100+ datasets found
  1. 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.

  2. d

    Consumer Price Index (CPI), index numbers for main groups, urban and rural,...

    • archive.data.gov.my
    Updated Mar 14, 2021
    + more versions
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    (2021). Consumer Price Index (CPI), index numbers for main groups, urban and rural, Malaysia (Monthly) - Dataset - MAMPU [Dataset]. https://archive.data.gov.my/data/dataset/consumer-price-index-cpi-index-numbers-for-main-groups-urban-and-rural-malaysia-monthly
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    Dataset updated
    Mar 14, 2021
    License

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

    Area covered
    Malaysia
    Description

    This dataset shows the Consumer Price Index (2010=100), Index Numbers For Main Groups, Urban and Rural, 2017- 2023 (Jan-Jul) Malaysia (Monthly) Footnote Weight: Main Groups Weight Urban Total 100.0 Food and Non- Alcoholic Beverages 28.4 Alcoholic Beverages and Tobacco 2.3 Clothing and Footware 3.2 Housing, Water, Electricity, Gas and Other Fuels 24.5 Furnishings, Households Equipment and Routine Household Maintenance 4.2 Health 1.8 Transport 14.6 Communication 4.9 Recreation Services and Culture 5.0 Education 1.4 Restaurants and Hotels 3.0 Miscellaneous Goods and Services 6.7 Weight Rural Total 100.0 Food and Non- Alcoholic Beverages 35.6 Alcoholic Beverages and Tobacco 3.0 Clothing and Footware 3.6 Housing, Water, Electricity, Gas and Other Fuels 19.9 Furnishings, Households Equipment and Routine Household Maintenance 3.7 Health 2.0 Transport 14.6 Communication 4.4 Recreation Services and Culture 3.6 Education 0.9 Restaurants and Hotels 2.4 Miscellaneous Goods and Services 6.3 Source : Department of Statistics, Malaysia No. of Views : 455

  3. Consumer Price Index (CPI)

    • catalog.data.gov
    • cloud.csiss.gmu.edu
    • +1more
    Updated May 16, 2022
    + more versions
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    Bureau of Labor Statistics (2022). Consumer Price Index (CPI) [Dataset]. https://catalog.data.gov/dataset/consumer-price-index-cpi-ee18b
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    Dataset updated
    May 16, 2022
    Dataset provided by
    Bureau of Labor Statisticshttp://www.bls.gov/
    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. More information and details about the data provided can be found at http://www.bls.gov/cpi

  4. Consumer Price Index 2021 - West Bank and Gaza

    • pcbs.gov.ps
    Updated May 18, 2023
    + more versions
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    Palestinian Central Bureau of Statistics (2023). Consumer Price Index 2021 - West Bank and Gaza [Dataset]. https://www.pcbs.gov.ps/PCBS-Metadata-en-v5.2/index.php/catalog/711
    Explore at:
    Dataset updated
    May 18, 2023
    Dataset authored and provided by
    Palestinian Central Bureau of Statisticshttp://pcbs.gov.ps/
    Time period covered
    2021
    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

  5. d

    Consumer Price Index (CPI)- Division and Group - Index Number

    • data.gov.bh
    csv, excel, json
    Updated Jun 30, 2025
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    (2025). Consumer Price Index (CPI)- Division and Group - Index Number [Dataset]. https://www.data.gov.bh/explore/dataset/01-consumer-price-index-division-and-group-index-number/
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    excel, csv, jsonAvailable download formats
    Dataset updated
    Jun 30, 2025
    Description

    Detailed monthly consumer price index published according to the COICOP classification divisions and groups. Base: April 2019 (=100)

  6. e

    Consumer price index

    • data.europa.eu
    excel xls, excel xlsx +1
    Updated Feb 9, 2018
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    North Gate II & III - INS (STATBEL - Statistics Belgium) (2018). Consumer price index [Dataset]. https://data.europa.eu/data/datasets/78b06e72e3614d1019d54adf9ff84d7f4b23c35f?locale=en
    Explore at:
    excel xlsx, excel xls, pdfAvailable download formats
    Dataset updated
    Feb 9, 2018
    Dataset authored and provided by
    North Gate II & III - INS (STATBEL - Statistics Belgium)
    Description

    Purpose and brief description The consumer price index is an economic indicator whose main task is to objectively reflect the price evolution over time for a basket of goods and services purchased by households and considered representative of their consumer habits. The index does not necessarily measure the price level of this basket for a specific period of time, but rather the fluctuation between two periods, the first one acting as basis for comparison. Moreover, this difference in the price level is not measured in absolute, but in relative terms. The consumer price index can be determined as a hundred times the ratio between the observed prices of a range of goods and services at a given time and the prices of the same goods and services, observed under the same circumstances during the reference period, chosen as basis for comparison. Price observations always take place in the same regions. Since 2014, the consumer price index has been a chain index in which the weighting reference period is regularly shifted and prices and quantities are no longer compared between the current period and a fixed reference period, but the current period is compared with an intermediate period. By multiplying these short-term indices, and so creating a chain, we get a long-term series with a fixed reference period. Population Belgian private households Data collection method and possible sampling Survey technique applied using a computer, based on the use of electronic questionnaires and laptops. Frequency Monthly. Timing of publication The results are available on the penultimate working day of the reference period. Definitions Weight (CPI): The weight represents the importance of the goods and services included in the CPI in the total expenditure patterns of the households. Weights are determined based on the household budget survey. Consumer price index (CPI): The consumer price index is an economic indicator whose main task is to objectively reflect the price evolution over time for a basket of goods and services purchased by households and considered representative of their consumer habits. Health index: The health index is derived from the consumer price index and has been published since January 1994. The current value of this index is determined by removing a number of products from the consumer price index product basket, in particular alcoholic beverages (bought in a shop or consumed in a bar), tobacco products and motor fuels except for LPG. Inflation: Inflation is defined as the ratio between the value of the consumer price index of a given month and the index of the same month the year before. Therefore, inflation measures the rhythm of the evolution of the overall price level. Consumer price index without petroleum products: This index is calculated by removing the following products from the consumer price index: butane, propane, liquid fuels and motor fuels. Consumer price index without energy products: This index is calculated by removing the following products from the consumer price index: electricity, natural gas, butane, propane, liquid fuels, solid fuels and motor fuels. Smoothed index: The smoothed health index, also called smoothed index (the average value of the health indexes of the last 4 months) is used as a basis for the indexation of retirement pensions, social security benefits and some salaries and wages. Public wages and social benefits are indexed as soon as the smoothed index reaches a given value, called the central index. The smoothed index is also called moving average. In order to perform a 2% index jump (laid down in the Law of 23 April 2015 on employment promotion), the smoothed health index has been temporarily blocked at its value of March 2015 (100.66). The smoothed health index was then reduced by 2% from April 2015. When the reduced smoothed health index (also called the reference index) had increased again by 2% or in other words when it had exceeded the value of 100.66, the index was no longer blocked. It occurred in April 2016. Since April 2016 the smoothed health index is calculated in the same manner as the reference index and therefore corresponds to the arithmetical mean of the health indexes of the last 4 months multiplied by a factor of 0.98. The central index is a predetermined threshold value against which the smoothed health index is compared. If the central index is reached or exceeded, there is an indexation of the wages and salaries or benefits. This indexation is proportional to the percentage between the old and the new central index. For the public sector and social benefits, the difference between the central indices always amounts to 2 %. Therefore, a 2 % indexation is applied every time the central index is reached. There are also collective labour agreements according to which the difference between the central indices amounts to 1 % or 1.5 %. The reaching of a central index then leads to an indexation of 1 % or 1,5 %. See also: https://bosa.belgium.

  7. d

    All India and Yearly Average and Year End Consumer Price Index Number for...

    • dataful.in
    Updated Jul 1, 2025
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    Dataful (Factly) (2025). All India and Yearly Average and Year End Consumer Price Index Number for Industrial Workers [Dataset]. https://dataful.in/datasets/17512
    Explore at:
    csv, xlsx, application/x-parquetAvailable download formats
    Dataset updated
    Jul 1, 2025
    Dataset authored and provided by
    Dataful (Factly)
    License

    https://dataful.in/terms-and-conditionshttps://dataful.in/terms-and-conditions

    Area covered
    India
    Variables measured
    Consumer Price Index
    Description

    The dataset contains yearly All India Yearly Average and Year End Consumer Price Index Numbers for Industrial Workers by Group in Real Sector.

  8. k

    Consumer Price Index

    • datasource.kapsarc.org
    Updated Dec 18, 2024
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    (2024). Consumer Price Index [Dataset]. https://datasource.kapsarc.org/explore/dataset/consumer-prices-index-less-housing-01_24_2018-15_54_14/
    Explore at:
    Dataset updated
    Dec 18, 2024
    Description

    Explore the Consumer Prices Index Less Housing dataset, featuring information on percentage change, index numbers, and more. Stay updated on CPI trends in Saudi Arabia, Bahrain, Kuwait, Oman, and Qatar.

    Percentage change - previous period, Index number, %, Percentage change- same period previous year, CPI, Cost of living, Price

    Saudi Arabia, Bahrain, Kuwait, Oman, QatarFollow data.kapsarc.org for timely data to advance energy economics research..Base year = 2018

  9. T

    India Consumer Price Index (CPI)

    • tradingeconomics.com
    • es.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated May 15, 2018
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    TRADING ECONOMICS (2018). India Consumer Price Index (CPI) [Dataset]. https://tradingeconomics.com/india/consumer-price-index-cpi
    Explore at:
    excel, xml, json, csvAvailable download formats
    Dataset updated
    May 15, 2018
    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, 2011 - Jun 30, 2025
    Area covered
    India
    Description

    Consumer Price Index CPI in India increased to 194.20 points in June from 193 points in May of 2025. This dataset provides - India Consumer Price Index (CPI) - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  10. Consumer Price Index 2019 - West Bank and Gaza

    • pcbs.gov.ps
    Updated Dec 26, 2021
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    Palestinian Central Bureau of Statistics (2021). Consumer Price Index 2019 - West Bank and Gaza [Dataset]. https://www.pcbs.gov.ps/PCBS-Metadata-en-v5.2/index.php/catalog/704
    Explore at:
    Dataset updated
    Dec 26, 2021
    Dataset authored and provided by
    Palestinian Central Bureau of Statisticshttp://pcbs.gov.ps/
    Time period covered
    2019
    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

  11. d

    Year-wise Consumer price index numbers for agricultural labourers and rural...

    • dataful.in
    Updated Jun 13, 2025
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    Dataful (Factly) (2025). Year-wise Consumer price index numbers for agricultural labourers and rural labourers [Dataset]. https://dataful.in/datasets/20942
    Explore at:
    csv, application/x-parquet, xlsxAvailable download formats
    Dataset updated
    Jun 13, 2025
    Dataset authored and provided by
    Dataful (Factly)
    License

    https://dataful.in/terms-and-conditionshttps://dataful.in/terms-and-conditions

    Area covered
    States of India
    Variables measured
    Weight, Unit
    Description

    Data in table tells us about the year-wise Consumer price index numbers for agricultural labourers and rural labourers. The two categories mentioned in the table are- general and food items for all the Indian States and UTs from 2005-06 to 2016-17. The specific weight of each index type- general and food is also calculated.

    Notes: 1.The linking factor at All India level for conversion of current series on base 1986-87=100 to old base 1960-61=100 is 5.89 for General Index and 6.38 for Food Index in respect of Indices of Agricultural Labourers. 2. Agricultural Year = July to June

  12. U.S. monthly change in the Consumer Price Index (CPI-U) 2023-2024

    • statista.com
    Updated Jun 27, 2025
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    Statista (2025). U.S. monthly change in the Consumer Price Index (CPI-U) 2023-2024 [Dataset]. https://www.statista.com/statistics/216037/monthly-percentage-of-change-in-the-cpi-u-in-the-us/
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    Dataset updated
    Jun 27, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Nov 2023 - Nov 2024
    Area covered
    United States
    Description

    In November 2024, the seasonally adjusted consumer price index for all urban consumers (CPI-U) in the United States increased *** percent from the previous month. The data represents city averages in the United States. The defined base period is: 1982-84=100. The CPI is defined by the United States Bureau of Labor Statistics as “a measure of the average change over time in the prices paid by urban consumers for a market basket of consumer goods and services”.

  13. o

    Consumers Price Index (CPI), Division - Index Numbers by Nationality

    • bahrain.opendatasoft.com
    • data.gov.bh
    csv, excel, json
    Updated Jun 26, 2025
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    (2025). Consumers Price Index (CPI), Division - Index Numbers by Nationality [Dataset]. https://bahrain.opendatasoft.com/explore/dataset/02-cpi-division-index-number-by-nationality/api/?flg=en-gb
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    json, excel, csvAvailable download formats
    Dataset updated
    Jun 26, 2025
    Description

    Consumers price index, division– index numbers by nationality: monthly Consumer Price index classified by nationality published according to the COICOP classification divisions. Base: April 2019 (=100)

  14. Iran CPI: Urban: Food and Non-Alcoholic Beverages (FB)

    • ceicdata.com
    Updated Mar 15, 2024
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    CEICdata.com (2024). Iran CPI: Urban: Food and Non-Alcoholic Beverages (FB) [Dataset]. https://www.ceicdata.com/en/iran/consumer-price-index-april-16march-17100-statistical-centre-of-iran-urban/cpi-urban-food-and-nonalcoholic-beverages-fb
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    Dataset updated
    Mar 15, 2024
    Dataset provided by
    CEIC Data
    License

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

    Time period covered
    Aug 1, 2018 - Jul 1, 2019
    Area covered
    Iran
    Description

    Iran Consumer Price Index (CPI): Urban: Food and Non-Alcoholic Beverages (FB) data was reported at 220.400 Apr2016-Mar2017=100 in Jul 2019. This records an increase from the previous number of 216.900 Apr2016-Mar2017=100 for Jun 2019. Iran Consumer Price Index (CPI): Urban: Food and Non-Alcoholic Beverages (FB) data is updated monthly, averaging 166.900 Apr2016-Mar2017=100 from Mar 2018 (Median) to Jul 2019, with 17 observations. The data reached an all-time high of 220.400 Apr2016-Mar2017=100 in Jul 2019 and a record low of 115.800 Apr2016-Mar2017=100 in Mar 2018. Iran Consumer Price Index (CPI): Urban: Food and Non-Alcoholic Beverages (FB) data remains active status in CEIC and is reported by Statistical Centre of Iran. The data is categorized under Global Database’s Iran – Table IR.I002: Consumer Price Index: April 16-March 17=100: Statistical Centre of Iran: Urban.

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

    • data.overheid.nl
    • cloud.csiss.gmu.edu
    • +2more
    atom, json
    Updated Nov 2, 2016
    + more versions
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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.

  16. Consumer price inflation tables

    • ons.gov.uk
    • cy.ons.gov.uk
    xlsx
    Updated Jun 18, 2025
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    Office for National Statistics (2025). Consumer price inflation tables [Dataset]. https://www.ons.gov.uk/economy/inflationandpriceindices/datasets/consumerpriceinflation
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    xlsxAvailable 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

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

  17. d

    Year-wise Consumer price index number for industrial workers

    • dataful.in
    Updated Jun 13, 2025
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    Dataful (Factly) (2025). Year-wise Consumer price index number for industrial workers [Dataset]. https://dataful.in/datasets/20937
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    application/x-parquet, xlsx, csvAvailable download formats
    Dataset updated
    Jun 13, 2025
    Dataset authored and provided by
    Dataful (Factly)
    License

    https://dataful.in/terms-and-conditionshttps://dataful.in/terms-and-conditions

    Area covered
    States of India
    Variables measured
    Weight, Unit
    Description

    Data in table tells us about the year-wise Consumer price index number for industrial workers. Parameters used to classify data in the table are: Clothing,bedding,footwear, Food and General. The specific weightage of these parameters is also calculated as percentage of whole. Data is gathered from 2007-2016 for Indian States and UTs and also for All India.

    Note: The total of the respective weights may not tally as the original weight are calculated to six places of decimals whereas the weights given here are rounded to two places of decimals.

  18. Median CPI

    • clevelandfed.org
    csv
    Updated Jun 11, 2025
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    Federal Reserve Bank of Cleveland (2025). Median CPI [Dataset]. https://www.clevelandfed.org/indicators-and-data/median-cpi
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    csvAvailable download formats
    Dataset updated
    Jun 11, 2025
    Dataset authored and provided by
    Federal Reserve Bank of Clevelandhttps://www.clevelandfed.org/
    Description

    The median CPI is a measure of inflation computed by the Federal Reserve Bank of Cleveland. It ranks the components of CPI inflation and picks the one in the middle. Its construction makes it less sensitive to short-lived price fluctuations, thereby better capturing the trend in prices. Released monthly.

  19. Consumer Price Index by product group, monthly, percentage change, not...

    • www150.statcan.gc.ca
    Updated Jun 24, 2025
    + more versions
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    Government of Canada, Statistics Canada (2025). Consumer Price Index by product group, monthly, percentage change, not seasonally adjusted, Canada, provinces, Whitehorse, Yellowknife and Iqaluit [Dataset]. http://doi.org/10.25318/1810000401-eng
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    Dataset updated
    Jun 24, 2025
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    Area covered
    Canada
    Description

    Monthly indexes and percentage changes for major components and special aggregates of the Consumer Price Index (CPI), not seasonally adjusted, for Canada, provinces, Whitehorse, Yellowknife and Iqaluit. Data are presented for the corresponding month of the previous year, the previous month and the current month. The base year for the index is 2002=100.

  20. e

    Consumer Price Index (CPI), total, Shadow Index numbers, 1980=100 (no update...

    • data.europa.eu
    json
    Updated Jul 19, 2023
    + more versions
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    Statistikmyndigheten SCB - Statistiska centralbyrån (2023). Consumer Price Index (CPI), total, Shadow Index numbers, 1980=100 (no update after 2022M11). Month 1980M01 - 2022M11 [Dataset]. https://data.europa.eu/data/datasets/https-statistikdatabasen-scb-se-dataset-tab2081?locale=en
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jul 19, 2023
    Dataset authored and provided by
    Statistikmyndigheten SCB - Statistiska centralbyrån
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    Consumer Price Index (CPI), total, Shadow Index numbers, 1980=100 by month

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TRADING ECONOMICS (2025). United States Consumer Price Index (CPI) [Dataset]. https://tradingeconomics.com/united-states/consumer-price-index-cpi

United States Consumer Price Index (CPI)

United States Consumer Price Index (CPI) - Historical Dataset (1950-01-31/2025-05-31)

Explore at:
21 scholarly articles cite this dataset (View in Google Scholar)
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.

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