This dataset contains a list of sales and movement data by item and department appended monthly. Update Frequency : Monthly

A series of retail sales data for Great Britain in value and volume terms, seasonally and non-seasonally adjusted.

Standard error reference tables for the Retail Sales Index in Great Britain.

Retail Sales in the United States increased 0.60 percent in August of 2025 over the previous month. This dataset provides - U.S. December Retail Sales Increased More Than Forecast - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Graph and download economic data for Advance Retail Sales: Department Stores (RSDSELD) from Jan 1992 to Mar 2025 about leases, retail trade, sales, retail, and USA.

Analysis of ‘Retail and Retailers Sales Time Series Collection’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/census/retail-and-retailers-sales-time-series-collection on 30 September 2021.

--- Dataset description provided by original source is as follows ---

Content

More details about each file are in the individual file descriptions.

Context

This is a dataset from the U.S. Census Bureau hosted by the Federal Reserve Economic Database (FRED). FRED has a data platform found here and they update their information according the amount of data that is brought in. Explore the U.S. Census Bureau using Kaggle and all of the data sources available through the U.S. Census Bureau organization page!

• Update Frequency: This dataset is updated daily.

Acknowledgements

This dataset is maintained using FRED's API and Kaggle's API.

Cover photo by Matteo Catanese on Unsplash
Unsplash Images are distributed under a unique Unsplash License.

--- Original source retains full ownership of the source dataset ---

Content

More details about each file are in the individual file descriptions.

Context

This is a dataset from the U.S. Census Bureau hosted by the Federal Reserve Economic Database (FRED). FRED has a data platform found here and they update their information according the amount of data that is brought in. Explore the U.S. Census Bureau using Kaggle and all of the data sources available through the U.S. Census Bureau organization page!

• Update Frequency: This dataset is updated daily.

Acknowledgements

This dataset is maintained using FRED's API and Kaggle's API.

Cover photo by Cristiane Teston on Unsplash
Unsplash Images are distributed under a unique Unsplash License.

Graph and download economic data for Retail Sales: Office Supplies and Stationery Stores (MRTSMPCSM45321USN) from Feb 1992 to Jul 2025 about paper, supplies, retail trade, sales, retail, and USA.

Internet sales in Great Britain by store type, month and year.

An indicator of Economic Growth in the Scottish Retail sector. Source agency: Scottish Government Designation: National Statistics Language: English Alternative title: Scottish Retail Sales Index

Total sales and average weekly spending estimates for each retail sector in Great Britain in thousands of pounds.

This dataset contains the spirits purchase information of Iowa Class “E” liquor licensees by product and date of purchase from January 1, 2012 to current. The dataset can be used to analyze total spirits sales in Iowa of individual products at the store level.

Class E liquor license, for grocery stores, liquor stores, convenience stores, etc., allows commercial establishments to sell liquor for off-premises consumption in original unopened containers.

The Department of Taxation and Finance administers the statewide New York State general retail sales and compensating use tax, as well as any general retail sales and compensating use tax imposed by a county or municipality in New York State. In addition, the Department administers any taxes imposed on consumer utilities services and other special taxes on selected commodities and services by municipalities and city school districts. This data set presents information on the yearly amount of the distribution of these taxes back to the appropriate taxing jurisdictions from fiscal years ended March 31, 1995.

Dataset from Singapore Department of Statistics. For more information, visit https://data.gov.sg/datasets/d_e5f83bef6d21f3e9edd7f9308bf9eeba/view

This dataset contains every wholesale purchase of liquor in the State of Iowa by retailers for sale to individuals since January 1, 2012. The State of Iowa controls the wholesale distribution of liquor intended for retail sale, which means this dataset offers a complete view of retail liquor sales in the entire state. The dataset contains every wholesale order of liquor by all grocery stores, liquor stores, convenience stores, etc., with details about the store and location, the exact liquor brand and size, and the number of bottles ordered. In addition to being an excellent dataset for analyzing liquor sales, this is a large and clean public dataset of retail sales data. It can be used to explore problems like stockout prediction, retail demand forecasting, and other retail supply chain problems. The data dictionary is available from the State of Iowa's Alcoholic Beverages Division , within the Iowa Department of Commerce . There are some minor discrepancies in the data, discussed in the web view of the data . This public dataset is hosted in Google BigQuery and is included in BigQuery's 1TB/mo of free tier processing. This means that each user receives 1TB of free BigQuery processing every month, which can be used to run queries on this public dataset. Watch this short video to learn how to get started quickly using BigQuery to access public datasets. What is BigQuery.

Dataset from Singapore Department of Statistics. For more information, visit https://data.gov.sg/datasets/d_65e4d47c3616d251f9a84ec1ad28f43c/view

Business' or organization's current level of total sales revenue and inventory levels compared to pre-pandemic levels, by North American Industry Classification System (NAICS), business employment size, type of business, business activity and majority ownership, third quarter of 2024.

Analysis of ‘US Public Food Assistance’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/jpmiller/publicassistance on 20 November 2021.

--- Dataset description provided by original source is as follows ---

Context

This dataset focuses on public assistance programs in the United States that provide food, namely SNAP and WIC. If you are interested in a broader picture of food security across the world, please see Food Security Indicators for the World 2016-2020.

Initial coverage was for the Special Supplemental Nutrition Program for Women, Infants, and Children Program, or simply WIC. The program allocates Federal and State funds to help low-income women and children up to age five who are at nutritional risk. Funds are used to provide supplemental foods, baby formula, health care, and nutrition education.

Starting with version 5, the dataset also covers the US Supplemental Nutrition Assistance Program, more commonly known as SNAP. The program is the successor to the Food Stamps program previously in place. The program provides food assistance to low-income families in the form of a debit card. A 2016 study using POS data from SNAP-eligible vendors showed the three most purchased types of food to be meats, sweetened beverages, and vegetables.

Content

Files may include participation data and spending for state programs, and poverty data for each state. Data for WIC covers fiscal years 2013-2016, which is actually October 2012 through September 2016. Data for SNAP covers 2015 to 2020.

Motivation

My original purpose here is two-fold:

• Explore various aspects of US Public Assistance. Show trends over recent years and better understand differences across state agencies. Although the federal government sponsors the program and provides funding, program are administered at the state level and can widely vary. Indian nations (native Americans) also administer their own programs.

• Share with the Kaggle Community the joy - and pain - of working with government data. Data is often spread across numerous agency sites and comes in a variety of formats. Often the data is provided in Excel, with the files consisting of multiple tabs. Also, files are formatted as reports and contain aggregated data (sums, averages, etc.) along with base data.

As of March 2nd, I am expanding the purpose to support the M5 Forecasting Challenges here on Kaggle. Store sales are partly driven by participation in Public Assistance programs. Participants typically receive the items free of charge. The store then recovers the sale price from the state agencies administering the program.

Additional Content Ideas

The dataset can benefit greatly from additional content. Economics, additional demographics, administrative costs and more. I'd like to eventually explore the money trail from taxes and corporate subsidies, through the government agencies, and on to program participants. All community ideas are welcome!

--- Original source retains full ownership of the source dataset ---

This table contains 164 series, with data for years 1968 - 1990 (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), Department store sales or stocks (2 items: Sales; Stocks), Seasonal adjustment (2 items: Unadjusted; Seasonally adjusted), Type of department (41 items: All departments; Women's and misses' dresses, et cetera; Women's and misses' coats and suits; Women's and misses' sportswear; ...).

This is a complementary dataset for DOI: 10.1007/978-3-030-22335-9_6 Following an open data policy as supported by the European Union (https://www.openaire.eu/), this is the dataset used for the following conference paper: Zimmermann R., Auinger A., Riedl R. (2019) Smartphones as an Opportunity to Increase Sales in Brick-and-Mortar Stores: Identifying Sales Influencers Based on a Literature Review. In: Nah FH., Siau K. (eds) HCI in Business, Government and Organizations. eCommerce and Consumer Behavior. HCII 2019. Lecture Notes in Computer Science, vol 11588. Springer, Cham The present work was conducted within the Innovative Training Network project PERFORM funded by the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No. 765395. The EU Research Executive Agency is not responsible for any use that may be made of the information it contains.