Retail Sales
Get Advance Retail Sales (Retail and Food Services) for the United States from the Census Bureau.
Retail Sales measures nominal spending at retail and food-service establishments. Since Personal Consumption Expenditures make up roughly two-thirds to three-quarters of US GDP, this monthly, high-frequency series is a core input to real-time (nowcast) GDP estimates such as the Federal Reserve Bank of Atlanta’s GDPNow.
The series is monthly, in millions of US dollars, seasonally adjusted, and covers retail trade and food services. It is nominal, so growth=True mixes volume and price changes together; compare against the Consumer Price Index to separate the two.
No API key is needed: without a FRED API key the data comes from the Census Bureau directly, which gives the same figures. When a FRED API key is set (see the fred_api_key parameter of the Economics class), it comes from FRED.
See definition: https://fred.stlouisfed.org/series/RSAFS
Also known as: retail trade, consumer spending (proxy).
Retail Sales in Python or via the MCP
Install the Finance Toolkit with:
pip install financetoolkit -U
Then call get_retail_sales as shown below.
from financetoolkit import Economics
economics = Economics(
start_date='2020-01-01',
end_date="2025-12-31",
)
economics.get_retail_sales()
Or, after setting up the Finance Toolkit MCP, ask:
How did monthly US retail and food services sales develop from August to December 2025?
Which returns:
| Date | United States |
|---|---|
| 2025-08-01 | 700407 |
| 2025-09-01 | 700948 |
| 2025-10-01 | 700790 |
| 2025-11-01 | 705453 |
| 2025-12-01 | 706264 |
Parameters
get_retail_sales accepts the following parameters.
| Parameter | Type | Description | Example |
|---|---|---|---|
rolling | int | The rolling window size to use for smoothing the data (simple moving average). Defaults to None. | 4 |
trailing | int | The trailing window size to use for summing the data over trailing periods. Defaults to None. | 4 |
growth | bool | Whether to return the growth data or the actual data. Defaults to False. | True |
lag | int | The number of periods to lag the data by. Defaults to 1. | 4 |
standardize | bool | Whether to standardize (Z-Score) the result. When combined with growth=True, standardizes the growth values instead of the raw values. Defaults to False. | True |
rounding | int | None | The number of decimals to round the results to. Defaults to None. | 2 |