using ML on real-world weather, pesticide, and agricultural data.

Global food & agriculture statistics from the UN FAOSTAT bulk-download corpus, served from a local SQLite mirror with a DataCanvas SQL surface, via MCP. STDIO or Streamable HTTP.

Crop production and arable-land pipeline in Streamlit

Sistema de predicción del rendimiento económico de reventa de cosechas — Proyecto Integrador de Analítica de Negocios 7A (ETL FAOSTAT + Banco Mundial, esquema estrella, Random Forest, dashboard)

This repository contains the work done as a part of a Data Analytics Program at neuefische.

FAOSTAT food-systems analytics: Python ETL to SQLite, 35 SQL analyses with Plotly, predictive models and an interactive dashboard

FoodLife MRIO Pipeline - Analysing the biodiversity impacts of food consumption

FAOSTAT Beta MCP (SDMX) - Internal Only

From a messy edge table to interactive network charts: clean, build a NetworkX graph, and plot with Plotly using one set of arguments. FAOSTAT trade data included.

This script is designed to be flexible and adaptable to any FAOSTAT data. Making it a useful tool for exploring and visualizing FAOSTAT datasets.

Land-Use Efficiency and Crop Yield Trends in the European Union: a data-driven assessment using FAOSTAT data (1995 - 2024)

41 recipes for pulling public statistics — with the gotchas written down

🌶️ Interactive Streamlit data story on where the world's spices are grown vs. where they're eaten — 28 years of UN FAOSTAT data, 9 spice categories, 198 countries.

Stata and R scripts to harmonize countries' name among different database sources. In collaboration with Federica Cappelli, Ph.D.

R script drawing streamgraphs (stacked-area charts around a central baseline) of category composition over time with the streamgraph package, using spline and step interpolation. Example data: FAOSTAT agricultural production and yield time series.

Excel analysis of Nigeria's production of five selected crops from 2015–2024 using FAOSTAT data.

Work-in-progress FAOSTAT agrifood MEL data foundation with reproducible Python preparation and tests.