Coffee fell to 408.66 USd/Lbs on December 2, 2025, down 0.95% from the previous day. Over the past month, Coffee's price has risen 0.50%, and is up 38.54% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Coffee - values, historical data, forecasts and news - updated on December of 2025.

Coffee growers raise two species of coffee bean: Arabica and robusta. The former is more expensive, selling for 2.93 U.S. dollars per kilogram in 2018 and projected to increase in price to 6.9 U.S. dollars in 2027. Robusta, named because it can grow at a wider range of altitudes and temperatures, sold for 1.87 U.S. dollars in 2018, projected to sell at 4.6 U.S. dollars per kilogram in 2027. Coffee production Coffee originally comes from Ethiopia, where a significant portion of coffee production continues to take place. The more popular bean, Arabica, takes its name from the Arabian Empire, when coffee consumption spread throughout the Middle East. After overcoming its ban by the Catholic Church, who saw coffee as an intoxicant from the Muslim world, coffee sales per capita are highest in European countries. Major players Starbucks has shaped the modern coffee culture, capitalizing on the Seattle coffee shop scene. This opened gourmet coffee to a wider market, shifting the global demand from cheaper robusta to better-tasting Arabica varieties. This shift has influenced the world coffee market, prompting companies such as McDonalds to open McCafé stores to cater to the evolving tastes of global consumers.

View monthly updates and historical trends for Coffee Arabica Price. Source: World Bank. Track economic data with YCharts analytics.

Global prices for coffee have skyrocketed to a seven-year high, driven by fears of a significant reduction in production in Brazil due to freezes and the depletion of global stocks. Further growth in prices for the product will be stimulated by the reduction in production in other leading supplying countries such as Honduras and Indonesia, coupled with increased freight costs. A decrease in coffee production will lead to a fall in global exports by -4% y-o-y, which could lead to local imbalances in supply and demand and drive up consumer prices in key European and American markets.

This table contains 23 series, with data for years 1994 - 1995 (not all combinations necessarily have data for all years), and is no longer being released. This table contains data described by the following dimensions (Not all combinations are available): Geography (1 item: Canada); Activity (2 items: Production; Stocks); Standard Classification of Goods (SCG) (12 items: Whole bean (whether or not decaffeinated);Caffeinated coffee in packages 300 grams and under; Caffeinated coffee in packages more than 300 grams but less than 454 grams; Caffeinated coffee in packages over 454 grams; ...).

Data Collecting

Historical Data on the Global Coffee Trade https://www.ico.org/new_historical.asp

International Coffee Organization(ICO) provides data on the coffee industry over 30 years between 1990-2019. I select 9 .xlsx files: production, domestic consumption, gross opening stocks, exports, imports, re-exports, price to growers, retail price, and consumption recorded for different countries and years. 5 of them --production, domestic consumption, gross opening stocks, exports, and price to growers-- includes data from the exporting countries and 4 of them have data from importing countries.

Data Cleaning

Each excel file should be a feature in the data frame in pandas. Our goal is to combine the tables into one, using 'pd.melt'and 'pd.merge'. At the same time, we deal with missing values and redundant values. Also, messy string data is cleaned.

Structure: assign a proper data type Quality: drop empty rows, unified format, remove unnessarily aggregated rows

Refer to https://github.com/mathjkim/coffee-crew

This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.

View monthly updates and historical trends for Coffee Robusta Price. Source: World Bank. Track economic data with YCharts analytics.

Overview This comprehensive dataset offers an in-depth look at the financial performance of five major entities within the coffee industry from 2014 to 2024 (up to May 8, 2024). Included are stock prices of Keurig Dr Pepper, Starbucks, J.M. Smucker, Luckin Coffee, and Nestlé, paired with the corresponding periodical commodity prices for coffee. This data facilitates robust analyses including time series analysis, correlation studies, volatility analysis, and Vector Autoregression (VAR) analysis.

Key Companies Profiled Keurig Dr Pepper (KDP) and J.M. Smucker: These companies are leaders in the North American coffee market, known for their extensive portfolios of coffee products. Their data can provide insights into market strategies and financial health in response to fluctuating coffee prices. Starbucks: As a global leader in coffee retail, Starbucks' data reflects trends in consumer coffee consumption worldwide, offering a unique view of the retail sector's dynamics. Luckin Coffee: Representing a rapidly growing market, Luckin Coffee's data highlights the expansion and consumer trends within the Chinese coffee market. Nestlé: This global giant provides a broader perspective on how multinational food and beverage companies adapt to global commodity price changes, with a particular focus on coffee.

Applications of the Dataset This dataset is ideal for researchers, economists, and data scientists interested in: Market Trend Analysis: Understand how global events and market forces influence coffee prices and, in turn, affect company stocks. Consumer Behaviour Studies: Analyse consumption patterns across different regions, especially with a focus on the burgeoning Asian markets. Risk Management and Forecasting: Develop models to predict future trends and prepare risk management strategies for companies within the food and beverage sector. Sustainability Studies: Explore how price volatility relates to environmental factors and sustainability initiatives.

This table contains 11 series, with data for years 1946 - 1994 (not all combinations necessarily have data for all years), and is no longer being released. This table contains data described by the following dimensions (Not all combinations are available): Geography (1 item: Canada); Production and stocks (11 items: Cereals ready to serve; Macaroni, et cetera, dry; Prepared cake mixes; Mixes, all other flour based; ...).

Brazil Agricultural Stock: Public Sector: Coffee data was reported at 0.000 Ton in May 2019. This stayed constant from the previous number of 0.000 Ton for Apr 2019. Brazil Agricultural Stock: Public Sector: Coffee data is updated monthly, averaging 10,930.000 Ton from Oct 2003 (Median) to May 2019, with 188 observations. The data reached an all-time high of 98,611.000 Ton in Jul 2010 and a record low of 0.000 Ton in May 2019. Brazil Agricultural Stock: Public Sector: Coffee data remains active status in CEIC and is reported by National Supply Company. The data is categorized under Brazil Premium Database’s Agriculture Sector – Table BR.RID001: Agricultural Stocks.

The report covers Brazil RTD Coffee Brands and is segmented by Packaging Type (Bottles, Cans, and Other Packaging Types), Product Type (Cold Brew Coffee and Other RTD Coffee), Distribution Channel (Supermarket/Hypermarkets, Specialist Stores, Online Retail, and Other Distribution Channels).

View monthly updates and historical trends for New York Arabica Coffee Price. Source: International Monetary Fund. Track economic data with YCharts analyt…

This statistic shows the consequences of out of stock coffee products among U.S. consumers as of February 2017. During the survey, a majority of ** percent said that they would buy the product from a different brand.

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

JVA Coffee Holding Co. Inc. Common Stock

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

Cafe Del Bello Coffee Trade Joint Stock Company Export Import Data. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.

The Coffee Market Report is Segmented by Product Type (Whole-Bean, Ground Coffee, and More), Distribution Channel (On-Trade and Off-Trade), Coffee Species (Arabica, Robusta and More), Origin (Single Origin/Specialty and Mixed), and Geography (North America, Europe, Asia-Pacific, South America, and Middle East and Africa). The Market Forecasts are Provided in Terms of Value (USD) and Volume (Tons).

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Starbucks Corporation, together with its subsidiaries, operates as a roaster, marketer, and retailer of coffee worldwide.

The dataset includes the daily Starbucks Corporation stock price.

Newell Brands stock price, live market quote, shares value, historical data, intraday chart, earnings per share and news.

The Italian Coffee Market Report is Segmented by Product Type (Whole Bean, Ground Coffee, Instant Coffee, and More), Flavor (Plain and Flavored), Category (Conventional and Specialty), Bean Type (Arabica, Robusta, and Others), and Distribution Channel (On-Trade and Off-Trade). The Market Forecasts are Provided in Terms of Value (USD) and Volume (Tons).