Global Commodity Prices
Monthly global benchmark prices for 80 commodities and price indices - crude oil, natural gas, coal, grains, edible oils, sugar, coffee, cocoa, fertilizers (DAP, potash, phosphate rock), base & precious metals, plus the World Bank price indices - back to 2000. Clean continuous per-commodity series from the World Bank Pink Sheet, normalized from a messy multi-header Excel workbook into tidy Parquet.
- Source
- World Bank
- Licence
- Redistributable open data
- Updates
- Monthly
- Data through
- 2026-06-01
- Quality
- QC clean · 0 failures
- Format
- Apache Parquet + dictionary
Safe to train on
Built only from a named, redistributable official source under a documented open licence - not scraped web data. No copyright grey zone, no personal data. Ships machine-readable Croissant metadata (ML Commons - loads in Hugging Face / Kaggle / Google), an AI training-licence manifest documenting source, licence and provenance for your model's data governance, and a machine-readable data dictionary (drop it into an agent / RAG prompt so the model knows every column) - all inspectable before you buy.
What's included
- 80 global benchmark commodities & indices: energy, food, fertilizer, metals
- Monthly, first-of-month timestamps, back to 2000
- Single GLOBAL zone - world reference prices, not country-specific
- Source: World Bank Commodity Price Data (Pink Sheet) (CC-BY-4.0)
Schema
| Column | Type | Description | Filled | Distinct |
|---|---|---|---|---|
| zone | str | Always GLOBAL | 100.0% | 1 |
| ts | timestamp (UTC) | Month (first-of-month) | 100.0% | 318 |
| commodity | str | Commodity name | 100.0% | 80 |
| price | float | Nominal USD price (native unit) | 100.0% | 8,340 |
| unit | str | Unit | 100.0% | 9 |
| res_min | int | Native resolution (monthly) | 100.0% | 1 |
Sample & preview
Every purchase ships as Apache Parquet with a data dictionary and the full QC report. A free sample (first rows + schema) is downloadable here - confirm fit before you buy. Source: World Bank (redistributable open data; attribution passes through - see our Licence).
Don't trust screenshots - drop the sample into your notebook right now.
import pandas as pd df = pd.read_parquet("global-commodity-prices_sample.parquet") df.info() # typed columns, gap-aware, ready to join⬇ Download free Parquet sample or CSV for Excel
Coverage: 1 zones
GLOBAL
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