US retail-sales signals
Monthly US retail-sales signals from Census advance retail data (FRED RSXFS nominal retail trade + RRSFS real retail & food services, 1992-01 ->, seasonally adjusted, keyless except the already-provisioned FRED key): year-on-year change, 3-month momentum, 12-month change volatility, 3-sigma anomaly flags, naive-drift forecasts, 5-year spending z-scores, and contraction/strong-expansion flags. The measured monthly household-spending lens between us-consumer-sentiment-signals (stated sentiment) and quarterly real PCE — the nominal/real split shows when spending growth is prices vs volume. All rows normalized to country_code USA. Raw data: Census Bureau via FRED.
Quality
Attribution
US Census Bureau, Monthly Retail Trade Survey via FRED; derived signals by Frontier Data Hub
Schema
| Column | Type | Description |
|---|---|---|
| date | string | Month of observation (Census Monthly Retail Trade Survey, monthly, seasonally adjusted). |
| country | string | |
| country_code | string | |
| series_id | string | RSXFS (advance retail sales, retail trade, nominal) or RRSFS (advance real retail and food services sales), FRED series IDs. |
| series_label | string | Series description: advance retail sales, retail trade (nominal, millions of dollars, SA) or advance real retail and food services sales (millions of 1982-84 CPI-adjusted dollars, SA). |
| value | float | Advance estimate of monthly retail sales in the series' native unit: nominal millions of dollars for RSXFS; millions of 1982-84 CPI-adjusted dollars for RRSFS. |
| yoy_change | float | |
| momentum_3m | float | |
| volatility_30d | float | |
| anomaly_flag | integer | |
| forecast_1m | float | |
| spend_z_5y | float | |
| contraction_flag | integer | |
| strong_flag | integer |
Sample rows
| date | country | country_code | series_id | series_label | value | yoy_change | momentum_3m | volatility_30d | anomaly_flag | forecast_1m | spend_z_5y | contraction_flag | strong_flag |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1992-01-01 | United States | USA | RRSFS | Advance real retail and food services sales (millions of 1982-84 CPI-adjusted $, SA) | 115095 | — | — | — | 0 | — | — | 0 | 0 |
| 1992-02-01 | United States | USA | RRSFS | Advance real retail and food services sales (millions of 1982-84 CPI-adjusted $, SA) | 114855 | — | — | — | 0 | — | — | 0 | 0 |
| 1992-03-01 | United States | USA | RRSFS | Advance real retail and food services sales (millions of 1982-84 CPI-adjusted $, SA) | 114052 | — | — | — | 0 | — | — | 0 | 0 |
| 1992-04-01 | United States | USA | RRSFS | Advance real retail and food services sales (millions of 1982-84 CPI-adjusted $, SA) | 114721 | — | -0.32494895521091305 | — | 0 | — | — | 0 | 0 |
| 1992-05-01 | United States | USA | RRSFS | Advance real retail and food services sales (millions of 1982-84 CPI-adjusted $, SA) | 114868 | — | 0.011318619128464213 | — | 0 | — | — | 0 | 0 |
Download sample data
Download the full sample snapshot for this dataset (sample rows, not the complete dataset).
Use with an LLM
Point any LLM at the metadata endpoint — the documentation above is machine-readable too (JSON-LD + Croissant).
cURL
curl "https://datazimuts.com/v1/datasets/retail_sales_signals/us_retail_sales_signals" | jq '{title, rows, columns_count, license}'Python
import requests
ds = requests.get("https://datazimuts.com/v1/datasets/retail_sales_signals/us_retail_sales_signals").json()
print(ds["title"], ds["rows"], "rows")
# Sample rows for an LLM context window
for row in ds.get("sample_rows", [])[:5]:
print(row)API endpoint: https://datazimuts.com/v1/datasets/retail_sales_signals/us_retail_sales_signals
Tip: fetch /llms.txt for the full machine-readable catalog.