Retail Price Index in the United Kingdom decreased to 3.40 percent in February from 3.60 percent in January of 2025. This dataset provides - United Kingdom Retail Price Index YoY- actual values, historical data, forecast, chart, statistics, economic calendar and news.

RPI, RPI(X), RPI(Y), RPI (pensioners) and RPI (low income) percentage changes and index numbers. The latest report on the Retail Prices index is published here on gov.je.

The Consumer Prices Index (CPI) and the Retail Prices Index (RPI) measure the changes from month to month in the cost of a representative 'basket' of goods and services bought by consumers within the UK. This involves weighting together price changes in the indices according to household spending patterns for different categories of goods and services so that each takes its appropriate share. At the beginning of each year the weights used to compile both the CPI and RPI are updated using the latest available information on household spending. Source agency: Office for National Statistics Designation: National Statistics Language: English Alternative title: Updating Weights

There are a number of differences between the Consumer Prices Index (CPI) and Retail Prices Index (RPI), including their coverage, population base, commodity measurement and methods of construction. Combined, these differences have meant that, for most of its history, the CPI has been lower than the RPI. One of the main reasons to this difference is the method of construction at the lowest level, where different formulae are used in the CPI and RPI to combine individual prices. This difference is usually referred to as the formula effect. This article will investigate similar formula effects present in the inflation measures of other countries, and where necessary will attempt to explain why the magnitude of the formula effect experienced by other countries differs from that of the UK.

Source agency: Office for National Statistics

Designation: National Statistics

Language: English

Alternative title: International Comparison

Inflation Rate in the United Kingdom decreased to 2.80 percent in February from 3 percent in January of 2025. This dataset provides - United Kingdom Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Measures of monthly UK inflation data including CPIH, CPI and RPI. These tables complement the consumer price inflation time series dataset.

The Regional Price Index contrasts the cost of a common basket of goods and services at a number of regional locations to the Perth metropolitan area. The RPIs were commissioned to assist with the calculation of the Western Australian State Government’s regional district allowance, and it has been used to assist in policy decision-making. Show full description

Comprehensive database of time series covering measures of inflation data for the UK including CPIH, CPI and RPI.

Inflation Rate in Spain increased to 3 percent in February from 2.90 percent in January of 2025. This dataset provides the latest reported value for - Spain Inflation Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Inflation Rate in Italy increased to 1.60 percent in February from 1.50 percent in January of 2025. This dataset provides the latest reported value for - Italy Inflation Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Abstract copyright UK Data Service and data collection copyright owner. The Prices Survey Microdata include the underlying price data used by the Office for National Statistics (ONS) to produce the Consumer Prices Index (CPI), the Retail Prices Index (RPI) and associated price indices. The CPI has become the main domestic measure of inflation for macroeconomic purposes in the UK. Since December 2003 it has been used for the inflation target that the Bank of England is required to achieve. The RPI is the most long-standing measure of inflation in the UK, and its uses have included the indexation of pensions, state benefits and index-linked gilts. The study also includes the data underlying the Producer Prices Index. There are four levels of sampling for local price collection: locations/shopping areas; outlets/shops within locations; representative items/goods and services; and products and varieties (price quotes). There are two basic price collection methods: local and central. Local collection is used for most items; prices are obtained from outlets in about 150 locations around the country. Some 110,000 quotations are obtained by this method. Normally, collectors must visit the outlet, but prices for some items may be collected by telephone. Central collection is used for items where all the prices can be collected centrally by the ONS with no field work. These prices can be further sub-divided into two categories, depending on their subsequent use: 1) central shops, where the prices are combined with prices obtained locally, and 2) central items, where the prices are used on their own to construct centrally calculated indices. There are about 130 items for which the prices are collected centrally. The retail price data include the locations containing the shopping outlets from which the price quotes were obtained. These locations are intended to be broadly representative of a central shopping area and the areas where the local shopping population tend to live. The data also include the regions in which those shopping areas are located. Linking to other business studies The producer prices data contain Inter-Departmental Business Register (IDBR) reference numbers. These are anonymous but unique reference numbers assigned to business organisations. Their inclusion allows researchers to combine different business survey sources together. Researchers may consider applying for other business data to assist their research. Latest edition informationFor the thirty-fifth edition (May 2024), monthly Item Indices and Price Quotes data files for January to March 2024 have been added to the study. Main Topics: The Prices Survey Microdata include both retail and producer prices. The retail data include the following files:'backdata' or background information fileslocally collected filescentrally collected item filesitem indices filesprice quote filesClassification of Individual Consumption by Purpose (COICOP) level maps and weights filesThe 'backdata' background information files include:COICOP descriptions and identification codesdescriptions and identification codes for each item (goods and services)location descriptions and identification codes (and the region of the UK)shop codes for each item and locationThe pre-2007 data also include postcodes for the shops. The retail prices data span from 1996 to 2009 (centrally collected item indices), from 1996 to 2013 (annual item indices), from 1st quarter 1996 to 3rd quarter 2016 (quarterly item indices and quarterly price quote data), from October 2016 to July 2023 (monthly item indices and monthly price quote data), and from 1996 to 2013 (locally collected data). The producer prices files span from 1998 to 2021 and include:item and index number codesInter-Departmental Business Register Reporting Unit reference numbers, allowing the data to be matched to other ONS business survey dataindex descriptionsprices for each item/index numberAdditional producer prices files spanning 1996 to 2019 provide only the Producer Prices Indices and summary tables. Other

Representative items within the Consumer Prices Index including owner occupiers' housing costs, Consumer Prices Index and Retail Prices Index for the basket of goods and services.

Goodness of causal knowledge “extraction” systems are typically determined by performance over some benchmarks and although quite a few of them already (BECAUSE, SemEval) exist, they’re marred by the following problems: a) focusing mainly on common-sense reasoning tasks b) making restricting assumptions, e.g. causes and effects being word tokens, or trigger verbs etc.

This endeavor seeks to build new benchmarks for causal knowledge extraction which can address at least some limitations of the previous benchmarks, particularly geared towards risk management and event forecasting.

This dataset born of such an endeavor, which is also a result of a collaboration between the International Business Machines Corporation (IBM) and Rensselaer Polytechnic Institute (RPI), seeks to focus on event forecasting tasks and derives solely from Wikinews.

Out of all (10k+) category pages that exist on wikinews, various automated and manual filtering approaches were applied to vet them to a lesser number, then finally combined into 39 significant "event" / category pages. From all these event / category pages, the first / earliest news article is considered the source event and all the following ones are considered consequences. Various negative or non-consequences are also found, these are events which might be topically (or semantically related to original topic of source event or from related set of categories of source event / original category page) related to source event which can serve as related but eventually "non-consequences" for a given source event. Using such a dataset, one can hope to create benchmarks for event forecasting systems or even use this as a benchmark itself. Due to the volume and the sheer number of event-consequence-negative_example subsets possible, this dataset can also be used to create training and testing sets for supervised classifiers which could perform answer simple multiple choice questions geared towards event forecasting, e.g. one such task can be:

Input Event: Massive anti-government protests in Egypt continue into second day, several killed
Choices:

1. Hosni Mubarak steps down as president of Egypt

2. Bomb threat on UK–Egypt plane; diverted to Greece

3. Benin, Nigeria join African Union continental free trade bloc

4. Gaza Strip reports first swine flu cases

Answer: (1)

or it can also be a question answering task of the form (one correct + one incorrect options):

Input Event: Massive anti-government protests in Egypt continue into second day, several killed
Choices:

1. Hosni Mubarak steps down as president of Egypt

2. Bomb threat on UK–Egypt plane; diverted to Greece

Answer: (1)

Included within is the end result of mining almost all of wikinews into a small, succinct and concise dataset filled with significant events and their consequences and some non consequences. Every event, consequence and non-consequence has a number of fields, including but not limited to:

a) categories
b) category_links
c) category_name
d) content
e) date
f) title
g) url

for every wikinews article present. There may be other differing extraction specific metadata fields included as well depending on which category of article (source event, consequences, negative examples / non-consequences) is being considered. There are 39 lines / category pages in the JSONL file with the following being the complete summary for the same:

{"information": "Complete Summary", "total_consequences": 570.0, "mean_consequences": 14.615384615384615, "median_consequences": 6.0, "total_negatives": 780.0, "total_negatives_before": 390.0, "total_negatives_after": 390.0}

Please feel free to contact the following people with any questions or comments:

Oktie Hassanzadeh
hassanzadeh at us.ibm.com

Gaurav Dass
dassg2 at rpi.edu
dassgaurav93 at gmail.com

Dataset collected in an indoor industrial environment using a mobile unit (manually pushed trolley) that resembles an industrial vehicle equipped with several sensors, namely, Wi-Fi, wheel encoder (displacement), and Inertial Measurement Unit (IMU).

Sensors were connected to a Raspberry Pi (RPi 3B +), which collected the data from the sensors. Ground truth information was obtained with video camera pointed towards the floor, registering the times when the trolley passed by reference tags.

List of sensors:

• 4x Wi-Fi interfaces: Edimax EW7811-Un
• 2x IMUs: Adafruit BNO055
• 1x Absolute Encoder: US Digital A2 (attached to a wheel with a diameter of 125 mm)

This dataset includes:

• 1x Wi-Fi radio map that can be used for Wi-Fi fingerprinting.
• 6x Trajectories: including sensor data + ground truth.
• APs Information: list of APs in the building, including their position and transmission channel.
• Floor plan: image of the building's floor plan with obstacles and non-navigable areas.
• Python package provided for:
  • parsing the dataset into a data structure (Pandas dataframes).
  • performing statistical analysis on the data (number of samples, time difference between consecutive samples, etc.).
  • computing Dead Reckoning trajectory from a provided initial position.
  • computing Wi-Fi fingerprinting position estimates.
  • determining positioning error in Dead Reckoning and Wi-Fi fingerprinting.
  • generating plots including the floor plan of the building, dead reckoning trajectories, and CDFs.

When using this dataset, please cite its data description paper:

Silva , I.; Pendão, C.; Torres-Sospedra, J.; Moreira, A. Industrial Environment Multi-Sensor Dataset for Vehicle Indoor Tracking with Wi-Fi, Inertial and Odometry Data. Data 2023, 8, 157. https://doi.org/10.3390/data8100157

We present a high-resolution magnetostratigraphy and relative paleointensity (RPI) record derived from the upper 85 meters of IODP Site U1336, an equatorial Pacific early to middle Miocene succession recovered during Expedition 320/321. The magnetostratigraphy is well resolved with reversals typically located to within a few centimeters resulting in a well-constrained age model. The lowest normal polarity interval, from 85 to 74.87 meters, is interpreted as the upper part of Chron C6n (18.614-19.599 Ma). Another 33 magnetozones occur from 74.87 to 0.85 m, which are interpret to represent the continuous sequence of chrons from Chron C5Er (18.431-18.614 Ma) up to the top of Chron C5An.1n (12.014 Ma). We identify three new possible subchrons within Chron C5Cn.1n, Chron 5Bn.1r, and C5ABn. Sedimentation rates vary from about 7 to 15 m/Myr with a mean of about 10 m/Myr. We observe rapid, apparent changes in the sedimentation rate at geomagnetic reversals between ~16 and 19 Ma that indicate a calibration error in geomagnetic polarity timescale (ATNTS2004). The remanence is carried mainly by non-interacting particles of fine-grained magnetite, which have FORC distributions characteristic of biogenic magnetite. Given the relative homogeneity of the remanence carriers throughout the 85-m-thick succession and the quality with which the remanence is recorded, we have constructed a relative paleointensity (RPI) record that provides new insights into middle Miocene geomagnetic field behavior. The RPI record indicates a gradual decline in field strength between 18.5 Ma and 14.5 Ma, and indicates no discernible link between RPI and either chron duration or polarity state.

Construction Output Price Indices (OPIs) from January 2014 to December 2024, UK. Summary.

Inflation Rate in Ireland decreased to 1.80 percent in February from 1.90 percent in January of 2025. This dataset provides the latest reported value for - Ireland Inflation Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Consumer Price Index CPI in Malta increased to 120.45 points in February from 119.92 points in January of 2025. This dataset provides - Malta Consumer Price Index (CPI) - actual values, historical data, forecast, chart, statistics, economic calendar and news.

This dataset provides values for RETAIL PRICE INDEX reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

Inflation Rate in Hong Kong decreased to 1.40 percent in February from 2 percent in January of 2025. This dataset provides the latest reported value for - Hong Kong Inflation Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.