This dataset provides comprehensive and up-to-date information on futures related to oil, gas, and other fuels. Futures are financial contracts obligating the buyer to purchase and the seller to sell a specified amount of a particular fuel at a predetermined price and future date.

Use Cases: 1. Trend Analysis: Scrutinize patterns and price fluctuations to anticipate future market directions in the energy sector. 2. Academic Research: Delve into the historical behavior of oil and gas prices and understand the influence of global events on these commodities. 3. Trading Strategies: Develop and test trading tactics based on the dynamics of oil, gas, and other fuel futures. 4. Risk Management: Utilize the dataset for hedging and risk management for corporations involved in the extraction, refining, or trading of fuels.

Dataset Image Source: Photo by Pixabay: https://www.pexels.com/photo/industrial-machine-during-golden-hour-162568/

Column Descriptions: 1. Date: The date when the data was documented. Format: YYYY-MM-DD. 2. Open: Market's opening price for the day. 3. High: Peak price during the trading window. 4. Low: Lowest traded price during the day. 5. Close: Price at which the market closed. 6. Volume: Number of contracts exchanged during the trading period. 7. Ticker: The unique market quotation symbol for the future. 8. Commodity: Specifies the type of fuel the future contract pertains to (e.g., crude oil, natural gas).

Corn rose to 433.53 USd/BU on December 2, 2025, up 0.01% from the previous day. Over the past month, Corn's price has fallen 0.17%, but it is still 2.43% higher than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Corn - values, historical data, forecasts and news - updated on December of 2025.

This paper constructs daily measures of the real interest rate and expected inflation using commodity futures prices and the term structure of Treasury yields. We find that commodity futures markets respond to surprise increases in the federal funds rate target by raising the inflation rate expected over the next three to nine months. There is no evidence that the real interest rate responds to surprises in the federal funds target. The data from the commodity futures markets are highly volatile. We show that one can substantially reduce the noise using limited information estimators such as the median change. Nevertheless, the basket of commodities actually traded daily is quite narrow and we do not know whether our observable rates are closely connected to the unobservable inflation and real rates that affect economy-wide consumption and investment decisions.

This dataset offers a unified collection of futures data across various commodities, bringing together individual datasets to provide a holistic view of the commodities futures market. If your intent is to use data from multiple categories simultaneously, this collection is ideal. However, for those looking to delve deeper into specific commodities, individual datasets are also available.

Individual Categories Datasets: If you wish to explore data specific to individual categories, please refer to the datasets linked below:

• Animal Products Futures: https://www.kaggle.com/datasets/guillemservera/animal-products-futures
• Agricultural Futures: https://www.kaggle.com/datasets/guillemservera/agricultural-futures
• Fuels and Energy Futures: https://www.kaggle.com/datasets/guillemservera/fuels-futures-data
• Precious Metals Futures: https://www.kaggle.com/datasets/guillemservera/precious-metals-data
• Grains and Cereals Futures: https://www.kaggle.com/datasets/guillemservera/grains-and-cereals-futures

File Structure: - all_commodities_futures_collection.csv: A consolidated file containing futures data across various commodities. Each row includes a Category column that indicates the specific commodity type, making filtering and exploration more manageable. - individual_data/: This directory houses separate files for each commodity, allowing for more detailed explorations of specific commodities without the need to filter from the master dataset.

Learn to Extract the Data:

If you're interested in learning how to obtain this type of data on your own, you can refer to an example notebook that showcases the process for Fuels and Energy Futures. Check it out here: Downloading Fuels & Energy Data with yfinance.

Use Cases: 1. Market Analysis: Investigate price trends across different commodities and identify potential interdependencies. 2. Machine Learning: Utilize the diverse dataset for model training, testing and forecasting of futures prices. 3. Educational Purpose: Understand and teach the dynamics of different commodities in the futures market.

Image Credit:

The dataset's cover image is sourced from The Balance Money and is credited to tradeandexportme.

Data Source: All datasets within this collection have been extracted from Yahoo Finance using the yfinance Python module.

Orange Juice fell to 147.99 USd/Lbs on December 2, 2025, down 0.38% from the previous day. Over the past month, Orange Juice's price has fallen 15.22%, and is down 71.10% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Orange Juice - values, historical data, forecasts and news - updated on December of 2025.

Content

File1: Time series of commodity futures from 2000 until present. Includes 23 different commodities. File2: Categories for each commodity.

All prices are quoted in Euros.

The different commodities included in the commodity_prices.csv file are described below:

1. Energy

a/ Natural Gas: quoted in EUR/MMBtu.
b/ Low Sulphur Gas Oil: quoted in EUR/MT.
c/ WTI Crude: quoted in EUR/barrel.
d/ Brent Crude: quoted in EUR/barrel.
e/ ULS Diesel: quoted in EUR/gallon.
f/ Gasoline: quoted in EUR/gallon.

2. Industrial Metals

a/ Copper: quoted in EUR/lb.
b/ Aluminum: quoted in EUR/MT.
c/ Zinc: quoted in EUR/MT.
d/ Nickel: quoted in EUR/MT.

3. Precious Metals

a/ Gold: quoted in EUR/t oz.
b/ Silver: quoted in EUR/t oz.

4. Grains

a/ Corn: quoted in EUR/bushel.
b/ Soybeans: quoted in EUR/bushel.
c/ Wheat: quoted in EUR/bushel.
d/ Soybean Oil: quoted in EUR/lb.
e/ Soybean Meal: quoted in EUR/T.
f/ HRW Wheat: quoted in EUR/bushel.

5. Livestock

a/ Live cattle: quoted in EUR/lb.
b/ Lean Hogs: quoted in EUR/lb.

6. Softs

a/ Sugar: quoted in EUR/lb.
b/ Coffee: quoted in EUR/lb.
c/ Cotton: quoted in EUR/lb.

Inspiration:

Collated for a personal ML project. Plan to update it weekly.

Source:

Web-scraped from multiple sources.

CN: Settlement Price: Shanghai Future Exchange: Fuel Oil: 5th Month data was reported at 2,519.000 RMB/Ton in Nov 2025. This records a decrease from the previous number of 2,732.000 RMB/Ton for Oct 2025. CN: Settlement Price: Shanghai Future Exchange: Fuel Oil: 5th Month data is updated monthly, averaging 3,278.000 RMB/Ton from Aug 2004 (Median) to Nov 2025, with 256 observations. The data reached an all-time high of 5,500.000 RMB/Ton in Feb 2012 and a record low of 1,513.000 RMB/Ton in Apr 2020. CN: Settlement Price: Shanghai Future Exchange: Fuel Oil: 5th Month data remains active status in CEIC and is reported by Shanghai Futures Exchange. The data is categorized under China Premium Database’s Financial Market – Table CN.ZB: Shanghai Futures Exchange: Commodity Futures: Settlement Price.

✍️ Personal Note: While I'm presenting this dataset for analysis and insights, I want to emphasize the importance of ethical sourcing and consumption, especially in commodities like cocoa and coffee which have known ethical concerns in their supply chains.

About This Dataset:

This dataset delivers an extensive and current assortment of futures related to soft commodities. Futures are financial contracts obligating the buyer to purchase, and the seller to sell, a specified amount of a particular commodity at a predetermined price on a set date in the future.

Use Cases: 1. Price Forecasting: Harness machine learning to predict the price dynamics of commodities like coffee and cocoa, aiding stakeholders in their decision-making. 2. Supply Chain Analysis: Evaluate the correlation between futures prices and global events, offering insights into potential supply chain disruptions. 3. Demand Projections: Utilize deep learning techniques to correlate historical consumption patterns with price movements, projecting future demand.

Dataset Image Source: Photo by Tom Fisk from Pexels: https://www.pexels.com/photo/aerial-shot-of-green-milling-tractor-1595108/

Column Descriptions: 1. Date: The date when the data was recorded. Format: YYYY-MM-DD. 2. Open: The opening market price for the day. 3. High: Maximum price achieved during the trading session. 4. Low: Lowest traded price during the session. 5. Close: Market's concluding price. 6. Volume: Count of contracts traded throughout the session. 7. Ticker: Distinct market quotation symbol for the commodity future. 8. Commodity: Indicates the type of soft commodity the futures contract pertains to (e.g., Cocoa, Coffee).

Remember to link to the correct image source for your dataset's image!

The datasets for the Role of Financial Investors on Commodity Futures Risk Premium are weekly datasets for the period from 1995 to 2015 for three commodities in the energy market: crude oil (WTI), heating oil, and natural gas. These datasets contain futures prices for different maturities, open interest positions for each commodity (long and short open interest positions), and S&P 500 composite index. The selected commodities are traded on the New York Mercantile Exchange (NYMEX). The data comes from the Thomson Reuters Datastream and from the Commodity Futures Trading Commission (CFTC).

CRB Index rose to 378.33 Index Points on December 1, 2025, up 0.45% from the previous day. Over the past month, CRB Index's price has fallen 0.80%, but it is still 10.95% higher than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. CRB Commodity Index - values, historical data, forecasts and news - updated on December of 2025.

Yearly citation counts for the publication titled "Temporal Relationships Among Prices on Commodity Futures Markets: Their Allocative and Stabilizing Roles".

The data is in Stata format and includes 2 files. The file named Agric has variables: spot price of Chicago corn and Chicago soybeans, the futures price of Chicago corn and Chicago soybeans and long positions of commodity index traders. The file named Energy contains variables on spot and futures prices of WTI crude oil and Henry Hub natural gas. The data is originally obtained from US commodity futures trading commission

Silver futures contracts to be settled in December 2028 were trading on U.S. markets at around ** U.S. dollars per troy ounce on June 20, 2023. This is above the price of ***** U.S. dollars per troy ounce for contracts to be settled in May 2024, indicating silver traders expect the price of silver to decrease over the next five years. Silver futures are contracts that effectively lock in a price for an amount of silver to be purchased at a time in the future, which can then be traded on markets. Futures markets therefore provide an indicator of how investors think a commodities market will develop in the future.

Crude oil commodity futures are financial contracts that allow investors to speculate on the future price of crude oil. These futures contracts are traded on commodity exchanges, and they offer a standardized method for individuals and institutions to buy or sell crude oil at a predetermined price and date in the future. Learn more about how crude oil futures work and the various participants in the market.

CN: Settlement Price: Shanghai Future Exchange: Zinc: 1st M data was reported at 22,420.000 RMB/Ton in Nov 2025. This records an increase from the previous number of 21,985.000 RMB/Ton for Oct 2025. CN: Settlement Price: Shanghai Future Exchange: Zinc: 1st M data is updated monthly, averaging 16,820.000 RMB/Ton from Mar 2007 (Median) to Nov 2025, with 225 observations. The data reached an all-time high of 32,410.000 RMB/Ton in Apr 2007 and a record low of 9,305.000 RMB/Ton in Dec 2008. CN: Settlement Price: Shanghai Future Exchange: Zinc: 1st M data remains active status in CEIC and is reported by Shanghai Futures Exchange. The data is categorized under China Premium Database’s Financial Market – Table CN.ZB: Shanghai Futures Exchange: Commodity Futures: Settlement Price.

Commodity Price Range 1877-Present

Historical Futures Contract Pricing for Wheat, Corn, and Oats

By [source]

About this dataset

This dataset contains over 140 years of historical commodity price ranges for wheat, corn, and oats futures contracts. It provides a glimpse into the evolution of our modern economic markets and the constant fluctuations in demand and supply that occur at all times. This data is invaluable to academic researchers, corporate strategists, economists, investors and traders alike as it reveals timely insight into various commodities' pricing trends over time. Each record includes the corresponding highest and lowest prices for each particular well-traded commodity on each particular day since 1877— providing an essential view into market dynamics across multiple decades. Use this data to identify recent pricing patterns or make predictions about future prices – no matter how you decide to use it–this may give you further insight into the ever-changing marketplace

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How to use the dataset

This dataset contains historical commodity price ranges for wheat, corn, and oats futures contracts from 1877 to present. It is a great resource for anyone interested in analyzing the trends of these commodities over time. Each row contains one day's data on the low and high prices of each contract.

To use this dataset, start by looking at the columns. There are several columns to choose from depending on which type of commodity you would like to analyze: Range_W_F1 (Lowest Price of Wheat Futures Contract), Range_W_F2 (Highest Price of Wheat Futures Contract), Range_C_F1 (Lowest Price of Corn Futures Contract), Range_C_F2 (Highest Price of Corn Futures Contract) and Range_O_F1 & 2 (Lowest and Highest Prices respectively for Oats Futures Contracts). Once you have selected the relevant columns for your analysis, pick a date range to focus on and filter out the rows outside that range. This will leave only those days within your chosen timeframe in the dataset so you can begin analyzing them more closely.

For an in-depth analysis it can be helpful to add other pieces data such as weather information or other economic indicators alongside these price ranges so you can investigate possible correlations between different factors that affect pricing in these markets over time. No matter how complex an analysis you might want to do with this data, this dataset provides a good starting point with reliable historical records dating all the way back over 140 years ago!

Research Ideas

• Market analysis to identify trends in prices of different commodities over time.
• Predictive modeling to forecast future prices based on past price ranges and market conditions.
• Proactive risk management strategies by tracking changes in commodity prices and anticipating potential changes in raw material costs for manufacturers or businesses that rely on commodities as part of their production processes

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: rangedata_commodities_since1877.csv | Column name | Description | |:---------------|:---------------------------------------------------------------| | Date | Date of the commodity price range. (Date) | | Range_W_F1 | Lowest price of wheat futures contract for the day. (Numeric) | | Range_W_F2 | Highest price of wheat futures contract for the day. (Numeric) | | Range_C_F1 | Lowest price of corn futures contract for the day. (Numeric) | | Range_C_F2 | Highest price of corn futures contract for the day. (Numeric) | | Range_O_F1 | Lowest price of oats futures contract for the day. (Numeric) | | Range_O_F2 | Highest price of oats futures contract for the day. (Numeric) |

Acknowledgements

If you use this dataset in your research, please credit the original authors. If you use this dataset in your research, please credit .

Natural gas rose to 4.94 USD/MMBtu on December 3, 2025, up 2.04% from the previous day. Over the past month, Natural gas's price has risen 13.71%, and is up 62.29% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Natural gas - values, historical data, forecasts and news - updated on December of 2025.

As of June 25, 2024, gold futures contracts to be settled in June 2030 were trading on U.S. markets at around ***** U.S. dollars per troy ounce. This is above the price of ******* U.S. dollars per troy ounce for contracts to be settled in June 2025, indicating that gold traders expect the price of gold to rise over the next five years. Gold futures are contracts that effectively lock in a price for an amount of gold to be purchased at a time in the future, which can then be traded on markets. Futures markets therefore provide an indicator of how investors think a commodities market will develop in the future.

The dataset contains daily price ranges calculated from the daily high and low prices for Chicago Wheat, Corn, and Oats futures contracts, starting in 1877. The data is manually extracted from the ``Annual Reports of the Trade and Commerce of Chicago'' (today, the Chicago Board of Trade, CBOT, which is part of the CME group).

The price range is calculated as Range_t = ln(H_t) - ln(L_t), where H_t and L_t are the highest and lowest price observed on trading day t.

Description of the dataset:

• Date: The trading day, format dd-mm-yyyy
• Range_W_F1: Price range Wheat futures, First expiration (nearby contract)
• Range_W_F2: Price range Wheat futures, Second expiration
• Range_C_F1: Price range Corn futures, First expiration (nearby contract)
• Range_C_F2: Price range Corn futures, Second expiration
• Range_O_F1: Price range Oats futures, First expiration (nearby contract)
• Range_O_F2: Price range Oats futures, Second expiration

Graph and download economic data for Global Price Index of All Commodities (PALLFNFINDEXQ) from Q1 2003 to Q2 2025 about World, commodities, price index, indexes, and price.