Retail Sales in the United States increased 0.20 percent in September 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.

This dataset, identified by the series ID RSXFS, is sourced from the U.S. Census Bureau and is available through the Federal Reserve Economic Data (FRED) system of the St. Louis Fed. It provides a monthly measure of retail sales across the United States. The data represents the total value of sales at retail and food services stores, measured in millions of dollars and adjusted for seasonal variations. It is important to note that the most recent month's value is an advance estimate, which is subject to revision in subsequent months as more comprehensive data becomes available. As a key economic indicator, this series is widely used by economists and analysts to gauge consumer spending and assess the overall health of the U.S. economy.

Suggested Use Cases: - This dataset is highly valuable for economic analysis and can be used to: - Conduct time series analysis and modeling. - Track consumer spending patterns. - Forecast future retail sales. - Analyze the impact of economic events on the retail sector.

License The RSXFS dataset is sourced from the U.S. Census Bureau and is considered Public Domain: Citation Requested. This means the data is freely available for use, but you must cite the source and acknowledge that the data was obtained from FRED. If you plan on using any copyrighted series from other data providers on FRED for commercial purposes, you would need to contact the original data owner for permission.

Data Fields: The dataset primarily contains two columns: - observation_date: The date of the monthly data point, recorded as the first day of each month from January 1992 to July 2025. - RSXFS: The value of advance retail sales in millions of dollars.

Citation and Provenance:
Source: U.S. Census Bureau
Release: Advance Monthly Sales for Retail and Food Services
FRED Link: https://fred.stlouisfed.org/series/RSXFS
Citation: U.S. Census Bureau, Advance Retail Sales: Retail Trade [RSXFS], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/RSXFS, September 8, 2025.

View monthly updates and historical trends for US Retail Sales. from United States. Source: Census Bureau. Track economic data with YCharts analytics.

This statistic shows a trend in total retail sales, including food services, in the United States from January 2017 to July 2025. In July 2025, U.S. retail sales had amounted to an estimated *********** U.S. dollars (not adjusted), which is an increase of approximately ** ******* U.S. dollars compared to the same month one year earlier.

Context

The Monthly State Retail Sales (MSRS) is the Census Bureau's new experimental data product featuring modeled state-level retail sales. This is a blended data product using Monthly Retail Trade Survey data, administrative data, and third-party data. Year-over-year percentage changes are available for Total Retail Sales excluding Non-store Retailers as well as 11 retail North American Industry Classification System (NAICS) retail subsectors. These data are provided by state and NAICS codes beginning with January 2019.

Content

Geography: US

Time period: 2019 - 2022

Unit of analysis: US Census Bureau's Monthly State Retail Sales Data

Variables

Variable	Description
fips	2-digit State Federal Information Processing Standards (FIPS) code. For more information on FIPS Codes, please reference this document. Note: The US is assigned a "00" State FIPS code.
state_abbr	States are assigned 2-character official U.S. Postal Service Code. The United States is assigned "USA" as its state_abbr value. For more information, please reference this document.
naics	Three-digit numeric NAICS value for retail subsector code.
subsector	Retail subsector.
year	Year.
month	Month.
change_yoy	Numeric year-over-year percent change in retail sales value.
change_yoy_se	Numeric standard error for year-over-year percentage change in retail sales value.
coverage_code	Character values assigned based on the non-imputed coverage of the data.

Variable	Description
coverage_code	Character values assigned based on the non-imputed coverage of the data.
coverage	Definition of the codes.

Acknowledgements

Datasource: United States Census Bureau's Monthly State Retail Sales

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View monthly updates and historical trends for US Real Retail Sales YoY. from United States. Source: Census Bureau. Track economic data with YCharts analy…

Graph and download economic data for Advance Retail Sales: Retail Trade (RSXFS) from Jan 1992 to Aug 2025 about retail trade, sales, retail, services, and USA.

Data Overview

• Scale: All sales figures are reported in millions of dollars.
• Size: The dataset contains 40,479 rows and 5 columns.
• Time Frame: January 1992 - September 2024.
• Industries Covered: Over 60 industries, including food, clothing, footwear, office supplies, automobiles, electronics, books, beverages, furniture, grocery and many more.
• Attributes:
  • naics_code
  • kind_of_business
  • sales_month
  • sales
  • estimate_type
• Source: This dataset was sourced from the publicly available U.S. Census Bureau retail sales data.

Cleaning & Preprocessing

• Missing Values:
  Some entries contained (NA) and (S) values, which were converted to null values.
  • (S): Estimate does not meet publication standards due to high sampling variability (coefficient of variation greater than 30%) or poor response quality (low total quantity response rate).
• Formatting:
  The downloaded data included headings, subheadings, and notes embedded within the tables. These extraneous elements were removed to ensure a clean and consistent dataset.
• Data Compilation:
  The original dataset was spread across multiple sheets, with each sheet containing data for a specific year. These sheets were consolidated into a single, unified table.
• Feature Engineering:
  A new column was created to provide both seasonally adjusted and non-seasonally adjusted sales values, enabling more nuanced analysis. Estimates are adjusted for seasonal variations, as well as holiday and trading-day differences, but not for price changes.

Use Cases

This dataset can be applied to a variety of analytical and machine learning tasks, including:

• Data Cleaning: Practice handling missing values, stray entries, and working with datetime data.
• Time Series Analysis: Perform trend analysis, seasonality detection, and forecasting.
• Exploratory Data Analysis (EDA): Gain insights into industry-specific trends and patterns.
• Machine Learning: Use it for predictive modeling and classification tasks.
• Market Research: Analyze industry performance to inform business strategies.

Columns: • Order Date: Consists the date on which a specific order was created. • Customer Name: Consists the full name of the customer who created an order. • State: Name of the state the customer belonged to. • Category: Which category did the ordered product belonged to. • Sub – Category: Name of the sub – category of the ordered product. • Product Name: Name of the ordered product. • Sales: The price at which the product was sold. • Quantity: Number of quantities the customer ordered of that product. • Profit: How much did the firm made in that transaction.

Overview with Chart & Report: Retail Sales m/m reflect a change in the US retail sails in the reported month compared to the previous one. The indicator is calculated based on statistics received from 5,000 retail stores of

View monthly updates and historical trends for US Real Retail Sales. from United States. Source: Census Bureau. Track economic data with YCharts analytics.

The 'Retail Sales MoM' (Month-over-Month) in the USA measures the percentage change in the total value of sales at the retail level from one month to the next.-2025-08-15

Graph and download economic data for Advance Retail Sales: Electronics and Appliance Stores (RSEAS) from Jan 1992 to Sep 2025 about appliances, electronics, retail trade, sales, retail, and USA.

Graph and download economic data for Advance Retail Sales: Food and Beverage Stores (RSDBS) from Jan 1992 to Sep 2025 about beverages, retail trade, food, sales, retail, and USA.

Graph and download economic data for Monthly State Retail Sales: Total Retail Sales Excluding Nonstore Retailers in the United States (MSRSUSATOTAL) from Jan 2019 to Jun 2025 about retail trade, sales, retail, and USA.

Key information about United States Retail Sales Growth

• United States Retail Sales grew 4.1 % YoY in Sep 2025, compared with a 4.9 % increase in the previous month.
• US Retail Sales Growth YoY data is updated monthly, available from Jan 1993 to Sep 2025, with an average growth rate of -8.8 %.
• The data reached an all-time high of 42.0 % in Apr 2021 and a record low of -15.8 % in Apr 2020.
• In the latest reports, Car Sales of US recorded 1,491,440.0 units in Aug 2025, representing a growth of 2.4 %.

CEIC calculates monthly Retail Sales: Excl. Motor Vehicles Growth from monthly Retail Sales excluding Motor Vehicle and Parts. The U.S. Census Bureau provides Retail Sales excluding Motor Vehicle and Parts in USD. Retail Sales include Food Services.

By the end of 2024, total retail sales reached approximately **** trillion U.S. dollars, around a quarter of a billion U.S. dollar increase from the year before. Retail sales have steadily increased since 2009, as the economy recovered from the downward trend due to the recession following the 2007-2008 financial crisis, and most recently from the impact of the coronavirus (COVID-19) crisis. The United States as retail powerhouse The United States is home to many of the leading retail companies in the world, including Walmart, Costco, and Amazon. Amazon, in particular, has seen extreme levels of growth in revenue in tandem with the increase of e-commerce globally. The rise of e-commerce and mobile shopping E-commerce is responsible for a growing percentage of total retail sales, partially due to a surge in mobile shopping, with customers increasingly using their mobile devices for various online shopping activities. Smartphones accounted for more retail website visits than desktops or tablets, and matched desktops in generating online shopping orders.

The statistic shows retail sales in the United States in 2015, by format, and provides a forecast for 2020. In 2015, about ****** billion U.S. dollars were generated through the supercenter channel.

The 'Retail Sales MoM' (Month-over-Month) in the USA measures the percentage change in the total value of sales at the retail level from one month to the next.-2025-01-16

The dataset contains 9,700 rows and 11 columns. The columns in the dataset are as follows:

Order_ID: A unique identifier for each order. Order_Date: Date the order was placed. Customer_ID: A unique identifier for each customer Segment: Customer segment. Country: The country in which the order was made. City: The city in which the order was made. State: The state in which the order was made. Product_ID: A unique identifier for each product. Category: Product category. SubCategory: Product subcategory. Sale_Value: Sale value.

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