Global Outlook Report 2026: projections dashboard

An interactive dashboard of IFPRI IMPACT model projections, 2025–2050, for the reference scenario (REF). It covers yields and area, production and demand, prices and trade, and food security. Users choose regions or countries, one or more commodities and a year, and see line charts, bar charts, area charts and maps. Line charts can also be shown as an index (2025 = 1) to compare growth rates. Every chart has a data table and a CSV download.

It is a static website (HTML, CSS and JavaScript), published with GitHub Pages from the docs/ folder.

Repository layout

Path	Contents
*_REF.csv	Cleaned IMPACT extracts, REF scenario: the dashboard's source data
metadata files/	IMPACT region and commodity nomenclature (current standard)
scripts/build_data.py	Converts the CSVs and metadata into docs/data/*.json
docs/	The website: index.html, css/, js/config.js (labels, units, colours), js/app.js, data/

Updating the data

After changing any *_REF.csv or metadata file, rebuild the browser data and commit the result:

python scripts/build_data.py

This requires Python 3 with pandas and openpyxl. The script stops with an error if the data contain a region or commodity that is missing from the metadata.

Previewing locally

Browsers block data loading from file://, so serve the folder instead:

python -m http.server 8000 -d docs

Then open http://localhost:8000.

Publishing on GitHub Pages

In the repository, go to Settings → Pages. Under "Build and deployment", choose "Deploy from a branch", then select the branch (e.g. main) and the /docs folder. The site appears at https://<user-or-org>.github.io/<repository>/.

Notes

• Charts use Plotly.js 2.35.2 (MIT licence), loaded from the jsDelivr CDN.

• Values are shown as in the source CSVs, except for a few changes made when the dashboard data is built (scripts/build_data.py):

  • negative risk-of-hunger values are shown as 0;
  • Burundi and Eritrea (risk of hunger), China's maize net trade, and all of Greenland's data are removed and show as "no data";
  • fodder and grass are removed.

  Regional and global totals are IMPACT's own and are never recomputed.

• Region code NA is North America, not a missing value.

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Dashboard developed by Nicola Cenacchi and Nilam Prasai using Claude (Anthropic), an AI model. Accuracy reviewed by developers, but errors may still exist. 2026-11-10