Daily market prices of agricultural commodities across India from 2001-2025. Contains 75+ million records covering 374 unique commodities and 1,504 varieties from various mandis (wholesale markets). Commodity Like: Vegetables, Fruits, Grains, Spices, etc.

Cleaned, deduplicated, and sorted by date and commodity for analysis.

Column Schema

Data sourced from the Government of India's Open Data Platform.

License: Government Open Data License - India (GODL-India) https://www.data.gov.in/Godl

GSCI fell to 556.57 Index Points on December 2, 2025, down 0.34% from the previous day. Over the past month, GSCI's price has fallen 0.80%, but it is still 3.06% higher than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. GSCI Commodity Index - values, historical data, forecasts and news - updated on December of 2025.

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.

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.

Graph and download economic data for Index of Spot Market Prices of 22 Commodities for United States (M04195USM350NNBR) from Jul 1946 to Nov 1969 about commodities, price index, indexes, price, and USA.

This dataset provides the current daily prices of various commodities sourced from multiple markets (mandis) across different regions. It includes detailed information on the market names, commodity types, and their respective prices, offering a snapshot of real-time agricultural and other commodity market trends. The data is valuable for farmers, traders, and analysts to monitor price fluctuations, compare regional price variations, and make informed decisions. It offers insights into supply and demand dynamics, and market conditions, and helps in understanding the economic factors affecting commodity pricing. This dataset supports decision-making, price forecasting, and market research.

Graph and download economic data for Index of Spot Market Prices of 28 Commodities for United States (M0495AUSM346NNBR) from Jan 1935 to Oct 1952 about commodities, price index, indexes, price, and USA.

Dataset: • Commodity Price Data. Eg. Commodity1_price.csv, Commodity2_price.csv, Commodity3_price.csv • Distance Matrix Data. Eg. Commodity1_matrix.csv, Commodity2_matrix.csv, Commodity3_matrix.csv

Price dataset description: It is a time-series data of prices of a particular perishable, limited consumption good or commodity (let’s say C) reported in markets of a country. • Date: It’s the date commodity C was reported in the respective market. • Market: Market in which commodity C was reported. • State: State in which the corresponding market is situated. • Variety: Variety of commodity C reported. • Grade: Grade of commodity C reported. • Tonnage (Arrival): Tonnage of a crop that arrives at the market • Prices: MinimumPrice, ModalPrice, and MaximumPrice columns are the corresponding prices of commodity C for the date-state-market-variety-grade combination.

The data has also been captured in form of combinatorial explosion matrix form. It contains market-varieties-grade combination as one cell in the matrix.

Distance matrix description: It is a distance matrix of one state-market combination with every other state-market combination in KM. The files have a distance matrix, whose entries a(i,j) represent distance between two statemarkets statemarket[i] and statemarket[j] in KMs.

Problem description: We have prices available reported for commodity C in different state and markets of the country. Our objective is to forecast the price of a commodity for a given date, state, market, variety, and grade.

Data Properties: 1. Time Series Data 2. Multivariate and multidimensional: Data is multivariate because a lot of factors (features) is responsible for the price of products (labels). 3. Super Sparse Data 4. We believe that there exists a very high degree of correlation between the price of one market and prices in another market. 5. We believe that there may be a high correlation between the prices of different varieties of the same good in the same mandi.

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.

At 3.82 U.S. dollars per gallon in October 2022, regular all formulation retail gasoline prices in the United States were considerably lower than in Hong Kong or the Central African Republic, which reported the highest gasoline prices in the world at the end of October 2022. Norway also ranked high this year. Its high gasoline prices might be one of the reasons why the country is leading the charge towards electric mobility. Gas prices in selected countries worldwide Fuel prices in different countries range from a few cents to almost two U.S. dollars per liter. Gasoline is often regarded as a key driver of a country’s economy, as it is the main fuel used in passenger vehicles and the automotive fleets of small and large businesses. The United States is one of the biggest consumers of gasoline on a per capita basis, with approximately 356 gallons of gasoline per person in 2020. Fuel prices respond to crude oil price changes One of the liquid’s main ingredients is crude oil. The spot prices of publicly traded crudes, such as U.S.-sourced WTI (West Texas Intermediate), UK Brent, and the OPEC basket grades, are highly volatile and have proven prone to inflation as of late, most recently due to the novel coronavirus outbreak in China, blockages in the Suez Canal, and the Russian invasion of Ukraine. Where access to oil is limited, this volatility may spur a shift towards alternative propulsion systems and fuels among a growing number of vehicle drivers. Affordability of fuel Gas prices in Europe are counted among the highest worldwide. At 7.6 U.S. dollars per gallon or more, gasoline is particularly expensive in Iceland, Norway, Denmark, Greece, Finland, and the Netherlands. Car drivers in Mozambique and Madagascar feel the most pain at the pump. Some 145.7 percent of a month's wages are needed to fill up a tank in Mozambique. The low affordability of fuel is due to weak currencies, limited wage growth, and a level of prosperity that is yet to meet other markets' standards. The high price in countries such as the Netherlands and Norway is largely attributable to taxes. Other factors driving gas prices include local demand, processing and distribution costs, and the aforementioned level of crude oil prices.

Learn about live grain commodity prices and how they impact the cost of production for farmers and the price consumers pay for food products. Track these prices on exchanges like CME, ICE, and MGEX to monitor broader trends in the agricultural industry.

Commodity Price Risk Dashboards Market Outlook

According to our latest research, the global commodity price risk dashboards market size reached USD 1.45 billion in 2024, reflecting the growing importance of real-time risk management tools in volatile commodity markets. With a robust compound annual growth rate (CAGR) of 10.6%, the market is projected to expand to USD 3.62 billion by 2033. This impressive growth is primarily driven by the increasing complexity of global supply chains, heightened geopolitical risks, and the escalating demand for data-driven decision-making across industries.

One of the most significant growth factors fueling the commodity price risk dashboards market is the increasing volatility and unpredictability in global commodity prices. Over the past decade, geopolitical tensions, trade disputes, and climate change events have contributed to sharp fluctuations in the prices of essential commodities such as oil, agricultural products, and metals. Enterprises and financial institutions are under mounting pressure to manage exposure to price risks more efficiently. As a result, organizations are rapidly adopting advanced dashboards that offer real-time price monitoring, predictive analytics, and scenario modeling capabilities. These tools empower stakeholders to make informed decisions, optimize procurement strategies, and safeguard profit margins against unpredictable market swings.

Another key driver is the digital transformation sweeping across industries, particularly in sectors with significant exposure to commodity risks such as energy, agriculture, and manufacturing. The integration of artificial intelligence, machine learning, and big data analytics into commodity price risk dashboards has elevated their value proposition. Modern dashboards can now process vast datasets from multiple sources, offering actionable insights and automated alerts. This technological evolution has not only improved the accuracy of risk assessments but also enhanced the speed at which organizations can respond to market movements. The growing emphasis on automation and data-driven strategies is expected to sustain robust demand for commodity price risk dashboards throughout the forecast period.

Furthermore, stringent regulatory requirements and the growing need for transparency in financial reporting have compelled organizations to adopt sophisticated risk management solutions. Regulatory bodies across the globe are mandating more comprehensive reporting and risk disclosure standards, particularly for companies engaged in commodity trading and procurement. Commodity price risk dashboards facilitate compliance by providing auditable records, detailed analytics, and customizable reporting features. This regulatory push, coupled with the increasing adoption of enterprise risk management frameworks, is anticipated to further stimulate market growth, as organizations seek to align their risk management practices with global standards.

From a regional perspective, North America currently leads the commodity price risk dashboards market, accounting for the largest share in 2024. This dominance is attributed to the presence of major commodity trading hubs, advanced technological infrastructure, and a high concentration of multinational corporations. However, Asia Pacific is poised to exhibit the highest growth rate during the forecast period, driven by rapid industrialization, expanding commodity markets, and increasing investments in digital transformation initiatives. Europe also remains a significant market, supported by robust regulatory frameworks and a strong emphasis on sustainability and risk management in commodity-intensive industries.

Component Analysis

The commodity price risk dashboards market is segmented by component into software and services, each playing a pivotal role in addressing the diverse needs of end-users. Software solutions constitute the core of risk management, offering advanced functionalities such as real-time price tracking, analytics,

The global commodity trading services market is experiencing robust growth, driven by increasing globalization, fluctuating commodity prices, and the need for efficient supply chain management. The market size in 2025 is estimated at $2 trillion, exhibiting a Compound Annual Growth Rate (CAGR) of 6% between 2025 and 2033. This growth is fueled by several key factors. Firstly, the rising demand for raw materials across various sectors, including metals, energy, and agriculture, is creating lucrative opportunities for commodity trading firms. Secondly, technological advancements in areas like data analytics and blockchain technology are improving transparency, efficiency, and risk management within commodity trading, further stimulating market expansion. Finally, the increasing complexity of global supply chains necessitates the expertise of specialized commodity traders to navigate market volatility and ensure secure and timely delivery of goods. The market is segmented by commodity type (metals, energy, agricultural, and others) and by the size of the businesses served (large enterprises and SMEs). While large enterprises dominate the market currently, the SME segment shows strong potential for future growth as businesses increasingly rely on external expertise for commodity sourcing. The geographical distribution of the commodity trading services market is diverse, with North America, Europe, and Asia Pacific representing the major regions. However, emerging markets in Asia and Africa are showing significant growth potential due to rapid industrialization and rising consumer demand. Competitive pressures within the industry are high, with numerous large multinational corporations vying for market share. These companies, including Vitol, Glencore, Trafigura, Mercuria, and Cargill, possess extensive global networks, strong financial capabilities, and deep expertise in risk management, allowing them to dominate the market. Nevertheless, smaller, specialized trading firms are also finding success by focusing on niche markets or employing innovative trading strategies. The overall outlook for the commodity trading services market remains optimistic, with continued growth expected over the coming years, albeit with some potential challenges related to geopolitical instability and regulatory changes.

The US_Stock_Data.csv dataset offers a comprehensive view of the US stock market and related financial instruments, spanning from January 2, 2020, to February 2, 2024. This dataset includes 39 columns, covering a broad spectrum of financial data points such as prices and volumes of major stocks, indices, commodities, and cryptocurrencies. The data is presented in a structured CSV file format, making it easily accessible and usable for various financial analyses, market research, and predictive modeling. This dataset is ideal for anyone looking to gain insights into the trends and movements within the US financial markets during this period, including the impact of major global events.

Key Features and Data Structure

The dataset captures daily financial data across multiple assets, providing a well-rounded perspective of market dynamics. Key features include:

• Commodities: Prices and trading volumes for natural gas, crude oil, copper, platinum, silver, and gold.
• Cryptocurrencies: Prices and volumes for Bitcoin and Ethereum, including detailed 5-minute interval data for Bitcoin.
• Stock Market Indices: Data for major indices such as the S&P 500 and Nasdaq 100.
• Individual Stocks: Prices and volumes for major companies including Apple, Tesla, Microsoft, Google, Nvidia, Berkshire Hathaway, Netflix, Amazon, and Meta.

The dataset’s structure is designed for straightforward integration into various analytical tools and platforms. Each column is dedicated to a specific asset's daily price or volume, enabling users to perform a wide range of analyses, from simple trend observations to complex predictive models. The inclusion of intraday data for Bitcoin provides a detailed view of market movements.

Applications and Usability

This dataset is highly versatile and can be utilized for various financial research purposes:

• Market Analysis: Track the performance of key assets, compare volatility, and study correlations between different financial instruments.
• Risk Assessment: Analyze the impact of commodity price movements on related stock prices and evaluate market risks.
• Educational Use: Serve as a resource for teaching market trends, asset correlation, and the effects of global events on financial markets.

The dataset’s daily updates ensure that users have access to the most current data, which is crucial for real-time analysis and decision-making. Whether for academic research, market analysis, or financial modeling, the US_Stock_Data.csv dataset provides a valuable foundation for exploring the complexities of financial markets over the specified period.

Acknowledgements:

This dataset would not be possible without the contributions of Dhaval Patel, who initially curated the US stock market data spanning from 2020 to 2024. Full credit goes to Dhaval Patel for creating and maintaining the dataset. You can find the original dataset here: US Stock Market 2020 to 2024.

Historical commodity (daily) price from 2000-2022 (March). 1. Gold 2. Palladium 3. Nickel 4. Brent Oil 5. Natural Gas 6. Wheat

• cover image credit: https://www.pexels.com/photo/industrial-machine-during-golden-hour-162568/

Wheat fell to 529.25 USd/Bu on December 1, 2025, down 0.33% from the previous day. Over the past month, Wheat's price has fallen 2.62%, and is down 1.53% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Wheat - values, historical data, forecasts and news - updated on December of 2025.

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.

Commodity Price Risk Dashboards Market Outlook

According to our latest research, the Global Commodity Price Risk Dashboards market size was valued at $1.8 billion in 2024 and is projected to reach $4.7 billion by 2033, expanding at a robust CAGR of 11.2% during 2024–2033. The primary factor fueling this market’s growth is the increasing volatility in global commodity prices, which is compelling enterprises across industries to adopt advanced risk management solutions. These dashboards empower organizations to make informed decisions, optimize procurement strategies, and hedge against unpredictable price fluctuations. As businesses contend with increasingly complex supply chains and heightened geopolitical uncertainties, the demand for real-time, data-driven analytics platforms has surged, making commodity price risk dashboards an indispensable tool for modern risk management and strategic planning.

Regional Outlook

North America currently dominates the Commodity Price Risk Dashboards market, holding the largest share, which accounted for approximately 38% of the global market value in 2024. This regional leadership is attributed to the mature technological landscape, widespread adoption of advanced analytics, and a high concentration of multinational corporations with sophisticated risk management needs. The United States, in particular, is home to several leading dashboard solution providers and benefits from robust regulatory frameworks that encourage transparency and proactive risk mitigation. Additionally, the region’s established commodity trading infrastructure, especially in sectors like energy, agriculture, and financial services, has created a fertile ground for the integration of real-time risk dashboards. These factors, combined with ongoing investments in digital transformation and enterprise analytics, have solidified North America’s position at the forefront of the market.

The Asia Pacific region is emerging as the fastest-growing market for commodity price risk dashboards, with a projected CAGR of 14.7% between 2024 and 2033. This accelerated growth is driven by rapid industrialization, increasing cross-border commodity trade, and a rising awareness of risk management best practices among enterprises in China, India, Japan, and Southeast Asia. Governments in the region are also implementing policies to enhance transparency and efficiency in commodity markets, further spurring demand for advanced dashboard solutions. The significant investments being made in cloud infrastructure and digitalization initiatives are enabling even small and medium-sized enterprises (SMEs) to access sophisticated risk analytics tools. As a result, Asia Pacific is expected to contribute substantially to the global market’s expansion over the coming decade.

Emerging economies in Latin America, the Middle East, and Africa are gradually adopting commodity price risk dashboards, albeit at a slower pace due to challenges such as limited digital infrastructure, lower technology penetration, and regulatory uncertainties. However, these regions represent untapped potential, particularly as local industries in agriculture, oil and gas, and mining begin to recognize the value of real-time risk management. Policy reforms aimed at market liberalization and increased foreign investment are encouraging adoption, but localized demand remains fragmented. The need for customized solutions that address unique regional requirements, language preferences, and compliance standards will be pivotal in unlocking growth in these emerging markets over the forecast period.

Report Scope

Indices in terms of dollars or sdrs, indices of market prices for non-fuel commodities and petroleum, actual market prices for non-fuel commodities and petroleum, and average weekly prices for non-fuel commodities and petroleum.

Learn about the various factors that influence grain commodity prices, including supply and demand, weather patterns, transportation costs, and government policies. Gain insight into how traders and analysts make predictions about price movements and why understanding these factors is crucial for farmers, traders, and consumers.