100+ datasets found
  1. Meta: annual revenue and net income 2007-2024

    • statista.com
    • ai-chatbox.pro
    Updated Jan 31, 2025
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    Statista (2025). Meta: annual revenue and net income 2007-2024 [Dataset]. https://www.statista.com/statistics/277229/facebooks-annual-revenue-and-net-income/
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    Dataset updated
    Jan 31, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    In 2024, Meta Platforms generated a revenue of over 164 billion U.S. dollars, up from 134 billion USD in 2023. The majority of Meta’s profits come from its advertising revenue.Meta’s total Family of Apps revenue for 2022 amounted to 114 billion U.S. dollars. Additionally, Meta’s Reality Labs, the company’s VR division, generated around 2.1 billion dollars. Meta’s marketing expenditure for 2022 amounted to just over 15 billion U.S. dollars, up from 14 billion U.S. dollars in the previous year. Increasing audience base despite privacy misgivings Meta’s user numbers have continued to grow steadily throughout past years. In the fourth quarter of 2022, there was a total of 3.74 billion worldwide users across all of Meta’s platforms. For this same time frame, the company recorded 407 million monthly active users across Europe. Downloads of Meta’s app Oculus, for which virtual reality headsets are required, increased greatly from 2020 to 2021, reaching a total of 10.62 million downloads by the end of last year. Up until 2021, downloads had grown in a steady manner but from 2020 to 2021, they more than doubled.User numbers have increased despite data security issues and past controversy such as the Cambridge Analytica scandal in 2018. There remains skepticism surrounding the idea of the metaverse in which Meta aims to immerse itself. Of surveyed adults in the United States, the majority said that they were concerned about their privacy if Meta were to succeed in creating the metaverse.

  2. F

    Employed full time: Median usual weekly real earnings: Wage and salary...

    • fred.stlouisfed.org
    json
    Updated Jan 22, 2025
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    (2025). Employed full time: Median usual weekly real earnings: Wage and salary workers: 16 years and over: White: Men [Dataset]. https://fred.stlouisfed.org/series/LEU0252884000A
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    jsonAvailable download formats
    Dataset updated
    Jan 22, 2025
    License

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

    Description

    Graph and download economic data for Employed full time: Median usual weekly real earnings: Wage and salary workers: 16 years and over: White: Men (LEU0252884000A) from 2000 to 2024 about full-time, males, salaries, workers, earnings, white, 16 years +, wages, median, real, employment, and USA.

  3. F

    Employed full time: Median usual weekly real earnings: Wage and salary...

    • fred.stlouisfed.org
    json
    Updated Apr 16, 2025
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    (2025). Employed full time: Median usual weekly real earnings: Wage and salary workers: 16 years and over: Women [Dataset]. https://fred.stlouisfed.org/series/LEU0252882800Q
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    jsonAvailable download formats
    Dataset updated
    Apr 16, 2025
    License

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

    Description

    Graph and download economic data for Employed full time: Median usual weekly real earnings: Wage and salary workers: 16 years and over: Women (LEU0252882800Q) from Q1 1979 to Q1 2025 about females, full-time, salaries, workers, earnings, 16 years +, wages, median, real, employment, and USA.

  4. u

    Income and Earnings by Tracts 2018

    • gstore.unm.edu
    Updated Mar 6, 2020
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    (2020). Income and Earnings by Tracts 2018 [Dataset]. https://gstore.unm.edu/apps/rgis/datasets/307efd60-d30d-4ddd-b683-8cfd1d606ecd/metadata/ISO-19115:2003.html
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    Dataset updated
    Mar 6, 2020
    Time period covered
    2018
    Area covered
    West Bound -109.050173 East Bound -103.001964 North Bound 37.000293 South Bound 31.332172
    Description

    A broad and generalized selection of 2014-2018 US Census Bureau 2018 5-year American Community Survey race, ethnicity and citizenship data estimates, obtained via Census API and joined to the appropriate geometry (in this case, New Mexico Census tracts). The selection is not comprehensive, but allows a first-level characterization of the household income, median household income by race and by age group, Social Security income, the GINI Index, per capita income, median family income, and median household earnings by age, and by education level, in New Mexico. The determination of which estimates to include was based upon level of interest and providing a manageable dataset for users.The U.S. Census Bureau's American Community Survey (ACS) is a nationwide, continuous survey designed to provide communities with reliable and timely demographic, housing, social, and economic data every year. The ACS collects long-form-type information throughout the decade rather than only once every 10 years. The ACS combines population or housing data from multiple years to produce reliable numbers for small counties, neighborhoods, and other local areas. To provide information for communities each year, the ACS provides 1-, 3-, and 5-year estimates. ACS 5-year estimates (multiyear estimates) are “period” estimates that represent data collected over a 60-month period of time (as opposed to “point-in-time” estimates, such as the decennial census, that approximate the characteristics of an area on a specific date). ACS data are released in the year immediately following the year in which they are collected. ACS estimates based on data collected from 2009–2014 should not be called “2009” or “2014” estimates. Multiyear estimates should be labeled to indicate clearly the full period of time. While the ACS contains margin of error (MOE) information, this dataset does not. Those individuals requiring more complete data are directed to download the more detailed datasets from the ACS American FactFinder website. This dataset is organized by Census tract boundaries in New Mexico. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2010 Census Participant Statistical Areas Program. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of census data and comparison back to previous decennial censuses. Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. State and county boundaries always are census tract boundaries in the standard census geographic hierarchy. In a few rare instances, a census tract may consist of noncontiguous areas. These noncontiguous areas may occur where the census tracts are coextensive with all or parts of legal entities that are themselves noncontiguous. For the 2010 Census, the census tract code range of 9400 through 9499 was enforced for census tracts that include a majority American Indian population according to Census 2000 data and/or their area was primarily covered by federally recognized American Indian reservations and/or off-reservation trust lands; the code range 9800 through 9899 was enforced for those census tracts that contained little or no population and represented a relatively large special land use area such as a National Park, military installation, or a business/industrial park; and the code range 9900 through 9998 was enforced for those census tracts that contained only water area, no land area. NOTE: A '-666666666' entry indicates that either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.

  5. X/Twitter: quarterly net income 2012-2022

    • statista.com
    Updated Sep 25, 2023
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    Statista (2023). X/Twitter: quarterly net income 2012-2022 [Dataset]. https://www.statista.com/statistics/299119/twitter-net-income-quarterly/
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    Dataset updated
    Sep 25, 2023
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    In the last reported quarter, social network X/Twitter had a net loss of 270 million U.S. dollars, down from a net income of 513 million U.S. dollars in the first quarter of 2022.In 2020, the decline in revenue was due to an advertising slump caused by the outbreak of the global coronavirus pandemic, which led the company to recognize a deferred tax asset valuation allowance of 1.1 billion U.S. and a non-cash income tax expense based primarily on cumulative taxable losses driven primarily by COVID-19.

  6. Earnings and hours worked, age group: ASHE Table 6

    • ons.gov.uk
    • cy.ons.gov.uk
    zip
    Updated Oct 29, 2024
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    Office for National Statistics (2024). Earnings and hours worked, age group: ASHE Table 6 [Dataset]. https://www.ons.gov.uk/employmentandlabourmarket/peopleinwork/earningsandworkinghours/datasets/agegroupashetable6
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    zipAvailable download formats
    Dataset updated
    Oct 29, 2024
    Dataset provided by
    Office for National Statisticshttp://www.ons.gov.uk/
    License

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

    Description

    Annual estimates of paid hours worked and earnings for UK employees by sex, and full-time and part-time, by age group.

  7. F

    Employed full time: Median usual weekly nominal earnings (second quartile):...

    • fred.stlouisfed.org
    json
    Updated Jan 22, 2025
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    (2025). Employed full time: Median usual weekly nominal earnings (second quartile): Wage and salary workers: 16 years and over [Dataset]. https://fred.stlouisfed.org/series/LEU0252881500A
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    jsonAvailable download formats
    Dataset updated
    Jan 22, 2025
    License

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

    Description

    Graph and download economic data for Employed full time: Median usual weekly nominal earnings (second quartile): Wage and salary workers: 16 years and over (LEU0252881500A) from 1979 to 2024 about second quartile, full-time, salaries, workers, earnings, 16 years +, wages, median, employment, and USA.

  8. T

    Annual Personal Income for State of Iowa

    • data.iowa.gov
    • datasets.ai
    • +1more
    application/rdfxml +5
    Updated Jan 24, 2020
    + more versions
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    U.S. Department of Commerce, Bureau of Economic Analysis (SAINC1, SAINC4, SAINC5N, and SAINC6N) (2020). Annual Personal Income for State of Iowa [Dataset]. https://data.iowa.gov/w/dxzz-fkf8/9c2r-rgb3?cur=Uww2EdFa-qd&from=nbqIn3pgvss
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    csv, json, tsv, application/rssxml, application/rdfxml, xmlAvailable download formats
    Dataset updated
    Jan 24, 2020
    Dataset authored and provided by
    U.S. Department of Commerce, Bureau of Economic Analysis (SAINC1, SAINC4, SAINC5N, and SAINC6N)
    License

    https://www.usa.gov/government-workshttps://www.usa.gov/government-works

    Area covered
    Iowa
    Description

    This dataset provides annual personal income estimates for State of Iowa produced by the U.S. Bureau of Economic Analysis beginning in 1997. Data includes the following estimates: personal income, per capita personal income, wages and salaries, supplements to wages and salaries, private nonfarm earnings, compensation of employees, average compensation per job, and private nonfarm compensation.

    Personal income is defined as the sum of wages and salaries, supplements to wages and salaries, proprietors’ income, dividends, interest, and rent, and personal current transfer receipts, less contributions for government social insurance. Personal income for Iowa is the income received by, or on behalf of all persons residing in Iowa, regardless of the duration of residence, except for foreign nationals employed by their home governments in Iowa. Per capita personal income is personal income divided by the Census Bureau’s annual midyear (July 1) population estimates.

    Wages and salaries is defined as the remuneration receivable by employees (including corporate officers) from employers for the provision of labor services. It includes commissions, tips, and bonuses; employee gains from exercising stock options; and pay-in-kind. Judicial fees paid to jurors and witnesses are classified as wages and salaries. Wages and salaries are measured before deductions, such as social security contributions, union dues, and voluntary employee contributions to defined contribution pension plans.

    Supplements to wages and salaries consists of employer contributions for government social insurance and employer contributions for employee pension and insurance funds.

    Private nonfarm earnings is the sum of wages and salaries, supplements to wages and salaries, and nonfarm proprietors' income, excluding farm and government.

    Compensation to employees is the total remuneration, both monetary and in kind, payable by employers to employees in return for their work during the period. It consists of wages and salaries and of supplements to wages and salaries. Compensation is presented on an accrual basis - that is, it reflects compensation liabilities incurred by the employer in a given period regardless of when the compensation is actually received by the employee.

    Average compensation per job is compensation of employees divided by total full-time and part-time wage and salary employment.

    Private nonfarm compensation is the sum of wages and salaries and supplements to wages and salaries, excluding farm and government.

    More terms and definitions are available on https://apps.bea.gov/regional/definitions/.

  9. T

    United States - Sources of Revenue: Investment and Property Income for...

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Sep 15, 2020
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    TRADING ECONOMICS (2020). United States - Sources of Revenue: Investment and Property Income for Scientific Research and Development Services, Establishments Exempt from Federal Income Tax Employer Firms [Dataset]. https://tradingeconomics.com/united-states/sources-of-revenue-investment-and-property-income-for-scientific-research-and-development-services-establishments-exempt-from-federal-income-tax-employer-firms-fed-data.html
    Explore at:
    json, xml, excel, csvAvailable download formats
    Dataset updated
    Sep 15, 2020
    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 1, 1976 - Dec 31, 2025
    Area covered
    United States
    Description

    United States - Sources of Revenue: Investment and Property Income for Scientific Research and Development Services, Establishments Exempt from Federal Income Tax Employer Firms was 3395.00000 Mil. of $ in January of 2021, according to the United States Federal Reserve. Historically, United States - Sources of Revenue: Investment and Property Income for Scientific Research and Development Services, Establishments Exempt from Federal Income Tax Employer Firms reached a record high of 3395.00000 in January of 2021 and a record low of 1093.00000 in January of 2020. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Sources of Revenue: Investment and Property Income for Scientific Research and Development Services, Establishments Exempt from Federal Income Tax Employer Firms - last updated from the United States Federal Reserve on July of 2025.

  10. Brazil Average Real Monthly Income: Usual Earnings: North: Acre: 60 Years or...

    • ceicdata.com
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    CEICdata.com (2020). Brazil Average Real Monthly Income: Usual Earnings: North: Acre: 60 Years or More [Dataset]. https://www.ceicdata.com/en/brazil/average-real-monthly-household-income-usual-earning-by-age-north/average-real-monthly-income-usual-earnings-north-acre-60-years-or-more
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    Dataset provided by
    CEIC Data
    License

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

    Time period covered
    Dec 1, 2016 - Dec 1, 2017
    Area covered
    Brazil
    Description

    Brazil Average Real Monthly Income: Usual Earnings: North: Acre: 60 Years or More data was reported at 1,958.000 BRL in 2017. This records a decrease from the previous number of 2,232.000 BRL for 2016. Brazil Average Real Monthly Income: Usual Earnings: North: Acre: 60 Years or More data is updated yearly, averaging 2,095.000 BRL from Dec 2016 (Median) to 2017, with 2 observations. The data reached an all-time high of 2,232.000 BRL in 2016 and a record low of 1,958.000 BRL in 2017. Brazil Average Real Monthly Income: Usual Earnings: North: Acre: 60 Years or More data remains active status in CEIC and is reported by Brazilian Institute of Geography and Statistics. The data is categorized under Brazil Premium Database’s Domestic Trade and Household Survey – Table BR.HF052: Average Real Monthly Household Income: Usual Earning: by Age: North.

  11. a

    Incomes Occupations and Earnings - Seattle Neighborhoods

    • hub.arcgis.com
    • data.seattle.gov
    • +1more
    Updated Mar 8, 2024
    + more versions
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    City of Seattle ArcGIS Online (2024). Incomes Occupations and Earnings - Seattle Neighborhoods [Dataset]. https://hub.arcgis.com/maps/SeattleCityGIS::incomes-occupations-and-earnings-seattle-neighborhoods
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    Dataset updated
    Mar 8, 2024
    Dataset authored and provided by
    City of Seattle ArcGIS Online
    Area covered
    Seattle
    Description

    Table from the American Community Survey (ACS) 5-year series on income and earning related topics for City of Seattle Council Districts, Comprehensive Plan Growth Areas and Community Reporting Areas. Table includes B19025 Aggregate Household Income, B19013 Median Household Income, B19001 Household Income, B19113 Median Family Household Income, B19101 Family Household Income, B19202 Median Nonfamily Household Income, B19201 Nonfamily Household Income, B19301 Per Capita Income/B19313 Aggregate Income/B01001 Sex by Age, C24010 Sex by Occupation of the Civilian Employed Population 16 years and Over, B20017 Median Earnings by Sex by Work Experience for the Population 16 years and over with Earnings, B20001 Sex by Earnings for the Population 16 years and over with Earnings. Data is pulled from block group tables for the most recent ACS vintage and summarized to the neighborhoods based on block group assignment.Table created for and used in the Neighborhood Profiles application.Vintages: 2023ACS Table(s): B19013, B19001, B19113, B19101, B19202, B19201, B19301, B19313, B01001, C24010, B20017, B20001, B19025Data downloaded from: Census Bureau's Explore Census Data The United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2020 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

  12. U.S. mean earnings 2005-2023, by educational attainment

    • statista.com
    • ai-chatbox.pro
    Updated Oct 28, 2024
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    Statista (2024). U.S. mean earnings 2005-2023, by educational attainment [Dataset]. https://www.statista.com/statistics/184242/mean-earnings-by-educational-attainment/
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    Dataset updated
    Oct 28, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In 2023 the mean earnings of Bachelor's degree holders in the United States amounted to 86,970 U.S. dollars. People with higher education degrees tended to earn more than those without. For example, high school graduates, including those with a GED, had mean earnings of 46,720 U.S. dollars.

  13. F

    Income Before Taxes: Wages and Salaries by Deciles of Income Before Taxes:...

    • fred.stlouisfed.org
    json
    Updated Sep 25, 2024
    + more versions
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    (2024). Income Before Taxes: Wages and Salaries by Deciles of Income Before Taxes: Ninth 10 Percent (81st to 90th Percentile) [Dataset]. https://fred.stlouisfed.org/series/CXU900000LB1510M
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    jsonAvailable download formats
    Dataset updated
    Sep 25, 2024
    License

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

    Description

    Graph and download economic data for Income Before Taxes: Wages and Salaries by Deciles of Income Before Taxes: Ninth 10 Percent (81st to 90th Percentile) (CXU900000LB1510M) from 2014 to 2023 about percentile, salaries, tax, wages, income, and USA.

  14. Average annual net earnings in the EU 2013-2023

    • statista.com
    • ai-chatbox.pro
    Updated Mar 10, 2025
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    Statista (2025). Average annual net earnings in the EU 2013-2023 [Dataset]. https://www.statista.com/statistics/1201068/annual-net-earnings-in-the-eu/
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    Dataset updated
    Mar 10, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    European Union, Europe
    Description

    The average annual net earning for an individual in the European Union was 28,000 Euros in 2023, an increase of over 2000 Euros since 2022. The average earning figure may not represent what a normal person earns in the EU, however, as this figure is skewed by regions and individuals which earn higher amounts.

  15. T

    United States - Employed full time: Median usual weekly real earnings: Wage...

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Mar 12, 2018
    + more versions
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    TRADING ECONOMICS (2018). United States - Employed full time: Median usual weekly real earnings: Wage and salary workers: 16 years and over: Men [Dataset]. https://tradingeconomics.com/united-states/employed-full-time-median-usual-weekly-real-earnings-wage-and-salary-workers-16-years-and-over-men-fed-data.html
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    xml, csv, excel, jsonAvailable download formats
    Dataset updated
    Mar 12, 2018
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    Jan 1, 1976 - Dec 31, 2025
    Area covered
    United States
    Description

    United States - Employed full time: Median usual weekly real earnings: Wage and salary workers: 16 years and over: Men was 408.00000 1982-84 CPI Adjusted $ in January of 2025, according to the United States Federal Reserve. Historically, United States - Employed full time: Median usual weekly real earnings: Wage and salary workers: 16 years and over: Men reached a record high of 427.00000 in July of 2020 and a record low of 348.00000 in July of 1994. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Employed full time: Median usual weekly real earnings: Wage and salary workers: 16 years and over: Men - last updated from the United States Federal Reserve on July of 2025.

  16. Income and earnings of RTP in Portugal 2021-2024, by source

    • statista.com
    Updated May 5, 2025
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    Statista (2025). Income and earnings of RTP in Portugal 2021-2024, by source [Dataset]. https://www.statista.com/statistics/1461163/portugal-rtp-s-income-and-earning-by-source/
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    Dataset updated
    May 5, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Portugal
    Description

    RTP, the public television and radio broadcaster, had a total income of 223.2 million euros in 2021. By 2022, this value increased to 230.6 million euros, 185 million euros of which originated in audiovisual contribution. 2023 rose further in income and earnings, with a total of 235.15 million euros, which were extended to 237.85 million euros in 2024. Audiovisual contribution equaled 193.39 million euros in the same year.

  17. T

    Germany - Taxes On Income, Profits And Capital Gains (% Of Revenue)

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Dec 31, 2006
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    TRADING ECONOMICS (2017). Germany - Taxes On Income, Profits And Capital Gains (% Of Revenue) [Dataset]. https://tradingeconomics.com/germany/taxes-on-income-profits-and-capital-gains-percent-of-revenue-wb-data.html
    Explore at:
    excel, xml, csv, jsonAvailable download formats
    Dataset updated
    Dec 31, 2006
    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 1, 1976 - Dec 31, 2025
    Area covered
    Germany
    Description

    Taxes on income, profits and capital gains (% of revenue) in Germany was reported at 18.01 % in 2022, according to the World Bank collection of development indicators, compiled from officially recognized sources. Germany - Taxes on income, profits and capital gains (% of revenue) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

  18. Table 3.11 Income and tax, by sex, region and country

    • gov.uk
    Updated Mar 12, 2025
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    HM Revenue & Customs (2025). Table 3.11 Income and tax, by sex, region and country [Dataset]. https://www.gov.uk/government/statistics/income-and-tax-by-gender-region-and-country-2010-to-2011
    Explore at:
    Dataset updated
    Mar 12, 2025
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    HM Revenue & Customs
    Description

    The information is presented on a region basis for England.

    These statistics are classified as accredited official statistics.

    $CTA

    You can find more information about these statistics and collated tables for the latest and previous tax years on the Statistics about personal incomes page.

    Supporting documentation on the methodology used to produce these statistics is available in the release for each tax year.

  19. N

    Keokuk, IA annual income distribution by work experience and gender dataset:...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
    + more versions
    Share
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    Neilsberg Research (2025). Keokuk, IA annual income distribution by work experience and gender dataset: Number of individuals ages 15+ with income, 2023 // 2025 Edition [Dataset]. https://www.neilsberg.com/insights/keokuk-ia-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
    Keokuk, Iowa
    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, Number of males working full time for a given income bracket, Number of males working part time for a given income bracket, Number of females working full time for a given income bracket, Number of females working part time for a given income bracket
    Measurement technique
    The data presented in this dataset is derived from the latest U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. To portray the number of individuals for both the genders (Male and Female), within each income bracket we conducted an initial analysis and categorization of the American Community Survey data. Households are categorized, and median incomes are reported based on the self-identified gender of the head of the household. 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 the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within Keokuk. The dataset can be utilized to gain insights into gender-based income distribution within the Keokuk population, aiding in data analysis and decision-making..

    Key observations

    • Employment patterns: Within Keokuk, among individuals aged 15 years and older with income, there were 3,125 men and 3,752 women in the workforce. Among them, 1,534 men were engaged in full-time, year-round employment, while 1,226 women were in full-time, year-round roles.
    • Annual income under $24,999: Of the male population working full-time, 13.62% fell within the income range of under $24,999, while 30.18% of the female population working full-time was represented in the same income bracket.
    • Annual income above $100,000: 12.32% of men in full-time roles earned incomes exceeding $100,000, while 4.81% of women in full-time positions earned within this income bracket.
    • Refer to the research insights for more key observations on more income brackets ( Annual income under $24,999, Annual income between $25,000 and $49,999, Annual income between $50,000 and $74,999, Annual income between $75,000 and $99,999 and Annual income above $100,000) and employment types (full-time year-round and part-time)
    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

    Income brackets:

    • $1 to $2,499 or loss
    • $2,500 to $4,999
    • $5,000 to $7,499
    • $7,500 to $9,999
    • $10,000 to $12,499
    • $12,500 to $14,999
    • $15,000 to $17,499
    • $17,500 to $19,999
    • $20,000 to $22,499
    • $22,500 to $24,999
    • $25,000 to $29,999
    • $30,000 to $34,999
    • $35,000 to $39,999
    • $40,000 to $44,999
    • $45,000 to $49,999
    • $50,000 to $54,999
    • $55,000 to $64,999
    • $65,000 to $74,999
    • $75,000 to $99,999
    • $100,000 or more

    Variables / Data Columns

    • Income Bracket: This column showcases 20 income brackets ranging from $1 to $100,000+..
    • Full-Time Males: The count of males employed full-time year-round and earning within a specified income bracket
    • Part-Time Males: The count of males employed part-time and earning within a specified income bracket
    • Full-Time Females: The count of females employed full-time year-round and earning within a specified income bracket
    • Part-Time Females: The count of females employed part-time and earning within a specified income bracket

    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.

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

  20. N

    Anderson, AK annual income distribution by work experience and gender...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
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    Close
    Cite
    Neilsberg Research (2025). Anderson, AK annual income distribution by work experience and gender dataset: Number of individuals ages 15+ with income, 2023 // 2025 Edition [Dataset]. https://www.neilsberg.com/insights/anderson-ak-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
    Anderson
    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, Number of males working full time for a given income bracket, Number of males working part time for a given income bracket, Number of females working full time for a given income bracket, Number of females working part time for a given income bracket
    Measurement technique
    The data presented in this dataset is derived from the latest U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. To portray the number of individuals for both the genders (Male and Female), within each income bracket we conducted an initial analysis and categorization of the American Community Survey data. Households are categorized, and median incomes are reported based on the self-identified gender of the head of the household. 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 the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within Anderson. The dataset can be utilized to gain insights into gender-based income distribution within the Anderson population, aiding in data analysis and decision-making..

    Key observations

    • Employment patterns: Within Anderson, among individuals aged 15 years and older with income, there were 77 men and 50 women in the workforce. Among them, 47 men were engaged in full-time, year-round employment, while 15 women were in full-time, year-round roles.
    • Annual income under $24,999: Of the male population working full-time, 36.17% fell within the income range of under $24,999, while none of the female population working full-time was represented in the same income bracket.
    • Annual income above $100,000: 19.15% of men in full-time roles earned incomes exceeding $100,000, while 20% of women in full-time positions earned within this income bracket.
    • Refer to the research insights for more key observations on more income brackets ( Annual income under $24,999, Annual income between $25,000 and $49,999, Annual income between $50,000 and $74,999, Annual income between $75,000 and $99,999 and Annual income above $100,000) and employment types (full-time year-round and part-time)
    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

    Income brackets:

    • $1 to $2,499 or loss
    • $2,500 to $4,999
    • $5,000 to $7,499
    • $7,500 to $9,999
    • $10,000 to $12,499
    • $12,500 to $14,999
    • $15,000 to $17,499
    • $17,500 to $19,999
    • $20,000 to $22,499
    • $22,500 to $24,999
    • $25,000 to $29,999
    • $30,000 to $34,999
    • $35,000 to $39,999
    • $40,000 to $44,999
    • $45,000 to $49,999
    • $50,000 to $54,999
    • $55,000 to $64,999
    • $65,000 to $74,999
    • $75,000 to $99,999
    • $100,000 or more

    Variables / Data Columns

    • Income Bracket: This column showcases 20 income brackets ranging from $1 to $100,000+..
    • Full-Time Males: The count of males employed full-time year-round and earning within a specified income bracket
    • Part-Time Males: The count of males employed part-time and earning within a specified income bracket
    • Full-Time Females: The count of females employed full-time year-round and earning within a specified income bracket
    • Part-Time Females: The count of females employed part-time and earning within a specified income bracket

    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.

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

Share
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TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Statista (2025). Meta: annual revenue and net income 2007-2024 [Dataset]. https://www.statista.com/statistics/277229/facebooks-annual-revenue-and-net-income/
Organization logo

Meta: annual revenue and net income 2007-2024

Explore at:
60 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Jan 31, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Area covered
Worldwide
Description

In 2024, Meta Platforms generated a revenue of over 164 billion U.S. dollars, up from 134 billion USD in 2023. The majority of Meta’s profits come from its advertising revenue.Meta’s total Family of Apps revenue for 2022 amounted to 114 billion U.S. dollars. Additionally, Meta’s Reality Labs, the company’s VR division, generated around 2.1 billion dollars. Meta’s marketing expenditure for 2022 amounted to just over 15 billion U.S. dollars, up from 14 billion U.S. dollars in the previous year. Increasing audience base despite privacy misgivings Meta’s user numbers have continued to grow steadily throughout past years. In the fourth quarter of 2022, there was a total of 3.74 billion worldwide users across all of Meta’s platforms. For this same time frame, the company recorded 407 million monthly active users across Europe. Downloads of Meta’s app Oculus, for which virtual reality headsets are required, increased greatly from 2020 to 2021, reaching a total of 10.62 million downloads by the end of last year. Up until 2021, downloads had grown in a steady manner but from 2020 to 2021, they more than doubled.User numbers have increased despite data security issues and past controversy such as the Cambridge Analytica scandal in 2018. There remains skepticism surrounding the idea of the metaverse in which Meta aims to immerse itself. Of surveyed adults in the United States, the majority said that they were concerned about their privacy if Meta were to succeed in creating the metaverse.

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