100+ datasets found
  1. T

    United States Inflation Rate

    • tradingeconomics.com
    • fa.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Oct 24, 2025
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    TRADING ECONOMICS (2025). United States Inflation Rate [Dataset]. https://tradingeconomics.com/united-states/inflation-cpi
    Explore at:
    json, excel, xml, csvAvailable download formats
    Dataset updated
    Oct 24, 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
    Dec 31, 1914 - Sep 30, 2025
    Area covered
    United States
    Description

    Inflation Rate in the United States increased to 3 percent in September from 2.90 percent in August of 2025. This dataset provides - United States Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  2. T

    United States Consumer Inflation Expectations

    • tradingeconomics.com
    • it.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Oct 16, 2025
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    TRADING ECONOMICS (2025). United States Consumer Inflation Expectations [Dataset]. https://tradingeconomics.com/united-states/inflation-expectations
    Explore at:
    json, excel, xml, csvAvailable download formats
    Dataset updated
    Oct 16, 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
    Jun 30, 2013 - Oct 31, 2025
    Area covered
    United States
    Description

    Inflation Expectations in the United States decreased to 3.20 percent in October from 3.40 percent in September of 2025. This dataset provides - United States Consumer Inflation Expectations- actual values, historical data, forecast, chart, statistics, economic calendar and news.

  3. T

    United States Core Inflation Rate

    • tradingeconomics.com
    • id.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Oct 24, 2025
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    TRADING ECONOMICS (2025). United States Core Inflation Rate [Dataset]. https://tradingeconomics.com/united-states/core-inflation-rate
    Explore at:
    excel, csv, json, xmlAvailable download formats
    Dataset updated
    Oct 24, 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 - Sep 30, 2025
    Area covered
    United States
    Description

    Core consumer prices in the United States increased 3 percent in September of 2025 over the same month in the previous year. This dataset provides - United States Core Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  4. F

    30-Year Expected Inflation

    • fred.stlouisfed.org
    json
    Updated Oct 24, 2025
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    (2025). 30-Year Expected Inflation [Dataset]. https://fred.stlouisfed.org/series/EXPINF30YR
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Oct 24, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Description

    Graph and download economic data for 30-Year Expected Inflation (EXPINF30YR) from Jan 1982 to Oct 2025 about 30-year, projection, inflation, and USA.

  5. T

    India Inflation Rate

    • tradingeconomics.com
    • fa.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Nov 12, 2025
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    TRADING ECONOMICS (2025). India Inflation Rate [Dataset]. https://tradingeconomics.com/india/inflation-cpi
    Explore at:
    csv, xml, excel, jsonAvailable download formats
    Dataset updated
    Nov 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
    Jan 31, 2012 - Oct 31, 2025
    Area covered
    India
    Description

    Inflation Rate in India decreased to 0.25 percent in October from 1.44 percent in September of 2025. This dataset provides - India Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  6. GDP by Country 2005–2025: 20 Years of Global Data

    • kaggle.com
    zip
    Updated Sep 25, 2025
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    Code by Nadiia (2025). GDP by Country 2005–2025: 20 Years of Global Data [Dataset]. https://www.kaggle.com/datasets/codebynadiia/gdp-by-country-20052025-20-years-of-global-data
    Explore at:
    zip(15170 bytes)Available download formats
    Dataset updated
    Sep 25, 2025
    Authors
    Code by Nadiia
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    This dataset provides annual GDP data for 196 countries from 2005 to 2025, measured in USD billions. Data is sourced from the International Monetary Fund (IMF).

    Coverage: 196 countries + header row Time span: 2005–2024 (reported), 2025 (projected) Notable trends: The data clearly shows the impact of the 2008 global financial crisis and the 2020 COVID-19 pandemic on world economies. Missing values: In some cases, GDP values are unavailable because countries did not report them.

    Usability

    Trend analysis — Study global and regional GDP growth patterns across two decades.

    Forecasting models — Train ARIMA, Prophet, LSTM, or other models to predict future GDP.

    Comparative studies — Benchmark economic performance between countries, continents, or economic blocs (e.g., G7, BRICS).

    Impact assessment — Analyze the effect of global events such as the 2008 crisis and COVID-19 on GDP.

    Correlation research — Combine with other datasets (population, inflation, CO₂ emissions) for cross indicator analysis.

    Visualization projects — Build dashboards, choropleth maps, or interactive charts to illustrate global growth.

    Educational use — Teach concepts of macroeconomics, time series data, and forecasting in classrooms.

    Investment & policy insights — Support macro level decision making, financial market analysis, or policy research.

  7. Inflation Nowcasting Quarterly

    • clevelandfed.org
    Updated Mar 10, 2017
    + more versions
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    Federal Reserve Bank of Cleveland (2017). Inflation Nowcasting Quarterly [Dataset]. https://www.clevelandfed.org/indicators-and-data/inflation-nowcasting
    Explore at:
    Dataset updated
    Mar 10, 2017
    Dataset authored and provided by
    Federal Reserve Bank of Clevelandhttps://www.clevelandfed.org/
    License

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

    Description

    Inflation Nowcasting Quarterly is a part of the Inflation Nowcasting indicator of the Federal Reserve Bank of Cleveland.

  8. T

    Israel Inflation Expectations

    • tradingeconomics.com
    • jp.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Nov 20, 2025
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    TRADING ECONOMICS (2025). Israel Inflation Expectations [Dataset]. https://tradingeconomics.com/israel/inflation-expectations
    Explore at:
    xml, json, csv, excelAvailable download formats
    Dataset updated
    Nov 20, 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, 1994 - Nov 30, 2025
    Area covered
    Israel
    Description

    Inflation Expectations in Israel decreased to 1.60 percent in November from 1.70 percent in October of 2025. This dataset provides - Israel Inflation Expectations- actual values, historical data, forecast, chart, statistics, economic calendar and news.

  9. T

    Sweden Inflation Rate

    • tradingeconomics.com
    • zh.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Nov 14, 2025
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    TRADING ECONOMICS (2025). Sweden Inflation Rate [Dataset]. https://tradingeconomics.com/sweden/inflation-cpi
    Explore at:
    csv, excel, json, xmlAvailable download formats
    Dataset updated
    Nov 14, 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, 1980 - Oct 31, 2025
    Area covered
    Sweden
    Description

    Inflation Rate in Sweden remained unchanged at 0.90 percent in October. This dataset provides - Sweden Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  10. T

    Japan Inflation Rate

    • tradingeconomics.com
    • zh.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Nov 20, 2025
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    TRADING ECONOMICS (2025). Japan Inflation Rate [Dataset]. https://tradingeconomics.com/japan/inflation-cpi
    Explore at:
    csv, json, excel, xmlAvailable download formats
    Dataset updated
    Nov 20, 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, 1958 - Oct 31, 2025
    Area covered
    Japan
    Description

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

  11. T

    Germany Inflation Rate

    • tradingeconomics.com
    • pl.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Nov 28, 2025
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    TRADING ECONOMICS (2025). Germany Inflation Rate [Dataset]. https://tradingeconomics.com/germany/inflation-cpi
    Explore at:
    json, csv, excel, xmlAvailable download formats
    Dataset updated
    Nov 28, 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 - Nov 30, 2025
    Area covered
    Germany
    Description

    Inflation Rate in Germany remained unchanged at 2.30 percent in November. This dataset provides the latest reported value for - Germany Inflation Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

  12. N

    Morocco, IN 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). Morocco, IN 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/a529d0b8-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
    Morocco
    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 Morocco. 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 Morocco, the median income for all workers aged 15 years and older, regardless of work hours, was $42,279 for males and $25,066 for females.

    These income figures highlight a substantial gender-based income gap in Morocco. Women, regardless of work hours, earn 59 cents for each dollar earned by men. This significant gender pay gap, approximately 41%, underscores concerning gender-based income inequality in the town of Morocco.

    - Full-time workers, aged 15 years and older: In Morocco, among full-time, year-round workers aged 15 years and older, males earned a median income of $51,016, while females earned $42,566, leading to a 17% gender pay gap among full-time workers. This illustrates that women earn 83 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.

    Surprisingly, the gender pay gap percentage was higher across all roles, including non-full-time employment, for women compared to men. This suggests that full-time employment offers a more equitable income scenario for women compared to other employment patterns in Morocco.

    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 Morocco median household income by race. You can refer the same here

  13. N

    Dorchester, New Hampshire 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). Dorchester, New Hampshire 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/a5109eaf-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
    Dorchester, New Hampshire
    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 Dorchester town. 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 Dorchester town, while the Census reported a median income of $20,857 for all female workers aged 15 years and older, data for males in the same category was unavailable due to an insufficient number of sample observations.

    Because income data for males was not available from the Census Bureau, conducting a comprehensive analysis of gender-based pay disparity in the town of Dorchester town was not possible.

    - Full-time workers, aged 15 years and older: In Dorchester town, among full-time, year-round workers aged 15 years and older, males earned a median income of $72,750, while females earned $93,750

    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 Dorchester town median household income by race. You can refer the same here

  14. 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.

  15. N

    Fairfield township, Cumberland County, New Jersey annual median income by...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
    + more versions
    Share
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    Neilsberg Research (2025). Fairfield township, Cumberland County, New Jersey 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/a5144903-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
    Cumberland County, New Jersey, Fairfield
    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 Fairfield 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 Fairfield township, the median income for all workers aged 15 years and older, regardless of work hours, was $24,430 for males and $29,506 for females.

    Contrary to expectations, women in Fairfield township, women, regardless of work hours, earn a higher income than men, earning 1.21 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 Fairfield township, among full-time, year-round workers aged 15 years and older, males earned a median income of $40,238, while females earned $45,814

    Contrary to expectations, in Fairfield township, women, earn a higher income than men, earning 1.14 dollars for every dollar earned by men. This analysis showcase a consistent trend of women outearning men, when working full-time or part-time in the township of Fairfield township.

    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 Fairfield township median household income by race. You can refer the same here

  16. T

    Euro Area Inflation Rate

    • tradingeconomics.com
    • fa.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Dec 2, 2025
    Share
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    TRADING ECONOMICS (2025). Euro Area Inflation Rate [Dataset]. https://tradingeconomics.com/euro-area/inflation-cpi
    Explore at:
    excel, json, csv, xmlAvailable download formats
    Dataset updated
    Dec 2, 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, 1991 - Nov 30, 2025
    Area covered
    Euro Area
    Description

    Inflation Rate In the Euro Area increased to 2.20 percent in November from 2.10 percent in October of 2025. This dataset provides the latest reported value for - Euro Area Inflation Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

  17. N

    Clearwater, NE annual median income by work experience and sex dataset: Aged...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
    + more versions
    Share
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    Neilsberg Research (2025). Clearwater, NE 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/a50b8f48-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
    Clearwater, Nebraska
    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 Clearwater. 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 Clearwater, while the Census reported a median income of $47,500 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 village of Clearwater was not possible.

    - Full-time workers, aged 15 years and older: In Clearwater, among full-time, year-round workers aged 15 years and older, males earned a median income of $63,125, while females earned $47,083, leading to a 25% gender pay gap among full-time workers. This illustrates that women earn 75 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 Clearwater median household income by race. You can refer the same here

  18. N

    Clifton, TN annual median income by work experience and sex dataset: Aged...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
    + more versions
    Share
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    Close
    Cite
    Neilsberg Research (2025). Clifton, TN 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/a50bdbe1-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
    Tennessee, Clifton
    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 Clifton. 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 Clifton, the median income for all workers aged 15 years and older, regardless of work hours, was $19,696 for males and $23,636 for females.

    Contrary to expectations, women in Clifton, women, regardless of work hours, earn a higher income than men, earning 1.2 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 Clifton, among full-time, year-round workers aged 15 years and older, males earned a median income of $32,845, while females earned $32,543, resulting in a 1% gender pay gap among full-time workers. This illustrates that women earn 99 cents for each dollar earned by men in full-time positions. While this gap shows a trend where women are inching closer to wage parity with men, it also exhibits a noticeable income difference for women working full-time in the city of Clifton.

    Surprisingly, across all roles (including non-full-time employment), women had a higher median income compared to men in Clifton. This might indicate a more favorable income scenario for female workers across different employment patterns within the city of Clifton, especially in non-full-time positions.

    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 Clifton median household income by race. You can refer the same here

  19. T

    Greece Inflation Rate

    • tradingeconomics.com
    • pl.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Oct 9, 2025
    Share
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    Close
    Cite
    TRADING ECONOMICS (2025). Greece Inflation Rate [Dataset]. https://tradingeconomics.com/greece/inflation-cpi
    Explore at:
    csv, excel, json, xmlAvailable download formats
    Dataset updated
    Oct 9, 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, 1960 - Oct 31, 2025
    Area covered
    Greece
    Description

    Inflation Rate in Greece increased to 2 percent in October from 1.90 percent in September of 2025. This dataset provides the latest reported value for - Greece Inflation Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

  20. N

    Saratoga Springs, UT annual median income by work experience and sex...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Neilsberg Research (2025). Saratoga Springs, UT 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/a5357330-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
    Saratoga Springs, Utah
    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 Saratoga Springs. 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 Saratoga Springs, the median income for all workers aged 15 years and older, regardless of work hours, was $78,648 for males and $21,924 for females.

    These income figures highlight a substantial gender-based income gap in Saratoga Springs. Women, regardless of work hours, earn 28 cents for each dollar earned by men. This significant gender pay gap, approximately 72%, underscores concerning gender-based income inequality in the city of Saratoga Springs.

    - Full-time workers, aged 15 years and older: In Saratoga Springs, among full-time, year-round workers aged 15 years and older, males earned a median income of $95,906, while females earned $50,204, leading to a 48% gender pay gap among full-time workers. This illustrates that women earn 52 cents for each dollar earned by men in full-time roles. This level of income gap emphasizes the urgency to address and rectify this ongoing disparity, where women, despite working full-time, face a more significant wage discrepancy compared to men in the same employment roles.

    Remarkably, across all roles, including non-full-time employment, women displayed a similar gender pay gap percentage. This indicates a consistent gender pay gap scenario across various employment types in Saratoga Springs, showcasing a consistent income pattern irrespective of employment status.

    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 Saratoga Springs median household income by race. You can refer the same here

Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
TRADING ECONOMICS (2025). United States Inflation Rate [Dataset]. https://tradingeconomics.com/united-states/inflation-cpi

United States Inflation Rate

United States Inflation Rate - Historical Dataset (1914-12-31/2025-09-30)

Explore at:
146 scholarly articles cite this dataset (View in Google Scholar)
json, excel, xml, csvAvailable download formats
Dataset updated
Oct 24, 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
Dec 31, 1914 - Sep 30, 2025
Area covered
United States
Description

Inflation Rate in the United States increased to 3 percent in September from 2.90 percent in August of 2025. This dataset provides - United States Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

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