Makrognosis

United Kingdom RPI:Weights (parts per 1000) Two-person pensioner - Other clothing (ended 2016) ()

AnnualNot seasonally adjustedCode UK.RPI.A.NSA.ITEM-CCZV.MEASURE-WEIGHT

Latest8.00 parts per 10002016
Previous6.00 parts per 10002015
Year ago6.00 parts per 10002015

United Kingdom RPI:Weights (parts per 1000) Two-person pensioner - Other clothing (ended 2016) () was 8.00 parts per 1000 in 2016, up 33.3% from 2015.

That is the highest reading since 2009.

Over the past ten years it has ranged from 6.00 parts per 1000 (2010) to 9.00 parts per 1000 (2006), averaging 7.18 parts per 1000.

United Kingdom RPI:Weights (parts per 1000) Two-person pensioner - Other clothing (ended 2016) () (parts per 1000), 1992 – 20165.07.510.012.515.017.519952000200520102015Robomacro
United Kingdom RPI:Weights (parts per 1000) Two-person pensioner - Other clothing (ended 2016) () (parts per 1000), 1992 – 2016. Source: UK Office for National Statistics.

Showing the full history (downsampled for display). Open the interactive chart to zoom and switch transforms.

Recent data

PeriodValue
20168.00 parts per 1000
20156.00 parts per 1000
20146.00 parts per 1000
20136.00 parts per 1000
20126.00 parts per 1000
20116.00 parts per 1000
20106.00 parts per 1000
20098.00 parts per 1000
20089.00 parts per 1000
20079.00 parts per 1000
20069.00 parts per 1000
20059.00 parts per 1000
200410.00 parts per 1000
200311.00 parts per 1000
200212.00 parts per 1000
200113.00 parts per 1000
200011.00 parts per 1000
199910.00 parts per 1000
199812.00 parts per 1000
199714.00 parts per 1000
199615.00 parts per 1000
199514.00 parts per 1000
199416.00 parts per 1000
199316.00 parts per 1000

Last 24 observations. The full history (25 observations) is available through the API.

Get United Kingdom RPI:Weights (parts per 1000) Two-person pensioner - Other clothing (ended 2016) () in your code or spreadsheet

One guessable code, agency-direct, updated on release. Free tier available.

curl -H "X-API-Key: $MAKROGNOSIS_KEY" \
  "https://makrognosis.robomacro.com/v1/series/UK.RPI.A.NSA.ITEM-CCZV.MEASURE-WEIGHT"

# Python
import requests
r = requests.get("https://makrognosis.robomacro.com/v1/series/UK.RPI.A.NSA.ITEM-CCZV.MEASURE-WEIGHT",
                 headers={"X-API-Key": KEY})
obs = r.json()["observations"]
Get a free API key → · API docs

About this series

Latest observation2016
First observation1992
Observations25
FrequencyAnnual
Unitsparts per 1000
AdjustmentNot seasonally adjusted
10-year high9.00 parts per 1000 (2006)
10-year low6.00 parts per 1000 (2010)
10-year average7.18 parts per 1000
Source agencyUK Office for National Statistics
Makrognosis codeUK.RPI.A.NSA.ITEM-CCZV.MEASURE-WEIGHT

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Other United Kingdom indicators

United Kingdom GDP (Gross Domestic Product)United Kingdom Nominal GDP (current prices)United Kingdom Inflation Rate (CPI)United Kingdom Core Inflation RateUnited Kingdom Unemployment RateUnited Kingdom Credit Rating & Sovereign Risk ScoreUnited Kingdom Industrial ProductionUnited Kingdom Production Industries - Total (Index 1dp): CVM SAUnited Kingdom Retail SalesUnited Kingdom Producer Price Inflation (PPI)United Kingdom BoP Current Account Balance SAUnited Kingdom Trade Balance: Goods & ServicesUnited Kingdom Total Trade (TT): WW: Exports: BOP: CP: SA (goods + services)United Kingdom Total Trade: World: Exports: BOP: CVM SAUnited Kingdom Total Trade (TT): WW: Imports: BOP: CP: SA (goods + services)United Kingdom Total Trade: World: Imports: BOP: CVM SA

FAQ

What is the current rPI:Weights (parts per 1000) Two-person pensioner - Other clothing (ended 2016) () in United Kingdom?
The latest reading is 8.00 parts per 1000 for 2016, published by UK Office for National Statistics.
Where does this data come from?
It is collected directly from UK Office for National Statistics and is available through the Makrognosis API under the code UK.RPI.A.NSA.ITEM-CCZV.MEASURE-WEIGHT.

Last updated 2026-07-20. Source: UK Office for National Statistics. Original title: “RPI:Weights (parts per 1000) Two-person pensioner - Other clothing (ended 2016) (UK)”.