Cost of food in the United States increased 2.90 percent in May of 2025 over the same month in the previous year. This dataset provides the latest reported value for - United States Food Inflation - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Cost of food in Canada increased 3.40 percent in May of 2025 over the same month in the previous year. This dataset provides the latest reported value for - Canada Food Inflation - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Abstract

Food price inflation is an important metric to inform economic policy but traditional sources of consumer prices are often produced with delay during crises and only at an aggregate level. This may poorly reflect the actual price trends in rural or poverty-stricken areas, where large populations reside in fragile situations. This data set includes food price estimates and is intended to help gain insight in price developments beyond what can be formally measured by traditional methods. The estimates are generated using a machine-learning approach that imputes ongoing subnational price surveys, often with accuracy similar to direct measurement of prices. The data set provides new opportunities to investigate local price dynamics in areas where populations are sensitive to localized price shocks and where traditional data are not available.

Geographic coverage notes

The data cover the following areas: Afghanistan, Armenia, Bangladesh, Burkina Faso, Burundi, Cameroon, Central African Republic, Chad, Congo, Dem. Rep., Congo, Rep., Gambia, The, Guinea, Guinea-Bissau, Haiti, Indonesia, Iraq, Kenya, Lao PDR, Lebanon, Liberia, Libya, Malawi, Mali, Mauritania, Mozambique, Myanmar, Niger, Nigeria, Philippines, Senegal, Somalia, South Sudan, Sri Lanka, Sudan, Syrian Arab Republic, Yemen, Rep.

Abstract

Food price inflation is an important metric to inform economic policy but traditional sources of consumer prices are often produced with delay during crises and only at an aggregate level. This may poorly reflect the actual price trends in rural or poverty-stricken areas, where large populations reside in fragile situations. This data set includes food price estimates and is intended to help gain insight in price developments beyond what can be formally measured by traditional methods. The estimates are generated using a machine-learning approach that imputes ongoing subnational price surveys, often with accuracy similar to direct measurement of prices. The data set provides new opportunities to investigate local price dynamics in areas where populations are sensitive to localized price shocks and where traditional data are not available.

        A dataset of monthly food price inflation estimates (aggregated for all food products available in the data) is also available for all countries covered by this modeling exercise.

Geographic coverage notes

The data cover the following sub-national areas: North, South, Artibonite, Centre, South-East, Grande'Anse, North-East, West, North-West, Market Average

Cost of food in India increased 0.99 percent in May of 2025 over the same month in the previous year. This dataset provides - India Food Inflation - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Monthly average retail prices for selected products, for Canada and provinces. Prices are presented for the current month and the previous four months. Prices are based on transaction data from Canadian retailers, and are presented in Canadian current dollars.

This dataset contains Food Prices data for India, sourced from the World Food Programme Price Database. The World Food Programme Price Database covers foods such as maize, rice, beans, fish, and sugar for 98 countries and some 3000 markets. It is updated weekly but contains to a large extent monthly data. The data goes back as far as 1992 for a few countries, although many countries started reporting from 2003 or thereafter.

Cost of food in Australia increased 3.20 percent in March of 2025 over the same month in the previous year. This dataset provides - Australia Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

This dataset contains Global Food Prices data from the World Food Programme covering foods such as maize, rice, beans, fish, and sugar for 76 countries and some 1,500 markets. The data goes back as far as 1992 for a few countries, although many countries started reporting from 2003 or thereafter.

The CSV files contains more than 1.048M rows. Data includes information on country, market, price of good in local currency, quantity of good, and month recorded.

This data is compiled by the World Food Program and distributed by HDX.

A collection of over 75 charts and maps presenting key statistics on the farm sector, food spending and prices, food security, rural communities, the interaction of agriculture and natural resources, and more. How much do you know about food and agriculture? What about rural America or conservation? ERS has assembled more than 75 charts and maps covering key information about the farm and food sectors, including agricultural markets and trade, farm income, food prices and consumption, food security, rural economies, and the interaction of agriculture and natural resources. How much, for example, do agriculture and related industries contribute to U.S. gross domestic product? Which commodities are the leading agricultural exports? How much of the food dollar goes to farmers? How do job earnings in rural areas compare with metro areas? How much of the Nation’s water is used by agriculture? These are among the statistics covered in this collection of charts and maps—with accompanying text—divided into the nine section titles.

Explore the Meijer Grocery Store Dataset, a comprehensive collection of data on products available at Meijer, a leading American grocery store chain. This dataset includes detailed information on a wide variety of grocery items such as fresh produce, dairy, meat, beverages, household essentials, and more. Each product entry provides essential details, including product names, categories, prices, brands, descriptions, and availability, offering valuable insights for researchers, data analysts, and retail professionals.

Key Features:

• Extensive Product Range: Contains a wide array of grocery items from Meijer, covering multiple categories like fresh produce, dairy, meat, beverages, household essentials, and more.
• Detailed Product Information: Each entry includes key details such as product name, category, price, brand, description, and availability, allowing for in-depth analysis of retail trends and consumer preferences.
• Ideal for Market Analysis: Perfect for researchers, data scientists, and retail professionals interested in analyzing consumer behavior, studying grocery market trends, or optimizing inventory strategies in the retail sector.
• Rich Source of Retail Data: Provides a comprehensive overview of the grocery market at Meijer, helping professionals stay updated on the latest trends, popular products, and pricing strategies.

Whether you're analyzing market trends in the grocery sector, researching consumer behavior, or developing new retail strategies, the Meijer Grocery Store Dataset is an invaluable resource that provides detailed insights and extensive coverage of products available at Meijer.

Dataset from Singapore Department of Statistics. For more information, visit https://data.gov.sg/datasets/d_d2467766bca7c1ed64ecd8fe07029df3/view

August 2022 update

1. The updated database has monthly prices from over 400 supermarkets across six chains (all Shufersal stores, plus ~20 per chain for the other chains), from March 2022-August 2022. Before march there is a steady increase in the number of stores.
2. The current database has combined all the supermarket chains, which required adding two columns - 'ChainName' is the supermarket chain, and 'store_code' is a concatenation of the store_id and the beginning of the chain name, to solve the duplicate store_ids.
3. A new table was constructed to try and identify the manufacturers of each product, given the significant discrepancies in the retailers' reporting. This table ("manufacturer_finder") has identified the likely supplier of around half of the products in the database, and can be used to track specific suppliers (producers/importers).

This dataset was created to analyze changes in prices in the Israeli grocery retail market. It was created based on the files retailers are legally required to upload, available here: https://www.gov.il/he/departments/legalInfo/cpfta_prices_regulations

The data is not complete and downloads increased gradually. Beginning in May 2020 there are sporadic files for three specific Shufersal stores. Starting in November 2021 Downloads increased, ~20-50 stores downloaded at various times from Shufersal, and ~5-10 stores downloaded from a few other retailers.

Different table for each retailer. The table "snifim" specifies the names for stores for Shufersal (in the main table you can find store_id which can be joined to the names).

Description of columns in the Prices tables: Filename - original file name (without the xml extension) store_id - ID of the store upload_date - date of file download. Upload dates before 2020 - unclear what they are, probably of stores which shut down.
PriceUpdateDate - Last date of price change of the item. ItemCode - a unique ID of the item. ItemName - name. ManufacturerName - manufacturer. These data are messy. ManufactureCountry - country of production. ManufacturerItemDescription - similar to ItemName UnitQty - unit of measure Quantity - quantity. UnitOfMeasure - also unit of measure ItemPrice - price (NIS) UnitOfMeasurePrice - price divided by quantity AllowDiscount - boolean/dummy variable.

Supplementary data can be found here: https://docs.google.com/spreadsheets/d/1LYyCt3BTJ-QInja-4iN1vqZ91xV6TAwhywgJxecSOkM/edit?usp=sharing Including: - Analysis of suppliers - different labels associated with each supplier - A table linking Shufersal stores with their store_id - A table with details on how many price files (stores) were downloaded each date.

What are we looking for? - Price collusion - producers raising prices at the same time. - Which producers saw the greatest price increase? - Which is the most expensive store? - Which products are most promoted? You can go to the source and find "promo" tables. - Can you create a user-friendly tool to analyze these data for non-data scientists?

Cost of food in European Union increased 3.60 percent in May of 2025 over the same month in the previous year. This dataset provides - European Union Food Inflation - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Dataset Structure & Description

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Context and Inspiration

I read an article yesterday which got my mind storming, A article by Worldbank on August 15th, 2022 better explains it, It has been quoted below,
I already have a project i'm working on since Feb 2021, trying to solving this problem, listed in my datasets

This dataset showcases the statistics over the past 6-7 decades which covers the production of 150+ unique crops, 50+ livestock elements, Land distribution by usage and population, As aspiring data scientists one can try to extract insights incentivizing the optimal use of natural resources and distribution of resources

August 15, 2022 - Worldbank

Record high food prices have triggered a global crisis that will drive millions more into extreme poverty, magnifying hunger and malnutrition, while threatening to erase hard-won gains in development. The war in Ukraine, supply chain disruptions, and the continued economic fallout of the COVID-19 pandemic are reversing years of development gains and pushing food prices to all-time highs. Rising food prices have a greater impact on people in low- and middle-income countries, since they spend a larger share of their income on food than people in high-income countries. This brief looks at rising food insecurity and World Bank responses to date.

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Context

This is a relatively small dataset of the USDA Monthly Cost of Food report. The data given is from January of each year from 2000-2021. The report details expected food costs broken down by demographic and year, as well as food expenditure level, from a "Thrifty" food plan which describes careful budgeted food purchasing, to a "Liberal" food plan which entails more open food purchasing.

Content

This data was sourced directly from the USDA Food Plans website and read/converted from PDF form using Tabula

Acknowledgements

USDA Food Plans: https://www.fns.usda.gov/cnpp/usda-food-plans-cost-food-reports-monthly-reports Photo by Jakub Kapusnak on Unsplash

Inspiration

How have food costs increased in the last 20 years? Have food costs kept pace with overall inflation, or are they higher or lower than expected? What should projected food costs be going forward?

Like this dataset? See my other datasets!

During the school year, many children receive free and reduced-price breakfast and lunch through the School Breakfast and National School Lunch Programs. What happens when school lets out? Hunger is one of the most severe roadblocks to the learning process. Lack of nutrition during the summer months may set up a cycle for poor performance once school begins again. Hunger also may make children more prone to illness and other health issues. The Summer Food Service Program is designed to fill that nutrition gap and make sure children can get the nutritious meals they need. This data set contains information on summer food service participation, meals served and cash payments provided by state.

Abstract

Food price inflation is an important metric to inform economic policy but traditional sources of consumer prices are often produced with delay during crises and only at an aggregate level. This may poorly reflect the actual price trends in rural or poverty-stricken areas, where large populations reside in fragile situations. This data set includes food price estimates and is intended to help gain insight in price developments beyond what can be formally measured by traditional methods. The estimates are generated using a machine-learning approach that imputes ongoing subnational price surveys, often with accuracy similar to direct measurement of prices. The data set provides new opportunities to investigate local price dynamics in areas where populations are sensitive to localized price shocks and where traditional data are not available.

        A dataset of monthly food price inflation estimates (aggregated for all food products available in the data) is also available for all countries covered by this modeling exercise.

Geographic coverage notes

The data cover the following sub-national areas: Al Dhale'e, Aden, Al Bayda, Al Maharah, Lahj, Al Jawf, Raymah, Al Hudaydah, Hajjah, Amran, Shabwah, Dhamar, Ibb, Sana'a, Al Mahwit, Marib, Hadramaut, Sa'ada, Amanat Al Asimah, Socotra, Taizz, Abyan, Market Average

ABSTRACT Food prices play a major role in setting inflation rates, and in recent years’ global climatic conditions has worsened a lot while global demand is increasing due to the growth of the middle class in countries such as China and India. Rising food prices remains a key concern for the government of Saudi Arabia. Saudi Arabia remains vulnerable to increases in food prices due to its high dependence on imports. The Saudi economy is an open-market based economy which is reflected by data of foreign trade with trading partners of the Kingdom. High degree of economic openness of a country causes the domestic inflation rate to be affected by change in the prices of goods in the country of origin. Saudi government is facing the challenge of limiting inflation amid a spike in global food prices. Another major challenge to the effectiveness of the Saudi monetary policy is the lack of autonomy due to the pegged exchange rate system with the US dollar. This paper attempts to study the market dynamics of the kingdom of Saudi Arabia, drivers responsible for inflation and measures that has been taken by the government to deal with the situation.

The global food prices have surged to historical highs, and there is no consensus on the reasons behind this round of price increases in academia. Based on theoretical analysis, this study uses monthly data from January 2000 to May 2022 and machine learning models to examine the root causes of that period’s global food price surge and global food security situation. The results show that: Firstly, the increase in the supply of US dollars and the rise in oil prices during pandemic are the two most important variables affecting food prices. The unlimited quantitative easing monetary policy of the US dollar is the primary factor driving the global food price surge, and the alternating impact of oil prices and excessive US dollar liquidity are key features of the surge. Secondly, in the context of the global food shortage, the impact of food production reduction and demand growth expectations on food prices will further increase. Thirdly, attention should be paid to potential agricultural import supply chain risks arising from international uncertainty factors such as the ongoing Russia-Ukraine conflict. The Russian-Ukrainian conflict has profoundly impacted the global agricultural supply chain, and crude oil and fertilizers have gradually become the main driving force behind the rise in food prices.