88 datasets found
  1. Consumer price inflation consumption segment indices and price quotes

    • ons.gov.uk
    • cy.ons.gov.uk
    csv
    Updated Aug 20, 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
    Explore at:
    csvAvailable download formats
    Dataset updated
    Aug 20, 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.

  2. T

    United States Consumer Inflation Expectations

    • tradingeconomics.com
    • it.tradingeconomics.com
    • +13more
    csv, excel, json, xml
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    TRADING ECONOMICS, United States Consumer Inflation Expectations [Dataset]. https://tradingeconomics.com/united-states/inflation-expectations
    Explore at:
    json, excel, xml, csvAvailable download formats
    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
    Jun 30, 2013 - Jul 31, 2025
    Area covered
    United States
    Description

    Inflation Expectations in the United States increased to 3.10 percent in July from 3 percent in June of 2025. This dataset provides - United States Consumer Inflation Expectations- actual values, historical data, forecast, chart, statistics, economic calendar and news.

  3. T

    Canada Inflation Rate

    • tradingeconomics.com
    • es.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Aug 19, 2025
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    TRADING ECONOMICS (2025). Canada Inflation Rate [Dataset]. https://tradingeconomics.com/canada/inflation-cpi
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    json, excel, csv, xmlAvailable download formats
    Dataset updated
    Aug 19, 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, 1915 - Jul 31, 2025
    Area covered
    Canada
    Description

    Inflation Rate in Canada decreased to 1.70 percent in July from 1.90 percent in June of 2025. This dataset provides - Canada Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  4. Introducing the new RPIJ measure of Consumer Price Inflation - Dataset -...

    • ckan.publishing.service.gov.uk
    Updated Mar 12, 2013
    + more versions
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    ckan.publishing.service.gov.uk (2013). Introducing the new RPIJ measure of Consumer Price Inflation - Dataset - data.gov.uk [Dataset]. https://ckan.publishing.service.gov.uk/dataset/introducing_the_new_rpij_measure_of_consumer_price_inflation
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    Dataset updated
    Mar 12, 2013
    Dataset provided by
    CKANhttps://ckan.org/
    License

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

    Description

    This article describes the new RPIJ measure of Consumer Price Inflation. RPIJ is a Retail Prices Index (RPI) based measure that will use a geometric (Jevons) formula in place of one type of arithmetic formula (Carli). It is being launched in response to the National Statistician's conclusion that the RPI does not meet international standards due to the use of the Carli formula in its calculation. The accompanying Excel file includes a back series for RPIJ from 1997 to 2012. Source agency: Office for National Statistics Designation: National Statistics Language: English Alternative title: New RPIJ measure of Consumer Price Inflation

  5. Replication dataset for PIIE PB 24-2, The Inflation Surge in Europe by...

    • piie.com
    Updated May 25, 2024
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    Patrick Honohan (2024). Replication dataset for PIIE PB 24-2, The Inflation Surge in Europe by Patrick Honohan (2024). [Dataset]. https://www.piie.com/publications/policy-briefs/2024/inflation-surge-europe
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    Dataset updated
    May 25, 2024
    Dataset provided by
    Peterson Institute for International Economicshttp://www.piie.com/
    Authors
    Patrick Honohan
    Area covered
    Europe
    Description

    This data package includes the underlying data files to replicate the data and charts presented in The Inflation Surge in Europe by Patrick Honohan, PIIE Policy Brief 24-2.

    If you use the data, please cite as: Honohan, Patrick. 2024. The Inflation Surge in Europe. PIIE Policy Brief 24-2. Washington, DC: Peterson Institute for International Economics.

  6. w

    Dataset of demonym and inflation of countries per year in China (Historical)...

    • workwithdata.com
    Updated Apr 9, 2025
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    Work With Data (2025). Dataset of demonym and inflation of countries per year in China (Historical) [Dataset]. https://www.workwithdata.com/datasets/countries-yearly?col=country%2Cdate%2Cdemonym%2Cinflation&f=1&fcol0=country&fop0=%3D&fval0=China
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    Dataset updated
    Apr 9, 2025
    Dataset authored and provided by
    Work With Data
    License

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

    Area covered
    China
    Description

    This dataset is about countries per year in China. It has 64 rows. It features 4 columns: country, demonym, and inflation.

  7. T

    Nigeria Food Inflation

    • tradingeconomics.com
    • fa.tradingeconomics.com
    • +13more
    csv, excel, json, xml
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    TRADING ECONOMICS, Nigeria Food Inflation [Dataset]. https://tradingeconomics.com/nigeria/food-inflation
    Explore at:
    csv, xml, json, excelAvailable download formats
    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, 1996 - Jul 31, 2025
    Area covered
    Nigeria
    Description

    Cost of food in Nigeria increased 22.74 percent in July of 2025 over the same month in the previous year. This dataset provides - Nigeria Food Inflation - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  8. Producer price inflation (MM22)

    • ons.gov.uk
    • cy.ons.gov.uk
    xlsx
    Updated Feb 19, 2025
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    Office for National Statistics (2025). Producer price inflation (MM22) [Dataset]. https://www.ons.gov.uk/economy/inflationandpriceindices/datasets/mm22producerpriceindices
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    xlsxAvailable 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

    UK price index data at manufacturing, aggregated industry and product group levels. Data supplied from individual manufacturers, importers and exporters. Monthly and annual data.

  9. T

    Norway Inflation Rate

    • tradingeconomics.com
    • zh.tradingeconomics.com
    • +13more
    csv, excel, json, xml
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    TRADING ECONOMICS, Norway Inflation Rate [Dataset]. https://tradingeconomics.com/norway/inflation-cpi
    Explore at:
    excel, csv, json, xmlAvailable download formats
    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 - Jul 31, 2025
    Area covered
    Norway
    Description

    Inflation Rate in Norway increased to 3.30 percent in July from 3 percent in June of 2025. This dataset provides - Norway Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  10. T

    United States Core Inflation Rate MoM

    • tradingeconomics.com
    • jp.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Aug 12, 2025
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    TRADING ECONOMICS (2025). United States Core Inflation Rate MoM [Dataset]. https://tradingeconomics.com/united-states/core-inflation-rate-mom
    Explore at:
    excel, csv, json, xmlAvailable download formats
    Dataset updated
    Aug 12, 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
    Feb 28, 1957 - Jul 31, 2025
    Area covered
    United States
    Description

    Core Inflation Rate MoM in the United States increased to 0.30 percent in July from 0.20 percent in June of 2025. This dataset includes a chart with historical data for the United States Core Inflation Rate MoM.

  11. T

    Australia Inflation Rate

    • tradingeconomics.com
    • jp.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Jul 30, 2025
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    TRADING ECONOMICS (2025). Australia Inflation Rate [Dataset]. https://tradingeconomics.com/australia/inflation-cpi
    Explore at:
    csv, excel, json, xmlAvailable download formats
    Dataset updated
    Jul 30, 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
    Mar 31, 1951 - Jun 30, 2025
    Area covered
    Australia
    Description

    Inflation Rate in Australia decreased to 2.10 percent in the second quarter of 2025 from 2.40 percent in the first quarter of 2025. This dataset provides the latest reported value for - Australia Inflation Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

  12. N

    Success, AR annual median income by work experience and sex dataset: Aged...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
    + more versions
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    Neilsberg Research (2025). Success, AR annual median income by work experience and sex dataset: Aged 15+, 2010-2023 (in 2023 inflation-adjusted dollars) // 2025 Edition [Dataset]. https://www.neilsberg.com/research/datasets/a539c569-f4ce-11ef-8577-3860777c1fe6/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Feb 27, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

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

    Area covered
    Arkansas, Success
    Variables measured
    Income for Male Population, Income for Female Population, Income for Male Population working full time, Income for Male Population working part time, Income for Female Population working full time, Income for Female Population working part time
    Measurement technique
    The data presented in this dataset is derived from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates. The dataset covers the years 2010 to 2023, representing 14 years of data. To analyze income differences between genders (male and female), we conducted an initial data analysis and categorization. Subsequently, we adjusted these figures for inflation using the Consumer Price Index retroactive series (R-CPI-U-RS) based on current methodologies. For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Success. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

    Key observations: Insights from 2023

    Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Success, while the Census reported a median income of $41,875 for all male workers aged 15 years and older, data for females in the same category was unavailable due to an insufficient number of sample observations.

    Given the absence of income data for females from the Census Bureau, conducting a thorough analysis of gender-based pay disparity in the town of Success was not possible.

    - Full-time workers, aged 15 years and older: In Success, among full-time, year-round workers aged 15 years and older, males earned a median income of $53,333, while females earned $38,500, leading to a 28% gender pay gap among full-time workers. This illustrates that women earn 72 cents for each dollar earned by men in full-time roles. This analysis indicates a widening gender pay gap, showing a substantial income disparity where women, despite working full-time, face a more significant wage discrepancy compared to men in the same roles.

    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

    Gender classifications include:

    • Male
    • Female

    Employment type classifications include:

    • Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
    • Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

    Variables / Data Columns

    • Year: This column presents the data year. Expected values are 2010 to 2023
    • Male Total Income: Annual median income, for males regardless of work hours
    • Male FT Income: Annual median income, for males working full time, year-round
    • Male PT Income: Annual median income, for males working part time
    • Female Total Income: Annual median income, for females regardless of work hours
    • Female FT Income: Annual median income, for females working full time, year-round
    • Female PT Income: Annual median income, for females working part time

    Good to know

    Margin of Error

    Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

    Custom data

    If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

    Inspiration

    Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

    Recommended for further research

    This dataset is a part of the main dataset for Success median household income by race. You can refer the same here

  13. T

    INFLATION EXPECTATIONS by Country Dataset

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Jun 3, 2017
    + more versions
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    TRADING ECONOMICS (2017). INFLATION EXPECTATIONS by Country Dataset [Dataset]. https://tradingeconomics.com/country-list/inflation-expectations
    Explore at:
    xml, json, csv, excelAvailable download formats
    Dataset updated
    Jun 3, 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 INFLATION EXPECTATIONS reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

  14. T

    United Kingdom Food Inflation

    • tradingeconomics.com
    • jp.tradingeconomics.com
    • +12more
    csv, excel, json, xml
    Updated Jul 15, 2025
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    TRADING ECONOMICS (2025). United Kingdom Food Inflation [Dataset]. https://tradingeconomics.com/united-kingdom/food-inflation
    Explore at:
    excel, csv, json, xmlAvailable download formats
    Dataset updated
    Jul 15, 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, 1989 - Jul 31, 2025
    Area covered
    United Kingdom
    Description

    Cost of food in the United Kingdom increased 4.90 percent in July of 2025 over the same month in the previous year. This dataset provides the latest reported value for - United Kingdom Food Inflation - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

  15. N

    Boley, OK annual median income by work experience and sex dataset: Aged 15+,...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
    + more versions
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    Neilsberg Research (2025). Boley, OK annual median income by work experience and sex dataset: Aged 15+, 2010-2023 (in 2023 inflation-adjusted dollars) // 2025 Edition [Dataset]. https://www.neilsberg.com/insights/boley-ok-income-by-gender/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Feb 27, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

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

    Area covered
    Oklahoma, Boley
    Variables measured
    Income for Male Population, Income for Female Population, Income for Male Population working full time, Income for Male Population working part time, Income for Female Population working full time, Income for Female Population working part time
    Measurement technique
    The data presented in this dataset is derived from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates. The dataset covers the years 2010 to 2023, representing 14 years of data. To analyze income differences between genders (male and female), we conducted an initial data analysis and categorization. Subsequently, we adjusted these figures for inflation using the Consumer Price Index retroactive series (R-CPI-U-RS) based on current methodologies. For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Boley. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

    Key observations: Insights from 2023

    Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Boley, the median income for all workers aged 15 years and older, regardless of work hours, was $10,357 for males and $20,086 for females.

    Contrary to expectations, women in Boley, women, regardless of work hours, earn a higher income than men, earning 1.94 dollars for every dollar earned by men. This analysis indicates a significant shift in income dynamics favoring females.

    - Full-time workers, aged 15 years and older: In Boley, for full-time, year-round workers aged 15 years and older, while the Census reported a median income of $35,139 for males, while data for females was unavailable due to an insufficient number of sample observations.

    As there was no available median income data for females, conducting a comprehensive assessment of gender-based pay disparity in Boley was not feasible.

    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

    Gender classifications include:

    • Male
    • Female

    Employment type classifications include:

    • Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
    • Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

    Variables / Data Columns

    • Year: This column presents the data year. Expected values are 2010 to 2023
    • Male Total Income: Annual median income, for males regardless of work hours
    • Male FT Income: Annual median income, for males working full time, year-round
    • Male PT Income: Annual median income, for males working part time
    • Female Total Income: Annual median income, for females regardless of work hours
    • Female FT Income: Annual median income, for females working full time, year-round
    • Female PT Income: Annual median income, for females working part time

    Good to know

    Margin of Error

    Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

    Custom data

    If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

    Inspiration

    Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

    Recommended for further research

    This dataset is a part of the main dataset for Boley median household income by race. You can refer the same here

  16. T

    Ukraine Inflation Rate

    • tradingeconomics.com
    • id.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Aug 8, 2025
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    TRADING ECONOMICS (2025). Ukraine Inflation Rate [Dataset]. https://tradingeconomics.com/ukraine/inflation-cpi
    Explore at:
    excel, csv, xml, jsonAvailable download formats
    Dataset updated
    Aug 8, 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, 1995 - Jul 31, 2025
    Area covered
    Ukraine
    Description

    Inflation Rate in Ukraine decreased to 14.10 percent in July from 14.30 percent in June of 2025. This dataset provides the latest reported value for - Ukraine Inflation Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

  17. N

    Custer City, OK annual median income by work experience and sex dataset:...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
    + more versions
    Share
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    Cite
    Neilsberg Research (2025). Custer City, OK annual median income by work experience and sex dataset: Aged 15+, 2010-2023 (in 2023 inflation-adjusted dollars) // 2025 Edition [Dataset]. https://www.neilsberg.com/research/datasets/a50e46f9-f4ce-11ef-8577-3860777c1fe6/
    Explore at:
    json, csvAvailable download formats
    Dataset updated
    Feb 27, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

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

    Area covered
    Custer City, Oklahoma
    Variables measured
    Income for Male Population, Income for Female Population, Income for Male Population working full time, Income for Male Population working part time, Income for Female Population working full time, Income for Female Population working part time
    Measurement technique
    The data presented in this dataset is derived from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates. The dataset covers the years 2010 to 2023, representing 14 years of data. To analyze income differences between genders (male and female), we conducted an initial data analysis and categorization. Subsequently, we adjusted these figures for inflation using the Consumer Price Index retroactive series (R-CPI-U-RS) based on current methodologies. For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Custer City. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

    Key observations: Insights from 2023

    Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Custer City, while the Census reported a median income of $60,750 for all male workers aged 15 years and older, data for females in the same category was unavailable due to an insufficient number of sample observations.

    Given the absence of income data for females from the Census Bureau, conducting a thorough analysis of gender-based pay disparity in the town of Custer City was not possible.

    - Full-time workers, aged 15 years and older: In Custer City, among full-time, year-round workers aged 15 years and older, males earned a median income of $63,090, while females earned $44,583, leading to a 29% gender pay gap among full-time workers. This illustrates that women earn 71 cents for each dollar earned by men in full-time roles. This analysis indicates a widening gender pay gap, showing a substantial income disparity where women, despite working full-time, face a more significant wage discrepancy compared to men in the same roles.

    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

    Gender classifications include:

    • Male
    • Female

    Employment type classifications include:

    • Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
    • Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

    Variables / Data Columns

    • Year: This column presents the data year. Expected values are 2010 to 2023
    • Male Total Income: Annual median income, for males regardless of work hours
    • Male FT Income: Annual median income, for males working full time, year-round
    • Male PT Income: Annual median income, for males working part time
    • Female Total Income: Annual median income, for females regardless of work hours
    • Female FT Income: Annual median income, for females working full time, year-round
    • Female PT Income: Annual median income, for females working part time

    Good to know

    Margin of Error

    Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

    Custom data

    If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

    Inspiration

    Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

    Recommended for further research

    This dataset is a part of the main dataset for Custer City median household income by race. You can refer the same here

  18. T

    South Korea Inflation Rate

    • tradingeconomics.com
    • zh.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Sep 1, 2025
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    TRADING ECONOMICS (2025). South Korea Inflation Rate [Dataset]. https://tradingeconomics.com/south-korea/inflation-cpi
    Explore at:
    csv, json, xml, excelAvailable download formats
    Dataset updated
    Sep 1, 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, 1966 - Aug 31, 2025
    Area covered
    South Korea
    Description

    Inflation Rate in South Korea decreased to 1.70 percent in August from 2.10 percent in July of 2025. This dataset provides the latest reported value for - South Korea Inflation Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

  19. N

    Onota Township, Michigan annual median income by work experience and sex...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
    + more versions
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    Neilsberg Research (2025). Onota Township, Michigan annual median income by work experience and sex dataset: Aged 15+, 2010-2023 (in 2023 inflation-adjusted dollars) // 2025 Edition [Dataset]. https://www.neilsberg.com/research/datasets/a52ddeb9-f4ce-11ef-8577-3860777c1fe6/
    Explore at:
    json, csvAvailable download formats
    Dataset updated
    Feb 27, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

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

    Area covered
    Michigan, Onota Township
    Variables measured
    Income for Male Population, Income for Female Population, Income for Male Population working full time, Income for Male Population working part time, Income for Female Population working full time, Income for Female Population working part time
    Measurement technique
    The data presented in this dataset is derived from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates. The dataset covers the years 2010 to 2023, representing 14 years of data. To analyze income differences between genders (male and female), we conducted an initial data analysis and categorization. Subsequently, we adjusted these figures for inflation using the Consumer Price Index retroactive series (R-CPI-U-RS) based on current methodologies. For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Onota township. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

    Key observations: Insights from 2023

    Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Onota township, while the Census reported a median income of $26,573 for all male workers aged 15 years and older, data for females in the same category was unavailable due to an insufficient number of sample observations.

    Given the absence of income data for females from the Census Bureau, conducting a thorough analysis of gender-based pay disparity in the township of Onota township was not possible.

    - Full-time workers, aged 15 years and older: In Onota township, for full-time, year-round workers aged 15 years and older, while the Census reported a median income of $55,703 for males, while data for females was unavailable due to an insufficient number of sample observations.

    As there was no available median income data for females, conducting a comprehensive assessment of gender-based pay disparity in Onota township was not feasible.

    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

    Gender classifications include:

    • Male
    • Female

    Employment type classifications include:

    • Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
    • Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

    Variables / Data Columns

    • Year: This column presents the data year. Expected values are 2010 to 2023
    • Male Total Income: Annual median income, for males regardless of work hours
    • Male FT Income: Annual median income, for males working full time, year-round
    • Male PT Income: Annual median income, for males working part time
    • Female Total Income: Annual median income, for females regardless of work hours
    • Female FT Income: Annual median income, for females working full time, year-round
    • Female PT Income: Annual median income, for females working part time

    Good to know

    Margin of Error

    Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

    Custom data

    If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

    Inspiration

    Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

    Recommended for further research

    This dataset is a part of the main dataset for Onota township median household income by race. You can refer the same here

  20. T

    INFLATION RATE MOM by Country Dataset

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Sep 6, 2025
    + more versions
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    TRADING ECONOMICS (2013). INFLATION RATE MOM by Country Dataset [Dataset]. https://tradingeconomics.com/country-list/inflation-rate-mom
    Explore at:
    json, xml, csv, excelAvailable download formats
    Dataset updated
    Sep 6, 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
    2025
    Area covered
    World
    Description

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

Share
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Email
Click to copy link
Link copied
Close
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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
Organization logo

Consumer price inflation consumption segment indices and price quotes

Explore at:
7 scholarly articles cite this dataset (View in Google Scholar)
csvAvailable download formats
Dataset updated
Aug 20, 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.

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