100+ datasets found
  1. d

    Consumer Price Index

    • data.dathere.com
    • data-dathere.dataops.dathere.com
    csv
    Updated Feb 21, 2025
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    datHere (2025). Consumer Price Index [Dataset]. https://data.dathere.com/dataset/consumer-price-index
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    csv(20013), csv(817028), csv(924008)Available download formats
    Dataset updated
    Feb 21, 2025
    Dataset authored and provided by
    datHere
    Description

    The Consumer Price Index (CPI) is a measure of the average change over time in the prices paid by urban consumers for a market basket of consumer goods and services. Indexes are available for the U.S. and various geographic areas. Average price data for select utility, automotive fuel, and food items are also available. Prices for the goods and services used to calculate the CPI are collected in 75 urban areas throughout the country and from about 23,000 retail and service establishments. Data on rents are collected from about 43,000 landlords or tenants.

  2. A

    ‘🚊 Consumer Price Index’ analyzed by Analyst-2

    • analyst-2.ai
    Updated Aug 28, 2013
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2013). ‘🚊 Consumer Price Index’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/kaggle-consumer-price-index-ba9d/latest
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    Dataset updated
    Aug 28, 2013
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Analysis of ‘🚊 Consumer Price Index’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/yamqwe/consumer-price-indexe on 13 February 2022.

    --- Dataset description provided by original source is as follows ---

    About this dataset

    9The Consumer Price Index for All Urban Consumers: All Items (CPIAUCSL) is a measure of the average monthly change in the price for goods and services paid by urban consumers between any two time periods.(1) It can also represent the buying habits of urban consumers. This particular index includes roughly 88 percent of the total population, accounting for wage earners, clerical workers, technical workers, self-employed, short-term workers, unemployed, retirees, and those not in the labor force.(1)

    The CPIs are based on prices for food, clothing, shelter, and fuels; transportation fares; service fees (e.g., water and sewer service); and sales taxes. Prices are collected monthly from about 4,000 housing units and approximately 26,000 retail establishments across 87 urban areas.(1) To calculate the index, price changes are averaged with weights representing their importance in the spending of the particular group. The index measures price changes (as a percent change) from a predetermined reference date.(1) In addition to the original unadjusted index distributed, the Bureau of Labor Statistics also releases a seasonally adjusted index. The unadjusted series reflects all factors that may influence a change in prices. However, it can be very useful to look at the seasonally adjusted CPI, which removes the effects of seasonal changes, such as weather, school year, production cycles, and holidays.(1)

    The CPI can be used to recognize periods of inflation and deflation. Significant increases in the CPI within a short time frame might indicate a period of inflation, and significant decreases in CPI within a short time frame might indicate a period of deflation. However, because the CPI includes volatile food and oil prices, it might not be a reliable measure of inflationary and deflationary periods. For a more accurate detection, the core CPI (Consumer Price Index for All Urban Consumers: All Items Less Food & Energy [CPILFESL]) is often used. When using the CPI, please note that it is not applicable to all consumers and should not be used to determine relative living costs.(1) Additionally, the CPI is a statistical measure vulnerable to sampling error since it is based on a sample of prices and not the complete average.(1)

    Attribution: US. Bureau of Labor Statistics from The Federal Reserve Bank of St. Louis

    For more information on the consumer price indexes, see:

    This dataset was created by Finance and contains around 900 samples along with Consumer Price Index For All Urban Consumers: All Items, Title:, technical information and other features such as: - Consumer Price Index For All Urban Consumers: All Items - Title: - and more.

    How to use this dataset

    • Analyze Consumer Price Index For All Urban Consumers: All Items in relation to Title:
    • Study the influence of Consumer Price Index For All Urban Consumers: All Items on Title:
    • More datasets

    Acknowledgements

    If you use this dataset in your research, please credit Finance

    Start A New Notebook!

    --- Original source retains full ownership of the source dataset ---

  3. T

    United States Consumer Price Index (CPI)

    • tradingeconomics.com
    • fa.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Jun 11, 2025
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    TRADING ECONOMICS (2025). United States Consumer Price Index (CPI) [Dataset]. https://tradingeconomics.com/united-states/consumer-price-index-cpi
    Explore at:
    xml, csv, excel, jsonAvailable download formats
    Dataset updated
    Jun 11, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 31, 1950 - May 31, 2025
    Area covered
    United States
    Description

    Consumer Price Index CPI in the United States increased to 321.47 points in May from 320.80 points in April of 2025. This dataset provides the latest reported value for - United States Consumer Price Index (CPI) - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

  4. w

    Consumer Price Indices

    • data360.worldbank.org
    Updated Aug 18, 2020
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    (2020). Consumer Price Indices [Dataset]. https://data360.worldbank.org/en/dataset/FAO_CP
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    Dataset updated
    Aug 18, 2020
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    2000 - 2024
    Description

    The FAOSTAT monthly Food CPI and General CPI database was based on the ILO CPI data until December 2014. In 2014, IMF-ILO-FAO agreed to transfer global CPI data compilation from ILO to IMF. Upon agreement, CPIs for all items and its sub components originates from the International Monetary Fund (IMF), and the UN Statistics Division(UNSD) for countries not covered by the IMF. However, due to a limited time coverage from IMF and UNSD for a number of countries, the Organisation for Economic Co-operation and Development (OECD), Central Bank of Western African States (BCEAO), Eastern Caribbean Central Bank (ECCB), UNdata, United Nations Conference on Trade and Development (UNCTAD) and national statistical office website data are used for missing historical data from IMF and UNSD food CPI.

    The FAO CPI dataset for all items(or general CPI) and the Food CPI, consists of a complete and consistent set of time series from January 2000 onwards. Data gaps on monthly Food CPI and General CPI are filled using statistical estimation procedures to have full data coverage for all countries for Food CPI and for General CPI. These indices measure the price change between the current and reference periods of the average basket of goods and services purchased by households. The General CPI is typically used to measure and monitor inflation, set monetary policy targets, index social benefits such as pensions and unemployment benefits, and to escalate thresholds and credits in the income tax systems and wages in public and private wage contracts. The FAOSTAT monthly Food CPI inflation rates are annual year-over-year inflation or percentage change over corresponding month of the previous year.

    The data included in Data360 is a subset of the data available from the source. Please refer to the source for complete data and methodology details.

    This collection includes only a subset of indicators from the source dataset.

  5. Consumer prices; price index 2006 = 100, 1996 - 2015

    • data.overheid.nl
    • cloud.csiss.gmu.edu
    • +2more
    atom, json
    Updated Nov 2, 2016
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    Centraal Bureau voor de Statistiek (Rijk) (2016). Consumer prices; price index 2006 = 100, 1996 - 2015 [Dataset]. https://data.overheid.nl/dataset/4836-consumer-prices--price-index-2006---100--1996---2015
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    atom(KB), json(KB)Available download formats
    Dataset updated
    Nov 2, 2016
    Dataset provided by
    Statistics Netherlands
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    The Consumer price index (CPI) all households, calculated by Statistics Netherlands, measures the average price changes of goods and services purchased by households. The index is an important criterion for inflation, frequently used by trade and industry, employers' organisations, trade unions and government. The index is for instance, used to make adjustments to wages, tax tablesand index-linked rent increases, annuities, etc.

    Data available from: January 1996 till December 2015

    Status of the figures: The figures in this table are final.

    Changes as of 18 May 2016: None, this table is stopped.

    Changes from 7 January 2016: New figures added.

    Changes from 10 December 2015: On 1 October 2015, the points system for the pricing of rental homes was adjusted by the Dutch national government. As a direct consequence, rental prices of a limited number of dwellings were reduced, which had a downward effect on the average rental price. The effect of this decrease on the rental price indices and imputed rent value could not be determined in time because housing associations announced the impact of rent adjustments only in November. For this reason, the figures of the groups 04100 ‘Actual rentals for housing’ and 04200 ‘Imputed rent value’ over October 2015 have now been adjusted.

    The figures of the groups 061100 ‘Pharmaceutical products’, 061200 ‘Other medical products, equipment’, 072200 ‘Fuels and lubricants’ and 083000 ‘Telephone and internet services’ over the months June through September 2015 have been corrected. This has no impact on the headline indices.

    The derived CPI decreased by 0.01 index point over August 2015.

    When will new figures be published? Not applicable. This table is succeeded by Consumer prices; price index 2015=100. See paragraph 3.

  6. e

    Quarterly price indices of consumer goods and services from 1995

    • data.europa.eu
    html
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    Główny Urząd Statystyczny, Quarterly price indices of consumer goods and services from 1995 [Dataset]. https://data.europa.eu/data/datasets/https-dane-gov-pl-pl-dataset-2053-kwartalne-wskazniki-cen-towarow-i-uslug-konsumpcyj?locale=it
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    html(0)Available download formats
    Dataset authored and provided by
    Główny Urząd Statystyczny
    Description

    Price index of consumer goods and services is calculated on the basis of the results of:
    - surveys on prices of consumer goods and services on the retail market,
    - surveys on household budgets, providing data on average expenditures on consumer goods and services; these data are then used for compilation of a weight system.

    Calculating price index of consumer goods and services is done on the basis of the Classification of Individual Consumption by Purpose (COICOP) adapted for the use of Harmonized Indices of Consumer Prices (HICP).

    The price index of a representative in the region included in the price survey results from relating its average monthly price to an average annual price from the previous yea The all-Polish price index of a representative included in the survey is calculated as geometric mean of price indices from all regions. Calculating price indices of groups of consumer goods and services at the lowest level of weight system aggregation is done on the basis of price indices of the representatives included in price survey in a given group by using geometric mean. They are then used by applying weight system to calculate indices of higher level of aggregation up to the price index of total consumer goods and services. price index is calculated in line with the Laspeyress’s formula by applying weights from the year preceding the reference year.

  7. k

    Consumer Price Index By Commodities

    • data.kapsarc.org
    • datasource.kapsarc.org
    Updated May 27, 2025
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    (2025). Consumer Price Index By Commodities [Dataset]. https://data.kapsarc.org/explore/dataset/consumer-price-index0/?flg=ar-001
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    Dataset updated
    May 27, 2025
    Description

    Explore the Consumer Price Index dataset for Kuwait, covering categories such as HOUSING SERVICES, CLOTHING, RESTAURANT, HOTELS, TOBACCO, and more on a quarterly and monthly basis. Find valuable insights on cost of living, commodities, and price trends.

    HOUSEING SERVICES, CLOTHING and FOOTWEAR, RESTAURANT and HOTELS, TOBACCO and NARCOTICS, Quarterly, COMMUNICATION, FURNISHING EQUIPMENT HOUSEHOLD MAINTENANCE, Number, ALL ITEMS CONSUMPTION PRICE INDEX, SERVICES and MISCELLANEOUS GOODS, EDUCATION, % Monthly Change, Monthly, Annually, RECREATION andCULTURE, % Annual Change, TOTAL INDEX LESS FOOD, FOOD and BEVERAGES, % Quarterly Change, TOTAL INDEX LESS HOUSEING SERVICES, HEALTH, TRANSPORT, CPI, Cost of living, Commodities, Food, TOBACCO, Price

    KuwaitFollow data.kapsarc.org for timely data to advance energy economics research..All Copyright Reserved © 2013 Kuwait Central Statistical Bureau.

  8. Consumer price inflation consumption segment indices and price quotes

    • ons.gov.uk
    • cy.ons.gov.uk
    csv
    Updated Jun 18, 2025
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    Office for National Statistics (2025). Consumer price inflation consumption segment indices and price quotes [Dataset]. https://www.ons.gov.uk/economy/inflationandpriceindices/datasets/consumerpriceindicescpiandretailpricesindexrpiitemindicesandpricequotes
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    csvAvailable download formats
    Dataset updated
    Jun 18, 2025
    Dataset provided by
    Office for National Statisticshttp://www.ons.gov.uk/
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Description

    Price quote data (for locally collected data only) and consumption segment indices that underpin consumer price inflation statistics, giving users access to the detailed data that are used in the construction of the UK’s inflation figures. The data are being made available for research purposes only and are not an accredited official statistic. From October 2024, private school fees and part-time education classes have been included in the consumption segment indices file. For more information on the introduction of consumption segments, please see the Consumer Prices Indices Technical Manual, 2019. Note that this dataset was previously called the consumer price inflation item indices and price quotes dataset.

  9. d

    Western Australia Regional Price Index - Datasets - data.wa.gov.au

    • catalogue.data.wa.gov.au
    + more versions
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    Western Australia Regional Price Index - Datasets - data.wa.gov.au [Dataset]. https://catalogue.data.wa.gov.au/dataset/regional-price-index-western-australia
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    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Western Australia, Australia
    Description

    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

  10. d

    All-Transactions House Price Index for Connecticut

    • catalog.data.gov
    • fred.stlouisfed.org
    • +1more
    Updated Jul 12, 2025
    + more versions
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    data.ct.gov (2025). All-Transactions House Price Index for Connecticut [Dataset]. https://catalog.data.gov/dataset/all-transactions-house-price-index-for-connecticut
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    Dataset updated
    Jul 12, 2025
    Dataset provided by
    data.ct.gov
    Area covered
    Connecticut
    Description

    The FHFA House Price Index (FHFA HPI®) is the nation’s only collection of public, freely available house price indexes that measure changes in single-family home values based on data from all 50 states and over 400 American cities that extend back to the mid-1970s. The FHFA HPI incorporates tens of millions of home sales and offers insights about house price fluctuations at the national, census division, state, metro area, county, ZIP code, and census tract levels. FHFA uses a fully transparent methodology based upon a weighted, repeat-sales statistical technique to analyze house price transaction data. ​ What does the FHFA HPI represent? The FHFA HPI is a broad measure of the movement of single-family house prices. The FHFA HPI is a weighted, repeat-sales index, meaning that it measures average price changes in repeat sales or refinancings on the same properties. This information is obtained by reviewing repeat mortgage transactions on single-family properties whose mortgages have been purchased or securitized by Fannie Mae or Freddie Mac since January 1975. The FHFA HPI serves as a timely, accurate indicator of house price trends at various geographic levels. Because of the breadth of the sample, it provides more information than is available in other house price indexes. It also provides housing economists with an improved analytical tool that is useful for estimating changes in the rates of mortgage defaults, prepayments and housing affordability in specific geographic areas. U.S. Federal Housing Finance Agency, All-Transactions House Price Index for Connecticut [CTSTHPI], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/CTSTHPI, August 2, 2023.

  11. C

    Consumer prices; price index frequent purchases, 2006=100, 2006 - 2015

    • ckan.mobidatalab.eu
    • data.overheid.nl
    • +2more
    Updated Jul 13, 2023
    + more versions
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    OverheidNl (2023). Consumer prices; price index frequent purchases, 2006=100, 2006 - 2015 [Dataset]. https://ckan.mobidatalab.eu/dataset/4837-consumer-prices-price-index-frequent-purchases-2006-100-2006-2015
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    http://publications.europa.eu/resource/authority/file-type/atom, http://publications.europa.eu/resource/authority/file-type/jsonAvailable download formats
    Dataset updated
    Jul 13, 2023
    Dataset provided by
    OverheidNl
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This table shows the consumer price index for all households (CPI), split up into an index for frequent "out-of-pocket" purchases (FROOPP) and less frequent or "non-out-of-pocket" purchased items (non-FROOPP). Frequent purchased items are purchases that are typically done at least monthly. Out-of-pocket purchases are those that are considered to be typically paid for by the consumer directly and actively. This table also includes the monthly and yearly price developments. The FROOPP and non-FROOPP are special extracts of the CPI. The corresponding CPI weights and prices are used to calculate both indices. The segmentation used is derived from the FROOPP-classification of Eurostat. Data available from: January 2006 till December 2015 Status of the figures: The figures in this table are final. Changes as of 18 May 2016 None, this table is stopped. Changes as of 10 December 2015 On 1 October 2015, the points system for the pricing of rental homes was adjusted by the Dutch national government. As a direct consequence, rental prices of a limited number of dwellings were reduced, which had a downward effect on the average rental price. The effect of this decrease on the rental price indices and imputed rent value could not be determined in time because housing associations announced the impact of rent adjustments only in November. For this reason, the figures of the groups 04100 ‘Actual rentals for housing’ and 04200 ‘Imputed rent value’ over October 2015 have now been adjusted. The figures of the groups 061100 ‘Pharmaceutical products’, 061200 ‘Other medical products, equipment’, 072200 ‘Fuels and lubricants’ and 083000 ‘Telephone and internet services’ over the months June through September 2015 have been corrected. This has no impact on the headline indices. When will new figures be published? Not applicable.

  12. T

    CONSUMER PRICE INDEX CPI by Country Dataset

    • tradingeconomics.com
    csv, excel, json, xml
    Updated May 26, 2017
    + more versions
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    TRADING ECONOMICS (2017). CONSUMER PRICE INDEX CPI by Country Dataset [Dataset]. https://tradingeconomics.com/country-list/consumer-price-index-cpi
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    excel, csv, xml, jsonAvailable download formats
    Dataset updated
    May 26, 2017
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    2025
    Area covered
    World
    Description

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

  13. o

    NI House Price Index - Dataset - Open Data NI

    • admin.opendatani.gov.uk
    Updated Nov 18, 2015
    + more versions
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    (2015). NI House Price Index - Dataset - Open Data NI [Dataset]. https://admin.opendatani.gov.uk/dataset/nihpi-by-propertytype
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    Dataset updated
    Nov 18, 2015
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Area covered
    Northern Ireland
    Description

    A quarterly index providing a measure of change in the price of a standardised residential property sold in NI. The index is presented for each quarter from Q1 (January-March) 2005.

  14. s

    House price index (2015 = 100) - quarterly data - Datasets - This service...

    • store.smartdatahub.io
    Updated Aug 3, 2019
    + more versions
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    (2019). House price index (2015 = 100) - quarterly data - Datasets - This service has been deprecated - please visit https://www.smartdatahub.io/ to access data. See the About page for details. // [Dataset]. https://store.smartdatahub.io/dataset/fi_statistics_finland_teicp270_px
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    Dataset updated
    Aug 3, 2019
    Description

    House price index (2015 = 100) - quarterly data

  15. Consumer Price Index 2020 - West Bank and Gaza

    • pcbs.gov.ps
    Updated Jan 2, 2022
    + more versions
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    Palestinian Central Bureau of Statistics (2022). Consumer Price Index 2020 - West Bank and Gaza [Dataset]. https://www.pcbs.gov.ps/PCBS-Metadata-en-v5.2/index.php/catalog/706
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    Dataset updated
    Jan 2, 2022
    Dataset authored and provided by
    Palestinian Central Bureau of Statisticshttp://pcbs.gov.ps/
    Time period covered
    2020
    Area covered
    West Bank, Palestine
    Description

    Abstract

    The Consumer price surveys primarily provide the following: Data on CPI in Palestine covering the West Bank, Gaza Strip and Jerusalem J1 for major and sub groups of expenditure. Statistics needed for decision-makers, planners and those who are interested in the national economy. Contribution to the preparation of quarterly and annual national accounts data.

    Consumer Prices and indices are used for a wide range of purposes, the most important of which are as follows: Adjustment of wages, government subsidies and social security benefits to compensate in part or in full for the changes in living costs. To provide an index to measure the price inflation of the entire household sector, which is used to eliminate the inflation impact of the components of the final consumption expenditure of households in national accounts and to dispose of the impact of price changes from income and national groups. Price index numbers are widely used to measure inflation rates and economic recession. Price indices are used by the public as a guide for the family with regard to its budget and its constituent items. Price indices are used to monitor changes in the prices of the goods traded in the market and the consequent position of price trends, market conditions and living costs. However, the price index does not reflect other factors affecting the cost of living, e.g. the quality and quantity of purchased goods. Therefore, it is only one of many indicators used to assess living costs. It is used as a direct method to identify the purchasing power of money, where the purchasing power of money is inversely proportional to the price index.

    Geographic coverage

    Palestine West Bank Gaza Strip Jerusalem

    Analysis unit

    The target population for the CPI survey is the shops and retail markets such as grocery stores, supermarkets, clothing shops, restaurants, public service institutions, private schools and doctors.

    Universe

    The target population for the CPI survey is the shops and retail markets such as grocery stores, supermarkets, clothing shops, restaurants, public service institutions, private schools and doctors.

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    A non-probability purposive sample of sources from which the prices of different goods and services are collected was updated based on the establishment census 2017, in a manner that achieves full coverage of all goods and services that fall within the Palestinian consumer system. These sources were selected based on the availability of the goods within them. It is worth mentioning that the sample of sources was selected from the main cities inside Palestine: Jenin, Tulkarm, Nablus, Qalqiliya, Ramallah, Al-Bireh, Jericho, Jerusalem, Bethlehem, Hebron, Gaza, Jabalia, Dier Al-Balah, Nusseirat, Khan Yunis and Rafah. The selection of these sources was considered to be representative of the variation that can occur in the prices collected from the various sources. The number of goods and services included in the CPI is approximately 730 commodities, whose prices were collected from 3,200 sources. (COICOP) classification is used for consumer data as recommended by the United Nations System of National Accounts (SNA-2008).

    Sampling deviation

    Not apply

    Mode of data collection

    Computer Assisted Personal Interview [capi]

    Research instrument

    A tablet-supported electronic form was designed for price surveys to be used by the field teams in collecting data from different governorates, with the exception of Jerusalem J1. The electronic form is supported with GIS, and GPS mapping technique that allow the field workers to locate the outlets exactly on the map and the administrative staff to manage the field remotely. The electronic questionnaire is divided into a number of screens, namely: First screen: shows the metadata for the data source, governorate name, governorate code, source code, source name, full source address, and phone number. Second screen: shows the source interview result, which is either completed, temporarily paused or permanently closed. It also shows the change activity as incomplete or rejected with the explanation for the reason of rejection. Third screen: shows the item code, item name, item unit, item price, product availability, and reason for unavailability. Fourth screen: checks the price data of the related source and verifies their validity through the auditing rules, which was designed specifically for the price programs. Fifth screen: saves and sends data through (VPN-Connection) and (WI-FI technology).

    In case of the Jerusalem J1 Governorate, a paper form has been designed to collect the price data so that the form in the top part contains the metadata of the data source and in the lower section contains the price data for the source collected. After that, the data are entered into the price program database.

    Cleaning operations

    The price survey forms were already encoded by the project management depending on the specific international statistical classification of each survey. After the researcher collected the price data and sent them electronically, the data was reviewed and audited by the project management. Achievement reports were reviewed on a daily and weekly basis. Also, the detailed price reports at data source levels were checked and reviewed on a daily basis by the project management. If there were any notes, the researcher was consulted in order to verify the data and call the owner in order to correct or confirm the information.

    At the end of the data collection process in all governorates, the data will be edited using the following process: Logical revision of prices by comparing the prices of goods and services with others from different sources and other governorates. Whenever a mistake is detected, it should be returned to the field for correction. Mathematical revision of the average prices for items in governorates and the general average in all governorates. Field revision of prices through selecting a sample of the prices collected from the items.

    Response rate

    Not apply

    Sampling error estimates

    The findings of the survey may be affected by sampling errors due to the use of samples in conducting the survey rather than total enumeration of the units of the target population, which increases the chances of variances between the actual values we expect to obtain from the data if we had conducted the survey using total enumeration. The computation of differences between the most important key goods showed that the variation of these goods differs due to the specialty of each survey. For example, for the CPI, the variation between its goods was very low, except in some cases such as banana, tomato, and cucumber goods that had a high coefficient of variation during 2019 due to the high oscillation in their prices. The variance of the key goods in the computed and disseminated CPI survey that was carried out on the Palestine level was for reasons related to sample design and variance calculation of different indicators since there was a difficulty in the dissemination of results by governorates due to lack of weights. Non-sampling errors are probable at all stages of data collection or data entry. Non-sampling errors include: Non-response errors: the selected sources demonstrated a significant cooperation with interviewers; so, there wasn't any case of non-response reported during 2019. Response errors (respondent), interviewing errors (interviewer), and data entry errors: to avoid these types of errors and reduce their effect to a minimum, project managers adopted a number of procedures, including the following: More than one visit was made to every source to explain the objectives of the survey and emphasize the confidentiality of the data. The visits to data sources contributed to empowering relations, cooperation, and the verification of data accuracy. Interviewer errors: a number of procedures were taken to ensure data accuracy throughout the process of field data compilation: Interviewers were selected based on educational qualification, competence, and assessment. Interviewers were trained theoretically and practically on the questionnaire. Meetings were held to remind interviewers of instructions. In addition, explanatory notes were supplied with the surveys. A number of procedures were taken to verify data quality and consistency and ensure data accuracy for the data collected by a questioner throughout processing and data entry (knowing that data collected through paper questionnaires did not exceed 5%): Data entry staff was selected from among specialists in computer programming and were fully trained on the entry programs. Data verification was carried out for 10% of the entered questionnaires to ensure that data entry staff had entered data correctly and in accordance with the provisions of the questionnaire. The result of the verification was consistent with the original data to a degree of 100%. The files of the entered data were received, examined, and reviewed by project managers before findings were extracted. Project managers carried out many checks on data logic and coherence, such as comparing the data of the current month with that of the previous month, and comparing the data of sources and between governorates. Data collected by tablet devices were checked for consistency and accuracy by applying rules at item level to be checked.

    Data appraisal

    Other technical procedures to improve data quality: Seasonal adjustment processes

  16. CPI Consumer Price Index (1913 Jan - 2021 Jun)

    • kaggle.com
    Updated Aug 4, 2021
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    JS (2021). CPI Consumer Price Index (1913 Jan - 2021 Jun) [Dataset]. https://www.kaggle.com/joseserrat/cpi-consumer-price-index-1913-jan-2021-jun/metadata
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Aug 4, 2021
    Dataset provided by
    Kaggle
    Authors
    JS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Context

    I'm creating a new website (centralbankanalytics.com) in which I need this type of data. I didn't found it easily available as I had to scrape it from an interactive graph, so now I upload it here for everyone.

    Content

    The Consumer Price Index (CPI) is a measure of the average change over time in the prices paid by urban consumers for a market basket of consumer goods and services. Indexes are available for the U.S. and various geographic areas.

  17. e

    Services producer price index (SPPI); index 2015=100, 2002-2023

    • data.europa.eu
    • cbs.nl
    • +1more
    atom feed, json
    + more versions
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    Services producer price index (SPPI); index 2015=100, 2002-2023 [Dataset]. https://data.europa.eu/data/datasets/4209-services-producer-price-index-sppi-index-2015-100
    Explore at:
    json, atom feedAvailable download formats
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This table shows the price indices, quarterly and yearly changes in prices of services that companies provide. The figures are broken down by type of services according to the Classification of Products by Activity (CPA 2008). For some services, a further breakdown has been made on the basis of market data that differ from the CPA. This breakdown is indicated with a letter after the CPA code.

    The base year for all Services producer price indices is 2015. The year average, quarterly and yearly changes are calculated with unrounded figures.

    Data available from: 4th quarter 2002 up to and including 2023.

    Status of the figures: The figures in this table are final.

    Changes as of May 17 2024: None, this table is stopped.

    When will new figures be published? Not applicable anymore. This table was discontinued on May 17, 2024 and continued as Services producer price index (SPPI); index 2021=100. See paragraph 3.

    The Services producer price indices publication schedule can be downloaded as an Excel file under section: 3 relevant articles. More information about the pricing method can be found in the video under section: 3 relevant articles.

  18. A

    ‘Home Price Index’ analyzed by Analyst-2

    • analyst-2.ai
    Updated Jan 28, 2022
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2022). ‘Home Price Index’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/kaggle-home-price-index-edf4/latest
    Explore at:
    Dataset updated
    Jan 28, 2022
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Analysis of ‘Home Price Index’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/PythonforSASUsers/hpindex on 28 January 2022.

    --- Dataset description provided by original source is as follows ---

    Context

    The Federal Housing Finance Agency House Price Index (HPI) is a broad measure of the movement of single-family house prices. The HPI is a weighted, repeat-sales index, meaning that it measures average price changes in repeat sales or refinancings on the same properties. The technical methodology for devising the index, collection, and publishing the data is at: http://www.fhfa.gov/PolicyProgramsResearch/Research/PaperDocuments/1996-03_HPI_TechDescription_N508.pdf

    Content

    Contains monthly and quarterly time series from January 1991 to August 2016 for the U.S., state, and MSA categories. Analysis variables are the aggregate non-seasonally adjusted value and seasonally adjusted index values. The index value is 100 beginning January 1991.

    Acknowledgements

    This data is found on Data.gov

    Inspiration

    Can this data be combined with the corresponding census growth projections either at the state or MSA level to forecast 24 months out the highest and lowest home index values?

    --- Original source retains full ownership of the source dataset ---

  19. T

    Germany Consumer Price Index (CPI)

    • tradingeconomics.com
    • pl.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Mar 12, 2024
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    TRADING ECONOMICS (2024). Germany Consumer Price Index (CPI) [Dataset]. https://tradingeconomics.com/germany/consumer-price-index-cpi
    Explore at:
    xml, excel, json, csvAvailable download formats
    Dataset updated
    Mar 12, 2024
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 31, 1950 - May 31, 2025
    Area covered
    Germany
    Description

    Consumer Price Index CPI in Germany increased to 121.80 points in May from 121.70 points in April of 2025. This dataset provides the latest reported value for - Germany Consumer Price Index (CPI) - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

  20. Producer price inflation time series (MM22)

    • ons.gov.uk
    • cy.ons.gov.uk
    csdb, csv, xlsx
    Updated Feb 19, 2025
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    Office for National Statistics (2025). Producer price inflation time series (MM22) [Dataset]. https://www.ons.gov.uk/economy/inflationandpriceindices/datasets/producerpriceindex
    Explore at:
    csv, xlsx, csdbAvailable download formats
    Dataset updated
    Feb 19, 2025
    Dataset provided by
    Office for National Statisticshttp://www.ons.gov.uk/
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Description

    Producer Price Indices (PPIs) are a series of economic indicators that measure the price movement of goods bought and sold by UK manufacturers.

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datHere (2025). Consumer Price Index [Dataset]. https://data.dathere.com/dataset/consumer-price-index

Consumer Price Index

Explore at:
csv(20013), csv(817028), csv(924008)Available download formats
Dataset updated
Feb 21, 2025
Dataset authored and provided by
datHere
Description

The Consumer Price Index (CPI) is a measure of the average change over time in the prices paid by urban consumers for a market basket of consumer goods and services. Indexes are available for the U.S. and various geographic areas. Average price data for select utility, automotive fuel, and food items are also available. Prices for the goods and services used to calculate the CPI are collected in 75 urban areas throughout the country and from about 23,000 retail and service establishments. Data on rents are collected from about 43,000 landlords or tenants.

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