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Great Britain retail sales: chained volume index (monthly)

Retail sales index for Great Britain — chained volume of retail sales, all retailing including automotive fuel, seasonally adjusted, monthly. Office for National Statistics.

Source: Office for National Statistics457 rowsUpdated: 9/21/2026
retailconsumerspendinguk

Quality

98.4

Attribution

Office for National Statistics

Schema

ColumnTypeDescription
datestringObservation period from the ONS API Time dimension (code list mmm-yy, e.g. 'Jan-24'), stored as the first day of the month.
series_idstringONS API dimension option code identifying the series (e.g. 'CP00' for the CPIH overall index).
series_labelstringSeries label published by the ONS for the dimension option code (e.g. 'Overall Index').
valuefloatObservation value returned by the ONS API. Units are 2019=100. (unit: 2019=100)

Sample rows

dateseries_idseries_labelvalue
1988-01-01chained-volume-of-retail-salesChained volume of retail sales
1988-02-01chained-volume-of-retail-salesChained volume of retail sales
1988-03-01chained-volume-of-retail-salesChained volume of retail sales
1988-04-01chained-volume-of-retail-salesChained volume of retail sales
1988-05-01chained-volume-of-retail-salesChained volume of retail sales

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/ons/ons_retail_sales" | jq '{title, rows, columns_count, license}'

Python

import requests

ds = requests.get("https://datazimuts.com/v1/datasets/ons/ons_retail_sales").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/ons/ons_retail_sales

Tip: fetch /llms.txt for the full machine-readable catalog.