100+ datasets found
  1. T

    United States Dollar Data

    • tradingeconomics.com
    • pl.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Aug 1, 2025
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    TRADING ECONOMICS (2025). United States Dollar Data [Dataset]. https://tradingeconomics.com/united-states/currency
    Explore at:
    json, xml, excel, csvAvailable download formats
    Dataset updated
    Aug 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 4, 1971 - Aug 1, 2025
    Area covered
    United States
    Description

    The DXY exchange rate rose to 99.9812 on August 1, 2025, up 0.01% from the previous session. Over the past month, the United States Dollar has strengthened 3.31%, but it's down by 3.13% over the last 12 months. United States Dollar - values, historical data, forecasts and news - updated on August of 2025.

  2. T

    Euro US Dollar Exchange Rate - EUR/USD Data

    • tradingeconomics.com
    • it.tradingeconomics.com
    • +13more
    csv, excel, json, xml
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    TRADING ECONOMICS, Euro US Dollar Exchange Rate - EUR/USD Data [Dataset]. https://tradingeconomics.com/euro-area/currency
    Explore at:
    excel, csv, xml, jsonAvailable 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
    Dec 31, 1957 - Aug 1, 2025
    Area covered
    Euro Area
    Description

    The EUR/USD exchange rate rose to 1.1590 on August 1, 2025, up 1.48% from the previous session. Over the past month, the Euro US Dollar Exchange Rate - EUR/USD has weakened 1.76%, but it's up by 6.24% over the last 12 months. Euro US Dollar Exchange Rate - EUR/USD - values, historical data, forecasts and news - updated on August of 2025.

  3. d

    Foreign Exchange Rates

    • data.world
    csv, zip
    Updated Dec 2, 2024
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    The Associated Press (2024). Foreign Exchange Rates [Dataset]. https://data.world/associatedpress/foreign-exchange-rates
    Explore at:
    zip, csvAvailable download formats
    Dataset updated
    Dec 2, 2024
    Authors
    The Associated Press
    License

    U.S. Government Workshttps://www.usa.gov/government-works
    License information was derived automatically

    Description

    This dataset was generated by parsing PDFs released by the US Treasury for foreign exchange. An edited version (quarterly-edited.csv) includes fixes for typos in the Treasury data.

    Usage caveats from the documentation:

    "Exceptions to using the reporting rates as shown in the report are: * collections and refunds to be valued at specified rates set by international agreements, * conversions of one foreign currency into another, * foreign currencies sold for dollars, and * other types of transactions affecting dollar appropriations. (See Volume I Treasury Financial Manual 2-3200 for further details.)

    Since the exchange rates in this report are not current rates of exchange, they should not be used to value transactions affecting dollar appropriations."

    Additional caveats:

    This unified dataset should be used only for reference or ballpark estimation, and not for anything like automated valuation. The reason is because there's still a lot of messiness involving countries and changing units- when in doubt or if required, please do additional research to confirm the historical rates are indeed as stated.

    Future plans:

    • Clean this up so that it can indeed be used in an automated system for converting currencies
    • Fill in the missing entries
    • Standardize country names and currency names

    Documentation

    Source

  4. T

    Taiwanese Dollar Data

    • tradingeconomics.com
    • ar.tradingeconomics.com
    • +13more
    csv, excel, json, xml
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    TRADING ECONOMICS, Taiwanese Dollar Data [Dataset]. https://tradingeconomics.com/taiwan/currency
    Explore at:
    xml, json, csv, 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
    2025
    Area covered
    Taiwan
    Description

    The USD/TWD exchange rate fell to 29.7090 on August 1, 2025, down 0.70% from the previous session. Over the past month, the Taiwanese Dollar has weakened 2.54%, but it's up by 8.89% over the last 12 months. Taiwanese Dollar - values, historical data, forecasts and news - updated on August of 2025.

  5. T

    Mexican Peso Data

    • tradingeconomics.com
    • tr.tradingeconomics.com
    • +12more
    csv, excel, json, xml
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    TRADING ECONOMICS, Mexican Peso Data [Dataset]. https://tradingeconomics.com/mexico/currency
    Explore at:
    csv, excel, 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
    Apr 17, 1972 - Aug 1, 2025
    Area covered
    Mexico
    Description

    The USD/MXN exchange rate fell to 18.8538 on August 1, 2025, down 0.07% from the previous session. Over the past month, the Mexican Peso has weakened 0.40%, but it's up by 1.41% over the last 12 months. Mexican Peso - values, historical data, forecasts and news - updated on August of 2025.

  6. T

    Canadian Dollar Data

    • tradingeconomics.com
    • fr.tradingeconomics.com
    • +13more
    csv, excel, json, xml
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    TRADING ECONOMICS, Canadian Dollar Data [Dataset]. https://tradingeconomics.com/canada/currency
    Explore at:
    json, xml, excel, 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
    Jan 4, 1971 - Aug 1, 2025
    Area covered
    Canada
    Description

    The USD/CAD exchange rate fell to 1.3786 on August 1, 2025, down 0.52% from the previous session. Over the past month, the Canadian Dollar has weakened 1.45%, but it's up by 0.62% over the last 12 months. Canadian Dollar - values, historical data, forecasts and news - updated on August of 2025.

  7. F

    Nominal Broad U.S. Dollar Index

    • fred.stlouisfed.org
    json
    Updated Jul 28, 2025
    + more versions
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    (2025). Nominal Broad U.S. Dollar Index [Dataset]. https://fred.stlouisfed.org/series/DTWEXBGS
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jul 28, 2025
    License

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

    Description

    Graph and download economic data for Nominal Broad U.S. Dollar Index (DTWEXBGS) from 2006-01-02 to 2025-07-25 about trade-weighted, broad, exchange rate, currency, goods, services, rate, indexes, and USA.

  8. Forex News Annotated Dataset for Sentiment Analysis

    • zenodo.org
    • data.niaid.nih.gov
    csv
    Updated Nov 11, 2023
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    Georgios Fatouros; Georgios Fatouros; Kalliopi Kouroumali; Kalliopi Kouroumali (2023). Forex News Annotated Dataset for Sentiment Analysis [Dataset]. http://doi.org/10.5281/zenodo.7976208
    Explore at:
    csvAvailable download formats
    Dataset updated
    Nov 11, 2023
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Georgios Fatouros; Georgios Fatouros; Kalliopi Kouroumali; Kalliopi Kouroumali
    License

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

    Description

    This dataset contains news headlines relevant to key forex pairs: AUDUSD, EURCHF, EURUSD, GBPUSD, and USDJPY. The data was extracted from reputable platforms Forex Live and FXstreet over a period of 86 days, from January to May 2023. The dataset comprises 2,291 unique news headlines. Each headline includes an associated forex pair, timestamp, source, author, URL, and the corresponding article text. Data was collected using web scraping techniques executed via a custom service on a virtual machine. This service periodically retrieves the latest news for a specified forex pair (ticker) from each platform, parsing all available information. The collected data is then processed to extract details such as the article's timestamp, author, and URL. The URL is further used to retrieve the full text of each article. This data acquisition process repeats approximately every 15 minutes.

    To ensure the reliability of the dataset, we manually annotated each headline for sentiment. Instead of solely focusing on the textual content, we ascertained sentiment based on the potential short-term impact of the headline on its corresponding forex pair. This method recognizes the currency market's acute sensitivity to economic news, which significantly influences many trading strategies. As such, this dataset could serve as an invaluable resource for fine-tuning sentiment analysis models in the financial realm.

    We used three categories for annotation: 'positive', 'negative', and 'neutral', which correspond to bullish, bearish, and hold sentiments, respectively, for the forex pair linked to each headline. The following Table provides examples of annotated headlines along with brief explanations of the assigned sentiment.

    Examples of Annotated Headlines
    
    
        Forex Pair
        Headline
        Sentiment
        Explanation
    
    
    
    
        GBPUSD 
        Diminishing bets for a move to 12400 
        Neutral
        Lack of strong sentiment in either direction
    
    
        GBPUSD 
        No reasons to dislike Cable in the very near term as long as the Dollar momentum remains soft 
        Positive
        Positive sentiment towards GBPUSD (Cable) in the near term
    
    
        GBPUSD 
        When are the UK jobs and how could they affect GBPUSD 
        Neutral
        Poses a question and does not express a clear sentiment
    
    
        JPYUSD
        Appropriate to continue monetary easing to achieve 2% inflation target with wage growth 
        Positive
        Monetary easing from Bank of Japan (BoJ) could lead to a weaker JPY in the short term due to increased money supply
    
    
        USDJPY
        Dollar rebounds despite US data. Yen gains amid lower yields 
        Neutral
        Since both the USD and JPY are gaining, the effects on the USDJPY forex pair might offset each other
    
    
        USDJPY
        USDJPY to reach 124 by Q4 as the likelihood of a BoJ policy shift should accelerate Yen gains 
        Negative
        USDJPY is expected to reach a lower value, with the USD losing value against the JPY
    
    
        AUDUSD
    
        <p>RBA Governor Lowe’s Testimony High inflation is damaging and corrosive </p>
    
        Positive
        Reserve Bank of Australia (RBA) expresses concerns about inflation. Typically, central banks combat high inflation with higher interest rates, which could strengthen AUD.
    

    Moreover, the dataset includes two columns with the predicted sentiment class and score as predicted by the FinBERT model. Specifically, the FinBERT model outputs a set of probabilities for each sentiment class (positive, negative, and neutral), representing the model's confidence in associating the input headline with each sentiment category. These probabilities are used to determine the predicted class and a sentiment score for each headline. The sentiment score is computed by subtracting the negative class probability from the positive one.

  9. T

    Australian Dollar Data

    • tradingeconomics.com
    • zh.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Jul 16, 2025
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    TRADING ECONOMICS (2025). Australian Dollar Data [Dataset]. https://tradingeconomics.com/australia/currency
    Explore at:
    json, excel, csv, xmlAvailable download formats
    Dataset updated
    Jul 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
    Jan 4, 1971 - Aug 1, 2025
    Area covered
    Australia
    Description

    The AUD/USD exchange rate rose to 0.6470 on August 1, 2025, up 0.65% from the previous session. Over the past month, the Australian Dollar has weakened 1.71%, and is down by 0.61% over the last 12 months. Australian Dollar - values, historical data, forecasts and news - updated on August of 2025.

  10. N

    Fall River County, SD 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). Fall River County, SD 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/a51471cc-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
    South Dakota, Fall River County
    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 Fall River County. 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 Fall River County, the median income for all workers aged 15 years and older, regardless of work hours, was $39,662 for males and $25,929 for females.

    These income figures highlight a substantial gender-based income gap in Fall River County. Women, regardless of work hours, earn 65 cents for each dollar earned by men. This significant gender pay gap, approximately 35%, underscores concerning gender-based income inequality in the county of Fall River County.

    - Full-time workers, aged 15 years and older: In Fall River County, among full-time, year-round workers aged 15 years and older, males earned a median income of $49,653, while females earned $67,440

    Surprisingly, within the subset of full-time workers, women earn a higher income than men, earning 1.36 dollars for every dollar earned by men. This suggests that within full-time roles, womens median incomes significantly surpass mens, contrary to broader workforce trends.

    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 Fall River County median household income by race. You can refer the same here

  11. Foreign exchange rates in Canadian dollars, Bank of Canada, monthly

    • www150.statcan.gc.ca
    • open.canada.ca
    • +2more
    Updated May 2, 2017
    + more versions
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    Government of Canada, Statistics Canada (2017). Foreign exchange rates in Canadian dollars, Bank of Canada, monthly [Dataset]. http://doi.org/10.25318/1010000901-eng
    Explore at:
    Dataset updated
    May 2, 2017
    Dataset provided by
    Government of Canadahttp://www.gg.ca/
    Statistics Canadahttps://statcan.gc.ca/en
    Area covered
    Canada
    Description

    This table contains 45 series, with data for years 1950 - 2015 (not all combinations necessarily have data for all years), and was last released on 2016-01-05. This table contains data described by the following dimensions (Not all combinations are available): Geography (1 items: Canada ...), Type of currency (45 items: United States dollar; noon spot rate; average; Danish krone; noon spot rate; average; French franc; noon spot rate; average; Belgian franc; noon spot rate; average ...).

  12. N

    River Falls, AL annual median income by work experience and sex dataset:...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
    + more versions
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    Neilsberg Research (2025). River Falls, AL 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/river-falls-al-income-by-gender/
    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
    River Falls, Alabama
    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 River Falls. 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 River Falls, the median income for all workers aged 15 years and older, regardless of work hours, was $26,510 for males and $27,928 for females.

    Contrary to expectations, women in River Falls, women, regardless of work hours, earn a higher income than men, earning 1.05 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 River Falls, among full-time, year-round workers aged 15 years and older, males earned a median income of $41,705, while females earned $40,066, resulting in a 4% gender pay gap among full-time workers. This illustrates that women earn 96 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 town of River Falls.

    Surprisingly, across all roles (including non-full-time employment), women had a higher median income compared to men in River Falls. This might indicate a more favorable income scenario for female workers across different employment patterns within the town of River Falls, 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 River Falls median household income by race. You can refer the same here

  13. N

    Fall River, KS 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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    Cite
    Neilsberg Research (2025). Fall River, KS 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/fall-river-ks-income-by-gender/
    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
    Kansas, Fall River
    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 Fall River. 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 Fall River, the median income for all workers aged 15 years and older, regardless of work hours, was $31,908 for males and $21,875 for females.

    These income figures highlight a substantial gender-based income gap in Fall River. Women, regardless of work hours, earn 69 cents for each dollar earned by men. This significant gender pay gap, approximately 31%, underscores concerning gender-based income inequality in the city of Fall River.

    - Full-time workers, aged 15 years and older: In Fall River, for full-time, year-round workers aged 15 years and older, the Census reported a median income of $56,250 for females, while data for males was unavailable due to an insufficient number of sample observations.

    As there was no available median income data for males, conducting a comprehensive assessment of gender-based pay disparity in Fall River 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 Fall River median household income by race. You can refer the same here

  14. F

    Gross Domestic Product

    • fred.stlouisfed.org
    • trends.sourcemedium.com
    json
    Updated May 29, 2025
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    (2025). Gross Domestic Product [Dataset]. https://fred.stlouisfed.org/series/GDP
    Explore at:
    jsonAvailable download formats
    Dataset updated
    May 29, 2025
    License

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

    Description

    View economic output, reported as the nominal value of all new goods and services produced by labor and property located in the U.S.

  15. T

    United States Money Supply M0

    • tradingeconomics.com
    • zh.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Jul 22, 2025
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    TRADING ECONOMICS (2025). United States Money Supply M0 [Dataset]. https://tradingeconomics.com/united-states/money-supply-m0
    Explore at:
    json, excel, xml, csvAvailable download formats
    Dataset updated
    Jul 22, 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, 1959 - Jun 30, 2025
    Area covered
    United States
    Description

    Money Supply M0 in the United States increased to 5748600 USD Million in June from 5648700 USD Million in May of 2025. This dataset provides - United States Money Supply M0 - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  16. T

    United States Dollar Data

    • tradingeconomics.com
    • id.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Jul 16, 2025
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    TRADING ECONOMICS (2025). United States Dollar Data [Dataset]. https://tradingeconomics.com/puerto-rico/currency
    Explore at:
    json, excel, xml, csvAvailable download formats
    Dataset updated
    Jul 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
    Jan 4, 1971 - Aug 1, 2025
    Area covered
    Puerto Rico, United States
    Description

    The official currency of Puerto Rico is the US Dollar. This dataset displays a chart with historical values for the US Dollar Index. United States Dollar - values, historical data, forecasts and news - updated on August of 2025.

  17. N

    Hoosick Falls, NY annual median income by work experience and sex dataset:...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
    + more versions
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    Neilsberg Research (2025). Hoosick Falls, NY 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/hoosick-falls-ny-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
    Hoosick Falls, New York, Hoosick
    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 Hoosick Falls. 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 Hoosick Falls, the median income for all workers aged 15 years and older, regardless of work hours, was $26,354 for males and $29,444 for females.

    Contrary to expectations, women in Hoosick Falls, women, regardless of work hours, earn a higher income than men, earning 1.12 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 Hoosick Falls, among full-time, year-round workers aged 15 years and older, males earned a median income of $73,278, while females earned $51,250, leading to a 30% gender pay gap among full-time workers. This illustrates that women earn 70 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, across all roles (including non-full-time employment), women had a higher median income compared to men in Hoosick Falls. This might indicate a more advantageous income scenario for female workers across different employment patterns within the village of Hoosick Falls, particularly 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 Hoosick Falls median household income by race. You can refer the same here

  18. N

    Cuyahoga Falls, OH 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). Cuyahoga Falls, OH 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/a50e514a-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
    Cuyahoga Falls, Ohio
    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 Cuyahoga Falls. 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 Cuyahoga Falls, the median income for all workers aged 15 years and older, regardless of work hours, was $47,906 for males and $34,483 for females.

    These income figures indicate a substantial gender-based pay disparity, showcasing a gap of approximately 28% between the median incomes of males and females in Cuyahoga Falls. With women, regardless of work hours, earning 72 cents to each dollar earned by men, this income disparity reveals a concerning trend toward wage inequality that demands attention in thecity of Cuyahoga Falls.

    - Full-time workers, aged 15 years and older: In Cuyahoga Falls, among full-time, year-round workers aged 15 years and older, males earned a median income of $58,297, while females earned $52,955, resulting in a 9% gender pay gap among full-time workers. This illustrates that women earn 91 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 Cuyahoga Falls.

    Interestingly, when analyzing income across all roles, including non-full-time employment, the gender pay gap percentage was higher for women compared to men. It appears that full-time employment presents a more favorable income scenario for women compared to other employment patterns in Cuyahoga Falls.

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

  19. N

    Granite Falls Township, Minnesota annual median income by work experience...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
    + more versions
    Share
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    Cite
    Neilsberg Research (2025). Granite Falls Township, Minnesota 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/a5186dc6-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
    Minnesota, Granite Falls 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 Granite Falls 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 Granite Falls township, the median income for all workers aged 15 years and older, regardless of work hours, was $54,167 for males and $34,375 for females.

    These income figures highlight a substantial gender-based income gap in Granite Falls township. Women, regardless of work hours, earn 63 cents for each dollar earned by men. This significant gender pay gap, approximately 37%, underscores concerning gender-based income inequality in the township of Granite Falls township.

    - Full-time workers, aged 15 years and older: In Granite Falls township, among full-time, year-round workers aged 15 years and older, males earned a median income of $54,792, while females earned $58,750

    Surprisingly, within the subset of full-time workers, women earn a higher income than men, earning 1.07 dollars for every dollar earned by men. This suggests that within full-time roles, womens median incomes significantly surpass mens, contrary to broader workforce trends.

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

  20. T

    United States Money Supply M2

    • tradingeconomics.com
    • pl.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Jun 24, 2025
    Share
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    TRADING ECONOMICS (2025). United States Money Supply M2 [Dataset]. https://tradingeconomics.com/united-states/money-supply-m2
    Explore at:
    json, xml, csv, excelAvailable download formats
    Dataset updated
    Jun 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
    Jan 31, 1959 - Jun 30, 2025
    Area covered
    United States
    Description

    Money Supply M2 in the United States increased to 21942 USD Billion in May from 21862.40 USD Billion in April of 2025. This dataset provides - United States Money Supply M2 - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Share
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Click to copy link
Link copied
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Cite
TRADING ECONOMICS (2025). United States Dollar Data [Dataset]. https://tradingeconomics.com/united-states/currency

United States Dollar Data

United States Dollar - Historical Dataset (1971-01-04/2025-08-01)

Explore at:
58 scholarly articles cite this dataset (View in Google Scholar)
json, xml, excel, csvAvailable download formats
Dataset updated
Aug 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 4, 1971 - Aug 1, 2025
Area covered
United States
Description

The DXY exchange rate rose to 99.9812 on August 1, 2025, up 0.01% from the previous session. Over the past month, the United States Dollar has strengthened 3.31%, but it's down by 3.13% over the last 12 months. United States Dollar - values, historical data, forecasts and news - updated on August of 2025.

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