This dataset contains Food Prices data for Nigeria, 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.

Source: FEWSNET via FAO: GIEWS, FPMA, Nigeria, SIMA - Niger, WFP Contributor: WFP - World Food Programme License: Creative Commons Attribution for Intergovernmental Organisations (CC BY-IGO)

Explore this dataset, a vibrant part of the Nigeria Data Grid, offering a comprehensive view of Food Prices in Nigeria. Curated from the World Food Programme Price Database, it covers essentials like maize, rice, beans, fish, and sugar.

Unravel market dynamics, analyze trends, and gain unique insights for research, policymaking, and a nuanced understanding of the intricate tapestry of food pricing in Nigeria.

Cost of food in Nigeria increased 13.12 percent in October of 2025 over the same month in the previous year. This dataset provides - Nigeria Food Inflation - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Nigeria: Food price index, world average = 100: The latest value from 2021 is 101.71 index points, an increase from 84.436 index points in 2017. In comparison, the world average is 105.854 index points, based on data from 165 countries. Historically, the average for Nigeria from 2017 to 2021 is 93.073 index points. The minimum value, 84.436 index points, was reached in 2017 while the maximum of 101.71 index points was recorded in 2021.

As of May 2024, the average price in Nigeria for a unit of frozen chicken added up to slightly over 4,829 Nigerian naira (NGN), which equaled 3.2 U.S. dollars. One kilogram of boneless beef cost 4,712 NGN (3.14 U.S dollars), whereas one piece of medium-sized chicken eggs reached nearly 151 NGN (10 cents).

In September 2023, the Consumer Index Price of food in Nigeria stood at 737.3, increasing from the previous year. Consumer price index is a measure that examines the changes in the purchasing power of a currency. It measures changes in the price level of the market basket of consumer goods and services purchased by households. The movement of the Consumer Price Index is the main measure for inflation rate.

Online data collected from the Jumia online store. The data is centered around food stuff price variations given, discounts, ratings and other variables. - Name - Product Name - Current Price - price at the time of data gathering - Old Price - Price before discount(if any) - % discount - percentage discount that applies - Rating - Product ratings{on a 0-5 scale} - Review Count - Number of reviews per product - Shipped? - Factor variable; whether or not a product was shipped from overseas - Official Store? - Factor variable; whether or not a product was bought from the official store

This dataset provides a sample of 100+ Nigerian food items. It includes information on the food's name, main ingredients, a brief description, food health (generally healthy, moderately healthy, or not healthy), food class (traditional, snack, breakfast, etc.), region of origin, spice level (mild, medium, or spicy), and price range (affordable, moderate, expensive, or very expensive).

This data can be used to explore the variety of Nigerian cuisine, understand the health profile of different dishes, and learn about regional specialties.

The Data can be used for: - Food Recommendation: Recommend dishes based on user preferences (e.g., spice level, region, dietary restrictions). - Price Prediction: Predict the price range of a dish based on ingredients. - Nutritional Analysis: Estimate the nutritional content of a dish based on ingredients.

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: Abia, Borno, Yobe, Katsina, Kano, Kaduna, Gombe, Adamawa, Jigawa, Kebbi, Oyo, Sokoto, Zamfara, Lagos, Market Average

In April 2024, food prices in Nigeria increased considerably compared to April of the preceding year. Prices of sweet potato, plantain (unripe), and broken rice (ofada) increased the most. In particular, the price of a kilogram of unripe plantain grew by over 168 percent compared to the previous year, while the price of a tuber of yam rose by about 154 percent. Overall, none of the selected foods recorded a price decrease.

In 2023, overseas purchases of canned food were finally on the rise to reach 142K tons after two years of decline.

As of January 2021, the greatest majority of Nigerian households reported experiencing an increase in the prices of essential food items, as over ** percent of households said the prices of beans, cassava, yam, and sorghum shot higher since January 2020. Moreover, ** percent of respondents said that the prices of rice increased over the same timespan and ** percent found onion more expensive than it used to be.

As of December 2022, food inflation in Africa varied among the continent's sub-regions. East and West Africa registered **** percent and **** percent, respectively. Middle and Southern Africa recorded the lowest changes in food prices. Overall, food inflation increased in all regions compared to January 2020.

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: Ouaka, Mbomou, Bangui, Nana-Mambéré, Ouham, Sangha-Mbaéré, Ombella M'Poko, Mambéré-Kadéï, Vakaga, Ouham Pendé, Lobaye, Haute-Kotto, Kémo, Nana-Gribizi, Bamingui-Bangoran, Haut-Mbomou, Market Average

For the third consecutive year, Nigeria recorded decline in purchases abroad of food preparations for infants, which decreased by -8.9% to 14K tons in 2023.

Nigeria Weekly staple food price data collected by FEWS NET since 2003.

This dataset contains Food Prices data for Nigeria, 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.

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.

Get the latest USA Nigerian Foods import data with importer names, shipment details, buyers list, product description, price, quantity, and major US ports.

Timely and reliable monitoring of commodity food prices is an essential requirement for the assessment of market and food security risks and the establishment of early warning systems, especially in developing economies. However, data from regional or national systems for tracking changes of food prices in sub-Saharan Africa lacks the temporal or spatial richness and is often insufficient to inform targeted interventions. In addition to limited opportunity for [near-]real-time assessment of food prices, various stages in the commodity supply chain are mostly unrepresented, thereby limiting insights on stage-related price evolution. Yet, governments and market stakeholders rely on commodity price data to make decisions on appropriate interventions or commodity-focused investments. Recent rapid technological development indicates that digital devices and connectivity services are becoming affordable for many, including in remote areas of developing economies. This offers a great opportunity both for the harvesting of price data (via new data collection methodologies, such as crowdsourcing/crowdsensing — i.e. citizen-generated data — using mobile apps/devices), and for disseminating it (via web dashboards or other means) to provide real-time data that can support decisions at various levels and related policy-making processes. However, market information that aims at improving the functioning of markets and supply chains requires a continuous data flow as well as quality, accessibility and trust. More data does not necessarily translate into better information. Citizen-based data-generation systems are often confronted by challenges related to data quality and citizen participation, which may be further complicated by the volume of data generated compared to traditional approaches. Following the food price hikes during the first noughties of the 21st century, the European Commission's Joint Research Centre (JRC) started working on innovative methodologies for real-time food price data collection and analysis in developing countries. The work carried out so far includes a pilot initiative to crowdsource data from selected markets across several African countries, two workshops (with relevant stakeholders and experts), and the development of a spatial statistical quality methodology to facilitate the best possible exploitation of geo-located data. Based on the latter, the JRC designed the Food Price Crowdsourcing Africa (FPCA) project and implemented it within two states in Northern Nigeria. The FPCA is a credible methodology, based on the voluntary provision of data by a crowd (people living in urban, suburban, and rural areas) using a mobile app, leveraging monetary and non-monetary incentives to enhance contribution, which makes it possible to collect, analyse and validate, and disseminate staple food price data in real time across market segments. The granularity and high frequency of the crowdsourcing data open the door to real-time space-time analysis, which can be essential for policy and decision making and rapid response on specific geographic regions. Link to the project