The Consumer Price Index (CPI) for food is a component of the all-items CPI. The CPI measures the average change over time in the prices paid by urban consumers for a representative market basket of consumer goods and services. While the all-items CPI measures the price changes for all consumer goods and services, including food, the CPI for food measures the changes in the retail prices of food items only.This record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: Web page with links to Excel files For complete information, please visit https://data.gov.

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. The data goes back as far as 1992 for a few countries, although many countries started reporting from 2003 or thereafter.

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

Food price increases hit the egg category the hardest between December 2021 and December 2024 in the United States. The price of eggs increased by **** percent in 2024.

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

This statistic depicts the consumer price index (CPI) for food in the United States from 1960 to 2024. In December 2024, the consumer price index (CPI) for food amounted to ******, compared to the period from 1982 to 1984 (=100).

This dataset contains Food Prices data for Benin, 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.

Graph and download economic data for Global price of Food index (PFOODINDEXA) from 1992 to 2024 about World, food, indexes, and price.

View monthly updates and historical trends for US Consumer Price Index: Food. from United States. Source: Bureau of Labor Statistics. Track economic data …

Graph and download economic data for Consumer Price Index for All Urban Consumers: Nondurables Less Food in U.S. City Average (CUUR0000SANL1) from Mar 1935 to Sep 2025 about nondurable goods, food, urban, consumer, goods, CPI, inflation, price index, indexes, price, and USA.

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.

The FAO vegetable oil Price Index* reached 178.32 index points in June of 2008 during the financial crisis. During the pandemic, the price index rose to 184.56 points in October of 2021. After the start of the war in Ukraine, the index jumped to over 251 points in March of 2022. As of September 2025, the index had slightly declined to 167.9 points. For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page. For further information about the Russian invasion of Ukraine, please visit our dedicated page on the topic.

Context:

The Bureau of Labor Statistics defines the Consumer Price Index (CPI) as “a statistical measure of change, over time, of the prices of goods and services in major expenditure groups--such as food, housing, apparel, transportation, and medical care--typically purchased by urban consumers. Essentially, it compares the cost of a sample of goods and services in a specific month relative to the cost of the same "market basket" in an earlier reference period.

Make sure to read the cu.txt for more descriptive summaries on each data file and how to use the unique identifiers.

Content:

This dataset was collected June 27th, 2017 and may not be up-to-date.

The revised CPI introduced by the BLS in 1998 includes indexes for two populations; urban wage earners and clerical workers (CW), and all urban consumers (CU). This dataset covers all urban consumers (CU).

The Consumer Price Index (CPI) is a statistical measure of change, over time, of the prices of goods and services in major expenditure groups--such as food, housing, apparel, transportation, and medical care--typically purchased by urban consumers. Essentially, it compares the cost of a sample "market basket" of goods and services in a specific month relative to the cost of the same "market basket" in an earlier reference period. This reference period is designated as the base period.

As a result of the 1998 revision, both the CW and the CU utilize updated expenditure weights based upon data tabulated from three years (1982, 1983, and 1984) of the Consumer Expenditure Survey and incorporate a number of technical improvements, including an updated and revised item structure.

To construct the two indexes, prices for about 100,000 items and data on about 8,300 housing units are collected in a sample of 91 urban places. Comparison of indexes for individual CMSA's or cities show only the relative change over time in prices between locations. These indexes cannot be used to measure interarea differences in price levels or living costs.

Summary Data Available: U.S. average indexes for both populations are available for about 305 consumer items and groups of items. In addition, over 100 of the indexes have been adjusted for seasonality. The indexes are monthly with some beginning in 1913. Semi-annual indexes have been calculated for about 100 items for comparison with semi-annual areas mentioned below. Semi-annual indexes are available from 1984 forward.

Area indexes for both populations are available for 26 urban places. For each area, indexes are published for about 42 items and groups. The indexes are published monthly for three areas, bimonthly for eleven areas, and semi-annually for 12 urban areas.

Regional indexes for both populations are available for four regions with about 55 items and groups per region. Beginning with January 1987, indexes are monthly, with some beginning as early as 1966. Semi-annual indexes have been calculated for about 42 items for comparison with semi-annual areas mentioned above. Semi-annual indexes have been calculated for about 42 items in the 27 urban places for comparison with semi-annual areas.

City-size indexes for both populations are available for three size classes with about 55 items and groups per class. Beginning with January 1987, indexes are monthly and most begin in 1977. Semi-annual indexes have been calculated for about 42 items for comparison with semi-annual areas mentioned below.

Region/city-size indexes for both populations are available cross classified by region and city-size class. For each of 13 cross calculations, about 42 items and groups are available. Beginning with January 1987, indexes are monthly and most begin in 1977. Semi-annual indexes have been calculated for about 42 items in the 26 urban places for comparison with semi-annual areas.

Frequency of Observations: U.S. city average indexes, some area indexes, and regional indexes, city-size indexes, and region/city-size indexes for both populations are monthly. Other area indexes for both populations are bimonthly or semi-annual.

Annual Averages: Annual averages are available for all unadjusted series in the CW and CU.

Base Periods: Most indexes have a base period of 1982-1984 = 100. Other indexes, mainly those which have been added to the CPI program with the 1998 revision, are based more recently. The base period value is 100.0, except for the "Purchasing Power" values (AAOR and SAOR) where the base period value is 1.000.

Data Characteristics: Indexes are stored to one decimal place, except for the "Purchasing Power" values which are stored to three decimal places.

References: BLS Handbook of Methods, Chapter 17, "Consumer Price Index", BLS Bulletin 2285, April 1988.

Acknowledgements:

This dataset was taken directly from the U.S. Bureau of Labor Statistics web...

This dataset contains monthly retail price data for a wide range of consumer products sold in various Canadian provinces over several years. It has been enriched with tax, category, and classification metadata for deeper insights.

Usefulness of the Dataset

This dataset can be used for:

Purpose and Use Cases

This dataset is ideal for:

🏛️ Policy Analysis

Understand how federal and provincial taxes shape price access — especially for essentials like milk, bread, or medications.

🧍‍♀️ Consumer Insights

See how costs for personal care, food, and baby goods evolve month-over-month in each region.

💸 Inflation & Seasonality

Analyze how monthly or yearly trends (e.g., holiday spikes or inflation events) affect product pricing.

🌍 Social Impact Studies

Measure product accessibility gaps between provinces for low-income consumers or high-tax regions.

🛍️ Retail & Budget Planning

Guide families, retailers, or policymakers on where and when to buy or subsidize certain products.

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.

Graph and download economic data for Consumer Price Index for All Urban Consumers: Other Goods and Services in Northeast - Size Class A (CUURA100SAG) from Dec 1977 to Sep 2025 about urban, consumer, goods, CPI, services, inflation, price index, indexes, price, and USA.

In 2022 and 2023, the price for a hamper with essential food products rose continuously in Portugal, reaching its highest value in March 2023, at 234.84 euros. After a decrease for a few months, prices rose again starting in August 2023. In January 2024, the price escalated once again, meaning that Portuguese families had to pay more than 243 euros to supply their pantry with essential food items. The year 2024 presented slight fluctuations, and, by July 2025, the price of a hamper peaked to its all-time highest value of 245.79 euros.

Cost of food in Russia increased 8.91 percent in October of 2025 over the same month in the previous year. This dataset provides the latest reported value for - Russia Food Inflation - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

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.

Russia Consumer Price Index (CPI): Same Mth PY=100: Other Goods: Sports & Tourism Goods data was reported at 100.480 Same Mth PY=100 in Dec 2018. This records an increase from the previous number of 100.470 Same Mth PY=100 for Nov 2018. Russia Consumer Price Index (CPI): Same Mth PY=100: Other Goods: Sports & Tourism Goods data is updated monthly, averaging 105.815 Same Mth PY=100 from Jan 1999 (Median) to Dec 2018, with 240 observations. The data reached an all-time high of 198.490 Same Mth PY=100 in Aug 1999 and a record low of 99.880 Same Mth PY=100 in May 2018. Russia Consumer Price Index (CPI): Same Mth PY=100: Other Goods: Sports & Tourism Goods data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Russia Premium Database’s Inflation – Table RU.IA015: Consumer Price Index: Same Month Previous Year=100: Non Food.