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Cost of food in the United States increased 3 percent in June 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.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Cost of food in Canada increased 2.90 percent in June 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.
Value chain disruptions are expected to trigger sudden price changes and increase in price volatility. This is data from the FAO Daily Prices pages which monitors consumer prices of 14 main food products in all countries and compiles the average price change for each product since 14 February 2020.
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.
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.
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Cost of food in India decreased 1.06 percent in June 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.
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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.
Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
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The online price changes for a selection of food and drink products from several large UK retailers. These data are experimental estimates developed to deliver timely indicators to help better understand real time economic activity and social change in the UK.
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.
The data cover the following sub-national areas: Nord, Extrême-Nord, Ouest, Nord-Ouest, Adamaoua, Sud-Ouest, Est, Littoral, Centre, Market Average
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.
The data cover the following sub-national areas: North, South, Artibonite, Centre, South-East, Grande'Anse, North-East, West, North-West, Market Average
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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Food Price Index in World increased to 128 Index Points in June from 127.30 Index Points in May of 2025. This dataset includes a chart with historical data for World Food Price Index.
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.
The data cover the following sub-national areas: Akkar, Mount Lebanon, Baalbek-El Hermel, North, Beirut, Bekaa, El Nabatieh, South, Market Average
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.
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.
The data cover the following sub-national areas: Yangon, Rakhine, Shan (North), Kayin, Kachin, Shan (South), Mon, Tanintharyi, Mandalay, Kayah, Shan (East), Chin, Magway, Sagaing, Market Average
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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Cost of food in European Union increased 3.60 percent in June 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.
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.
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
This data package contains UK controlled drugs database, US food prices database, US nationwide food consumption survey, US national health and nutrition examination survey, US healthy eating index and data on food affordability for households led by females.
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
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How much do fruits and vegetables cost? ERS estimated average prices for 153 commonly consumed fresh and processed fruits and vegetables.
https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/
https://imgur.com/AYzsmYU.jpg" alt="Dataset Structure">
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
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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This series gives the average wholesale prices of selected home-grown horticultural produce in England and Wales. These are averages of the most usual prices charged by wholesalers for selected home-grown fruit, vegetables and cut flowers at the wholesale markets in Birmingham, Bristol, Manchester and a London Market (New Spitalfields or Western International). This publication is updated fortnightly.
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This file is in an <a href="https://www.gov.uk/guidance/using-open-document-formats-odf-in-your-organisation" target="_self" class="govuk-link">OpenDocument</a> format
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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Cost of food in the United Kingdom increased 4.50 percent in June of 2025 over the same month in the previous year. This dataset provides the latest reported value for - United Kingdom Food Inflation - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Cost of food in the United States increased 3 percent in June 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.