Puerto Rico

The Agri-environmental Indicators—Land domain provides information on the annual evolution of the distribution of agricultural and forest areas, and their sub-components, including irrigated areas, at national, regional and global levels.

Air Data reports are produced from a direct query of the AQS Data Mart. The data represent the best and most recent information available to EPA from state agencies. However, some values may be absent due to incomplete reporting, and some values may change due to quality assurance activities. The AQS database is updated by state, local, and tribal organizations who own and submit the data. Readers are cautioned not to rank order geographic areas based on Air Data reports. Air pollution levels measured at a particular monitoring site are not necessarily representative of the air quality for an entire county or urban area. This report is based on monitor-level summary statistics. Air quality standards for some pollutants (PM2.5 and Pb) allow for combining data from multiple monitors into a site-level summary statistic that can be compared to the standard. In those cases, the site-level statistics may differ from the monitor-level statistics upon which this report is based.

CITE SOURCE OF DATA AS: Kantar/CMAG with analysis by the Wesleyan Media Project. Note: Numbers include ads aired on broadcast television and national cable between September 5 and 27, 2020.  

General aviation operations are defined by the FAA based Source: FAA Operations Network (OPSNET) on the traffic operations counted in the OPSNET. Air Traffic Control data shows federal, non-federal, and military through 2005, while 2006 through 2011 are FAA and contract.    TRANSLATE with xEnglishArabicHebrewPolishBulgarianHindiPortugueseCatalanHmong DawRomanianChinese SimplifiedHungarianRussianChinese TraditionalIndonesianSlovakCzechItalianSlovenianDanishJapaneseSpanishDutchKlingonSwedishEnglishKoreanThaiEstonianLatvianTurkishFinnishLithuanianUkrainianFrenchMalayUrduGermanMalteseVietnameseGreekNorwegianWelshHaitian CreolePersian  TRANSLATE with COPY THE URL BELOW BackEMBED THE SNIPPET BELOW IN YOUR SITEEnable collaborative features and customize widget: Bing Webmaster PortalBack

This program was eventually taken to the National Center for Missing & Exploited Children®, known as NCMEC, with a request for a national initiative. It then became known as America’s Missing: Broadcast Emergency Response or the AMBER Plan, which allows broadcasters and transportation authorities to immediately distribute information about recent child abductions to the public and enables the entire community to assist in the search for, and safe recovery, of the child.

Average commute time per commuter Source:American Community Survey 1-Year Estimates Source Table: S0801

Note: ACS 1-Year Estimates 

Means of Transportation To Work by Age Universe: Workers 16 Years and Over More Information 2005 American Community Survey

The American Community Survey (ACS) is an ongoing survey that provides data every year -- giving communities the current information they need to plan investments and services. The ACS covers a broad range of topics about social, economic, demographic, and housing characteristics of the U.S. population. The 5-year estimates from the ACS are "period" estimates that represent data collected over a period of time. The primary advantage of using multiyear estimates is the increased statistical reliability of the data for less populated areas and small population subgroups.    

The American Community Survey (ACS) is an ongoing survey that provides data every year -- giving communities the current information they need to plan investments and services. Information from the survey generates data that help determine how more than $400 billion in federal and state funds are distributed each year. Housing Characteristics – house heating fuel, housing occupancy, housing value, mortgage status, occupants per room, rent, rooms, selected characteristics, selected monthly owner cost, units in structure, vehicles available, year of move-in, and year structure built.

The American Community Survey (ACS) is an ongoing survey that provides data every year -- giving communities the current information they need to plan investments and services. The 5-year estimates from the ACS are "period" estimates that represent data collected over a period of time. The primary advantage of using multiyear estimates is the increased statistical reliability of the data for less populated areas and small population subgroups. Notes on ACS Estimate:An '-999999999' entry in the estimate and margin of error columns indicates that data for this geographic area cannot be displayed because the number of sample cases is too small.An '(-888888888)' means that the estimate is not applicable or not available.A '-666666666' entry in the estimate column 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.A '-555555555' entry in the margin of error column indicates that the estimate is controlled. A statistical test for sampling variability is not appropriate.A '-333333333' entry in the margin of error column indicates that the median falls in the lowest interval or upper interval of an open-ended distribution. A statistical test is not appropriate.A '-222222222' entry in 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.

The American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities and towns and estimates of housing units for states and counties

Deployment data for terrestrial fixed 25 Mbps/3 Mbps and/or Mobile LTE services by urban and rural areas within each state, the District of Columbia and each county. Note: 2018 State data aggregated from sub-regions value.

Appendix E – Americans Without Access to Fixed Advanced Telecommunications Capability by County

Data cited at: CNBC Around 50 states have been assigned score on more than 60 measures of competitiveness which are  developed with input from a broad and diverse array of business and policy experts, official government sources, the CNBC Global CFO Council and the states themselves. States receive points based on their rankings in each metric. Then we separate those metrics into 10 broad categories, weighted based on how frequently each is used as a selling point in state economic development marketing materials. That way, our study ranks the states based on the criteria they use to sell themselves. This year some states were tied http://www.cnbc.com/top-states-past-year-rankings/  

State Population Totals and Components of Change: 2020-2022 Each year, the United States Census Bureau produces and publishes estimates of the population for the nation, states, counties, state/county equivalents, and Puerto Rico. With each annual release of population estimates, the Population Estimates Program revises and updated the entire time series of estimates from April 1, 2020 to July 1 of the current year.

U.S. Regional Data(MSAs) from Federal Financial Institutions Examination Council NOTE- data series are discontinued at source since 2020Q3

Sugar Data of United States

Between 1980 and 2023, 59 Severe Storm, 12 Winter Storm, 4 Flooding, 9 Drought, 4 Tropical Cyclone, and 2 Freeze billion-dollar disaster events affected Ohio (CPI-adjusted). Note: All Events data has been aggregated.

TOTAL FERTILITY RATE is the sum of the age-specific birth rates (5-year age groups between 10 and 49) for female residents of a specified geographic area (nation, state, county, etc.) during a specified time period (usually a calendar year) multiplied by 5. (NOTE: This rate estimates the number of children a hypothetical cohort of 1,000 females in the specified population would bear if they all went through their childbearing years experiencing the same age-specific birth rates for a specified time period.) Note : 2022 data is provisional

New Privately Owned Housing Units Authorized, Unadjusted Units for Regions, Divisions, and States County data collecting from the link https://www2.census.gov/econ/bps/County/

.

Canada and U.S. General Aviation Fleet, Flight Activity, and Forecast

This dataset is updated with data obtained from Statistics Canada and the U.S. Census Bureau. Trade Data is updated on a monthly and annual basis, with revisions in March, April, May, August and November to previous year's data. Trade Data is available on both product and industry-based versions. The product Trade Data is classified by Harmonized System (HS) codes while the industry data is based on North American Industry Classification System(NAICS) classification codes. Source: Statistics Canada and the U.S.Census Bureau

This data set provides the Estimated numbers of new cancer cases and deaths in 2023. In 2023, 1,958,310 new cancer cases and 609,820 cancer deaths are projected to occur in the United States. 

A case of occupational injury is the case of a worker incurring an occupational injury as a result of an occupational accident. An occupational injury that is fatal is the result of an occupational accident where death occurred within one year from the day of the accident. Data disaggregated by economic activity are provided according to the latest version of the International Standard Industrial Classification of All Economic Activities (ISIC) available for that year. Data may have been regrouped from national classifications, which may not be strictly compatible with ISIC. For more information, refer to the Occupational Safety and Health Statistics (OSH) database description.

A case of occupational injury is the case of a worker incurring an occupational injury as a result of an occupational accident. An occupational injury that is fatal is the result of an occupational accident where death occurred within one year from the day of the accident. For more information, refer to the Occupational Safety and Health Statistics (OSH) database description.

A case of non-fatal occupational injury is the case of a worker incurring an occupational injury as a result of an occupational accident not leading to death. The non-fatal occupational injury entails a loss of working time. Data disaggregated by economic activity are provided according to the latest version of the International Standard Industrial Classification of All Economic Activities (ISIC) available for that year. Data may have been regrouped from national classifications, which may not be strictly compatible with ISIC. For more information, refer to the Occupational Safety and Health Statistics (OSH) database description.

A case of non-fatal occupational injury is the case of a worker incurring an occupational injury as a result of an occupational accident not leading to death. The non-fatal occupational injury entails a loss of working time. For more information, refer to the Occupational Safety and Health Statistics (OSH) database description.

Census of Fatal Occupational InjuriesDimensionsData TypeAreaCaseCategorySourceSeasonal

Census of Fatal Occupational InjuriesDimensionsData TypeAreaCaseCategorySource

Census of Fatal Occupational InjuriesDimensionsData TypeAreaEventCaseCategorySeasonal

Census of Fatal Occupational InjuriesDimensionsData TypeAreaEventCaseCategory

Census of Fatal Occupational InjuriesDimensionsData TypeAreaIndustryCaseCategorySeasonal

Census of Fatal Occupational InjuriesDimensionsData TypeAreaIndustryCaseCategory

Census of Fatal Occupational InjuriesDimensionsData TypeAreaOccupationCaseCategorySeasonal

Census of Fatal Occupational InjuriesDimensionsData TypeAreaOccupationCaseCategory

Change-of-Address Stats on USPS FOIA Website

Program Overview:The Common Core of Data (CCD) nonfiscal surveys consist of data submitted annually to the National Center for Education Statistics (NCES) by state education agencies (SEAs) in the 50 states, the District of Columbia, Puerto Rico, the four US Island Areas (American Samoa, Guam, the Commonwealth of the Northern Mariana Islands, and the US Virgin Islands), the Department of Defense Education Activity (DoDEA), and the Bureau of Indian Education (BIE). In order to provide data comparable across states, NCES and representatives of SEAs have worked since the 1950s to develop and accept common data items and definitions. SEAs report school-, agency-, and state-level education data for the CCD through the US Department of Education's EDFacts collection system. CCD survey staff edits the data to produce the final data file, which NCES uses to construct general-purpose publications and specialized reports. The principal users of CCD nonfiscal data are the federal government; the education research community; state and local government officials, including school boards and LEA administrators; and the general public.   Guidelines for Missing, Not Applicable, and Suppression Code Values: For Numeric Data: -1 denotes missing, not available, or not reported data items. -2 denotes "not applicable" data items. -9 indicates suppressed data because it failed the multi-year edit.        

Note: Effective September 27, 2023, this dataset will no longer be updated.  This dataset shows health conditions and contributing causes mentioned in conjunction with deaths involving coronavirus disease 2019 (COVID-19).   Number of conditions reported in this table are tabulated from deaths received and coded as of the date of analysis and do not represent all deaths that occurred in that period. Data during this period are incomplete because of the lag in time between when the death occurred and when the death certificate is completed, submitted to NCHS and processed for reporting purposes. This delay can range from 1 week to 8 weeks or more. Conditions contributing to the death were identified using the International Classification of Diseases, Tenth Revision (ICD-10). Deaths involving more than one condition (e.g., deaths involving both diabetes and respiratory arrest) were counted in both totals. To avoid counting the same death multiple times, the numbers for different conditions should not be summated. Deaths with confirmed or presumed COVID-19, coded to ICD–10 code U07.1  

The national conforming loan limit for mortgages that finance single-family one-unit properties increased from $33,000 in the early 1970s to $417,000 for 2006-2008, with limits 50 percent higher for four statutorily-designated high cost areas: Alaska,  Hawaii, Guam, and the U.S. Virgin Islands.  Since 2008, various legislative acts increased the loan limits in certain high-cost areas in the United States.  While some of the legislative initiatives established temporary limits for loans originated in select time periods, a permanent formula was established under the Housing and Economic Recovery Act of 2008 (HERA).  The 2021 loan limits have been set under the HERA formula. 

Note: Industry classification is based on North American Industry Classification System (NAICS). County Business Patterns (CBP) is an annual series that provides sub-national economic data by industry. This series includes the number of establishments, employment during the week of March 12, first quarter payroll, and annual payroll. This data is useful for studying the economic activity of small areas, analyzing economic changes over time, and as a benchmark for other statistical series, surveys, and databases between economic censuses. Businesses use the data for analyzing market potential, measuring the effectiveness of sales and advertising programs, setting sales quotas, and developing budgets. Government agencies use the data for administration and planning.

These Community Mobility Reports aim to provide insights into what has changed in response to policies aimed at combating COVID-19. The reports chart movement trends over time by geography, across different categories of places such as retail and recreation, groceries and pharmacies, parks, transit stations, workplaces, and residential.

Data cited at: Homebase https://joinhomebase.com/data/covid-19/. This dataset is based on Homebase data covering 60,000 businesses and 1 million hourly employees active in these metropolitan areas in January 2020.   All the rates compare that day vs. the median for that day of the week for the period Jan 4, 2020 – Jan 31, 2020. In other words, they show the extent to which Covid-19 has impacted Main St. as compared to pre-Covid levels. 

Data cited at: COVID-19 Vaccine Projections https://covid19-projections.com/path-to-herd-immunity/

U.S. Regional Data from CredAbility Nonprofit Credit Counseling & Education

Citation: S.Gibson,B.Harris,N.Waters,K.Genthon,M.Hamilton,&D.Robinson,eds.Lastupdated8July2022CSPSTAT, Accessed on July 2022. https://www.courtstatistics.org/

Days lost due to temporary incapacity refers to the total number of calendar days during which those persons temporarily incapacitated were unable to work, excluding the day of the accident, up to a maximum of one year. Temporary absences from work of less than one day for medical treatment are not included. Data disaggregated by economic activity are provided according to the latest version of the International Standard Industrial Classification of All Economic Activities (ISIC) available for that year. Data may have been regrouped from national classifications, which may not be strictly compatible with ISIC. For more information, refer to the Occupational Safety and Health Statistics (OSH) database description.

Days lost due to temporary incapacity refers to the total number of calendar days during which those persons temporarily incapacitated were unable to work, excluding the day of the accident, up to a maximum of one year. Temporary absences from work of less than one day for medical treatment are not included. For more information, refer to the Occupational Safety and Health Statistics (OSH) database description.

Days not worked as a result of strikes and lockouts represent the total number of working days not worked as a result of strikes and lockouts in progress during the year. It is measured in terms of the sum of the actual working days during which work would normally have been carried out by each worker involved had there been no stoppage. Data disaggregated by economic activity are provided according to the latest version of the International Standard Industrial Classification of All Economic Activities (ISIC) available for that year. Data may have been regrouped from national classifications, which may not be strictly compatible with ISIC. For more information, refer to the Industrial Relations data (IRdata) database description.

Debt and state personal income are based on calendar years; pension and retiree health care data are based on states’ own fiscal years. Pension and debt data are shown starting in 2007—the year before the beginning of the 18-month Great Recession. Other post-employment benefits (OPEB) data is reported since fiscal 2008 because states only began publishing the plans’ unfunded obligations in fiscal 2007, and states were still adjusting to the new reporting standards in the first two years. Starting in fiscal 2017, the Governmental Accounting Standards Board implemented new requirements for reporting on the financial standing of state OPEB programs. As a result, Pew is updating its methodology for publishing unfunded OPEB promises for fiscal 2017 and beyond, and this will be reflected in future updates.The size of a state’s liability is expressed as a percentage of personal income. But when expressing how much a state’s liability has changed, such as between 2007 and 2020, the difference between those percentages is measured in percentage points, not percent.

The United Nations Statistics Division collects, compiles and disseminates official demographic and social statistics on a wide range of topics. Data have been collected since 1948 through a set of questionnaires dispatched annually to over 230 national statistical offices and have been published in the Demographic Yearbook collection. The Demographic Yearbook disseminates statistics on population size and composition, births, deaths, marriage and divorce, as well as respective rates, on an annual basis. The Demographic Yearbook census datasets cover a wide range of additional topics including economic activity, educational attainment, household characteristics, housing characteristics, ethnicity, language, foreign-born and foreign population. The available Population and Housing Censuses' datasets reported to UNSD for the censuses conducted worldwide since 1995, are now available in UNdata. This latest update includes several datasets on international travel and migration inflows and outflows, and on incoming and departing international migrants by several characteristics, as reported by the national authorities to the UN Statistics Division for the reference years 2010 to the present as available.

Data prior to 1999 are based on Standard International Trade Classification (SITC) 3. Data from 1999 onwards are based on SITC 4.1 and consistent with the ASEAN Harmonised Tariff Nomenclature (AHTN) 2017 version.

The economic activity index measures average economic growth in the metropolitan area. It is computed using a dynamic factor model that includes 12 variables measuring various aspects of economic activity in the MSA. The index is calibrated to Gross Metropolitan Product (GMP) growth and variance to allow for comparison across metro areas.

This report marks the thirteenth school year for which the U.S. Department of Education (ED) has collected annual performance data from all states for the Education for Homeless Children and Youth (EHCY) program. The EDFacts Submission System allows for the collection of un-duplicated data on students who experienced homelessness and were reported as enrolled in public schools, even if they attend more than one local educational agency (LEA) during the school year. This report draws from that data to provide the only publicly available compilation of un-duplicated data for the EHCY program. The number of homeless students enrolled in public school districts and reported by state educational agencies (SEAs) during School Year (SY) 2016-17 was 1,355,821. This total is not intended to indicate the prevalence of children and youth experiencing homelessness, as it only includes those students who are enrolled in public school districts or LEAs. It does not capture school-aged children and youth who experience homelessness during the summer only, those who dropped out of school, or young children who are not enrolled in preschool programs administered by LEAs.

Educational Attainment, U.S.

The dataset is about reported electric emergency incidents and disturbances. Note: This dataset is collected from "https://knoema.com/eqdpivf" using aggregation method present in knoema.

Figures compiled by Auto Alliance with data provided by IHS Markit represent new vehicle registrations between January 1, 2016 - December 31, 2018.

With the aim of promoting international comparability, statistics presented on ILOSTAT are based on standard international definitions wherever feasible and may differ from official national figures. This series is based on the 13th ICLS definitions. For time series comparability, it includes countries that have implemented the 19th ICLS standards, for which data are also available in the Work Statistics -- 19th ICLS (WORK) database. Employees are all those workers who hold paid employment jobs, which are those where the incumbents hold employment contracts which give them a basic remuneration not directly dependent upon the revenue of the unit for which they work. Data disaggregated by economic activity are provided according to the latest version of the International Standard Industrial Classification of All Economic Activities (ISIC) available for that year. Data may have been regrouped from national classifications, which may not be strictly compatible with ISIC. For more information, refer to the Labour Force Statistics (LFS and STLFS) database description.

U.S. Employment by Sector -  Monthly data

Imputed observations are not based on national data, are subject to high uncertainty and should not be used for country comparisons or rankings. The employed comprise all persons of working age who, during a specified brief period, were in one of the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work). The series is part of the ILO modelled estimates and is harmonized to account for differences in national data and scope of coverage, collection and tabulation methodologies as well as for other country-specific factors. For more information, refer to the ILOSTAT pages on concepts and definitions and ILO modelled estimates and projections.

With the aim of promoting international comparability, statistics presented on ILOSTAT are based on standard international definitions wherever feasible and may differ from official national figures. This series is based on the 13th ICLS definitions. For time series comparability, it includes countries that have implemented the 19th ICLS standards, for which data are also available in the Work Statistics -- 19th ICLS (WORK) database. The employed comprise all persons of working age who, during a specified brief period, were in one of the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work). For more information, refer to the Labour Force Statistics (LFS and STLFS) database description.

Imputed observations are not based on national data, are subject to high uncertainty and should not be used for country comparisons or rankings. The employed comprise all persons of working age who, during a specified brief period, were in the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work). Data are disaggregated by economic activity, which refers to the main activity of the establishment in which a person worked during the reference period. The series is part of the ILO modelled estimates and is harmonized to account for differences in national data and scope of coverage, collection and tabulation methodologies as well as for other country-specific factors. For more information, refer to the ILOSTAT pages on concepts and definitions and ILO modelled estimates and projections.

With the aim of promoting international comparability, statistics presented on ILOSTAT are based on standard international definitions wherever feasible and may differ from official national figures. This series is based on the 13th ICLS definitions. For time series comparability, it includes countries that have implemented the 19th ICLS standards, for which data are also available in the Work Statistics -- 19th ICLS (WORK) database. The employed comprise all persons of working age who, during a specified brief period, were in one of the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work). Data disaggregated by economic activity are provided according to the latest version of the International Standard Industrial Classification of All Economic Activities (ISIC) available for that year. Data may have been regrouped from national classifications, which may not be strictly compatible with ISIC. For more information, refer to the Labour Force Statistics (LFS and STLFS) database description.

Imputed observations are not based on national data, are subject to high uncertainty and should not be used for country comparisons or rankings. The employed comprise all persons of working age who, during a specified brief period, were in the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work). Data are disaggregated by occupation according to the latest version of the International Standard Classification of Occupations (ISCO). The series is part of the ILO modelled estimates and is harmonized to account for differences in national data and scope of coverage, collection and tabulation methodologies as well as for other country-specific factors. For more information, refer to the ILOSTAT pages on concepts and definitions and ILO modelled estimates and projections.

With the aim of promoting international comparability, statistics presented on ILOSTAT are based on standard international definitions wherever feasible and may differ from official national figures. This series is based on the 13th ICLS definitions. For time series comparability, it includes countries that have implemented the 19th ICLS standards, for which data are also available in the Work Statistics -- 19th ICLS (WORK) database. The employed comprise all persons of working age who, during a specified brief period, were in one of the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work). Data disaggregated by occupation are provided according to the latest version of the International Standard Classification of Occupations (ISCO). Data may have been regrouped from the national classifications, which may not be strictly compatible with ISCO. For more information, refer to the Labour Force Statistics (LFS and STLFS) database description.

Imputed observations are not based on national data, are subject to high uncertainty and should not be used for country comparisons or rankings. The employed comprise all persons of working age who, during a specified brief period, were in one of the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work). Data are disaggregated by status in employment according to the latest version of the International Standard Classification of Status in Employment (ICSE-93). Status in employment refers to the type of explicit or implicit contract of employment the person has with other persons or organizations. The basic criteria used to define the groups of the classification are the type of economic risk and the type of authority over establishments and other workers which the job incumbents have or will have. The series is part of the ILO modelled estimates and is harmonized to account for differences in national data and scope of coverage, collection and tabulation methodologies as well as for other country-specific factors. For more information, refer to the ILOSTAT pages on concepts and definitions and ILO modelled estimates and projections.

With the aim of promoting international comparability, statistics presented on ILOSTAT are based on standard international definitions wherever feasible and may differ from official national figures. This series is based on the 13th ICLS definitions. For time series comparability, it includes countries that have implemented the 19th ICLS standards, for which data are also available in the Work Statistics -- 19th ICLS (WORK) database. The employed comprise all persons of working age who, during a specified brief period, were in one of the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work). Data disaggregated by status in employment are provided according to the latest version of the International Standard Classification of Status in Employment (ICSE-93). Data may have been regrouped from the national classifications, which may not be strictly compatible with ICSE. For more information, refer to the Labour Force Statistics (LFS and STLFS) database description.

With the aim of promoting international comparability, statistics presented on ILOSTAT are based on standard international definitions wherever feasible and may differ from official national figures. This series is based on the 13th ICLS definitions. For time series comparability, it includes countries that have implemented the 19th ICLS standards, for which data are also available in the Work Statistics -- 19th ICLS (WORK) database. The employed comprise all persons of working age who, during a specified brief period, were in one of the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work). Data disaggregated by level of education are provided on the highest level of education completed, classified according to the International Standard Classification of Education (ISCED). Data may have been regrouped from national classifications, which may not be strictly compatible with ISCED. For more information, refer to the Education and Mismatch Indicators (EMI) database description.

The employed comprise all persons of working age who, during a specified brief period, were in the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work). Data are disaggregated by economic activity, which refers to the main activity of the establishment in which a person worked during the reference period and does not depend on the specific duties or functions of the person's job, but on the characteristics of the economic unit in which this person works. The series is part of the ILO estimates and is harmonized to account for differences in national data and scope of coverage, collection and tabulation methodologies as well as for other country-specific factors. Data for 1991-2016 are estimates while 2017-2021 data are projections. The dataset was updated as of November 2017. For more information, refer to the indicator description and the ILO estimates and projections methodological note.  

The employed comprise all persons of working age who, during a specified brief period, were in one of the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work). Data are disaggregated by level of education, which refers to the highest levelof education completed, classified according to the International Standard Classification of Education (ISCE). For more information, refer to the concepts and definitions page.

The employed comprise all persons of working age who, during a specified brief period, were in one of the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work). Data are disaggregated by weekly hours actually worked, on the basis of the mean number of hours of work per week, and with reference to hours worked in all jobs of employed persons and in all types of working time arrangements (e.g. full-time and part-time). Hours actually worked include (a) direct hours or the time spent carrying out the tasks and duties of a job, (b) related hours, or the time spent maintaining, facilitating or enhancing productive activities (c) down time, or time when a person in a job cannot work due to machinery or process breakdown, accident, lack of supplies or power or Internet access and (d) resting time, or time spent in short periods of rest, relief or refreshment, including tea, coffee or prayer breaks, generally practised by custom or contract according to established norms and/or national circumstances. Hours actually worked excludes time not worked during activities such as: (a) Annual leave, public holidays, sick leave, parental leave or maternity/paternity leave, other leave for personal or family reasons or civic duty, (b) Commuting time between work and home when no productive activity for the job is performed; for paid employment, even when paid by the employer; (c) Time spent in certain educational activities; for paid employment, even when authorized, paid or provided by the employer; (d) Longer breaks distinguished from short resting time when no productive activity is performed (such as meal breaks or natural repose during long trips); for paid employment, even when paid by the employer.

The employed comprise all persons of working age who, during a specified brief period, were in the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work). Data are disaggregated by occupation according to the latest version of the International Standard Classification of Occupations (ISCO). Information on occupation provides a description of the set of tasks and duties which are carried out by, or can be assigned to, one person. The series is part of the ILO estimates and is harmonized to account for differences in national data and scope of coverage, collection and tabulation methodologies as well as for other country-specific factors. Data for 1991-2016 are estimates while 2017-2021 data are projections. The dataset was updated as of November 2017. For more information, refer to the indicator description and the labour force estimates and projections methodological paper.   

The employed comprise all persons of working age who, during a specified brief period, were in the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work). Data are disaggregated by occupation according to the latest version of the International Standard Classification of Occupations (ISCO). For more information, refer to the concepts and definitions page.

The employed comprise all persons of working age who, during a specified brief period, were in one of the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work). Data are disaggregated by status in employment according to the latest version of the International Standard Classification of Status in Employment (ICSE-93). Status in employment refers to the type of explicit or implicit contract of employment the person has with other persons or organizations. The basic criteria used to define the groups of the classification are the type of economic risk and the type of authority over establishments and other workers which the job incumbents have or will have. For more information, refer to the concepts and definitions page.

Imputed observations are not based on national data, are subject to high uncertainty and should not be used for country comparisons or rankings. The employment-to-population ratio expresses the number of persons who are employed as a percent of the total working age population. The series is part of the ILO modelled estimates and is harmonized to account for differences in national data and scope of coverage, collection and tabulation methodologies as well as for other country-specific factors. For more information, refer to the ILOSTAT pages on concepts and definitions and ILO modelled estimates and projections.

With the aim of promoting international comparability, statistics presented on ILOSTAT are based on standard international definitions wherever feasible and may differ from official national figures. This series is based on the 13th ICLS definitions. For time series comparability, it includes countries that have implemented the 19th ICLS standards, for which data are also available in the Work Statistics -- 19th ICLS (WORK) database. The employment-to-population ratio is the number of persons who are employed as a percent of the total of working-age population. For more information, refer to the Labour Force Statistics (LFS and STLFS) database description.

Note: Source has discontinued Energy-related carbon dioxide (CO2) emissions vary significantly across states, whether considered on an absolute or per capita basis. Total state CO2 emissions include those from direct fuel use across all sectors, including residential, commercial, industrial, and transportation, as well as primary fuels consumed for electric generation. The overall size of a state, as well as the available fuels, types of businesses, climate, and population density, play a role in determining the level of both total and per capita emissions. Additionally, each state’s energy system reflects circumstances specific to that state. For example, some states have abundant hydroelectric supplies, while others contain abundant coal resources. This paper presents a basic analysis of the factors that contribute to a state’s CO2 profile. This analysis neither attempts to assess the effect of state policies on absolute emissions levels or on changes over time, nor does it intend to imply that certain policies would be appropriate for a particular state. The term energy-related CO2 emissions includes emissions released at the location where fossil fuels are consumed. Therefore, to the extent that fuels are used in one state to generate electricity that is consumed in another state, emissions are attributed to the former rather than the latter. Analysis attributing emissions to the consumption of electricity, rather than the production of electricity, would yield different results. For feed-stock application, carbon stored in products such as plastics are subtracted from reported emissions for the states where they are produced.

The State Preschool Yearbook is an annual publication which has tracked the funding, access, and policies of state-funded preschool programs since the 2001-2002 school year. The Yearbook seeks to improve the public’s knowledge and understanding of state efforts to expand the availability of high-quality education to young children in the 21st century. We hope that this report will serve as a resource for policymakers, advocates, and researchers to make more informed decisions as state-funded preschool education moves forward to further decades of progress.

The estimated resident population (ERP) is the official measure of the Australian population. This dataset contains annual ERP by country of birth, age and sex at the Australia level. At the state/territory level it is available for Census years only. Population_Estimates:_Concepts,_Sources_and_Methods_2009

The estimated resident population (ERP) is the official measure of the Australian population. This dataset contains annual ERP by country of birth, age and sex at the Australia level. At the state/territory level it is available for Census years only.

These annual statistics provide information on the amount and characteristics of new investments in the United States by foreign investors, including information on the acquisition and establishment of U.S. business enterprises by foreign investors and on the expansion of existing U.S. affiliates of foreign companies to establish new production facilities. 

The Export of Value Added (EVA) dataset illustrates the strength of economy- wide linkages. It provides data on how value added structures and services linkages to trade have evolved over time. Thanks to repeated updating of the GTAP dataset, we have data for both cross border linkages in recent years, and how these have changed since the early 1990s. This serves as the basis for the database, which builds on Christen, Francois, and Hoekman (2012) and Francois, Manchin, and Tomberger (2012). We work with a panel of global input-output data (a set of global social accounting matrices spanning intermittent years from 1992 to 2011) that covers not only key OECD economies, but also a range of developing countries as well. Sector_GMatrix:  This matrix contains the total domestic value added based on linkages. Depending whether rows or columns are considered its sum corresponds to forward (row) or backward (colunn) linkages. Thus reading a row for a given sector (sector presented on the y-axis) provides information about how much this sector went into each sector (on the x-axis) as inputs DomVAshare: This vector denotes the domestic share of value added of gross value of output per sector. GXshare: Denotes the share of each sector in total exports per country based on the gross value of exports. DXshare: Denotes the share of each sector’s exports of total exports per country based on direct value added, ignoring linkages. VXsharefwd: Denotes the total value added in exports based on forward linkages per sector and country. VXsharebwd: Denotes the total value added in exports based on backward linkages. It is obtained by taking the column-sums of matrix H.

Air pollution is considered one of the most pressing environmental and health issues across OECD countries and beyond. According to the World Health Organisation (WHO), exposure to fine particulate matter (PM2.5) has potentially the most significant adverse effects on health compared to other pollutants. PM2.5 can be inhaled and cause serious health problems including both respiratory and cardiovascular disease, having its most severe effects on children and elderly people. Exposure to PM2.5 has been shown to considerably increase the risk of heart disease and stroke in particular. For these reasons, population exposure to (outdoor or ambient) PM2.5 has been identified as an OECD Green Growth headline indicator. The underlying PM2.5 concentrations estimates are taken from van Donkelaar et al. (2016). They have been derived using satellite observations and a chemical transport model, calibrated to global ground-based measurements using Geographically Weighted Regression at 0.01° resolution. The underlying population data, Gridded Population of the World, version 4 (GPWv4) are taken from the Socioeconomic Data and Applications Center (SEDAC) at the NASA. The underlying boundary geometries are taken from the Global Administrative Unit Layers (GAUL) developed by the FAO, and the OECD Territorial Classification, when available. The current version of the database presents much more variation with respect to the previous one. The reason is that the underlying concentration estimates previously included smoothed multi-year averages and interpolations; while in the current version annual concentration estimates are used. Establishing trends of pollution exposure should be done with care, especially at smaller output areas, as their inputs (e.g. underlying data and models) can change from year to year. We recommend using a 3-year moving average for visualisation.

If a search in the StatBank does not return any result, this does not necessarily mean that there is no trade or that the country code is not valid in the particular period. A zero (0) could also imply that the figures are confidential or that the value is less than half of the unit used. From 2006 on the following countries had their belonging to continent changed - Cyprus from Asia to Europe, and Armenia, Georgia, Kyrgyzstan, Kazakhstan, Tajikistan, Turkmenistan and Uzbekistan from Europe to Asia. The total for Trade are/continent includes this change - while in the selections of countries in the pull-down menu for European/Asian countries it is the present classification that will be shown for the whole time period (Cypros belonging to Europe and the other countries to Asia). Statistics Norway do not publish figures for the trade region previously Comecon after 2011. For more information, see About the statisticsMonthly figures are released on the 15th of the month after the observation period (the previous month), or the first subsequent working day. These figures are preliminary. Corresponding yearly figures are published together with the monthly figures for December. With regard to the current year, all the monthly figures are updated in every publication. Final figures for the preceding year are released twice. For the first time in May the following year, while the corrected final figures are published in May one year later.countryEUCroatia is included in the trade with the EU from 2014 on.Palestine (2013-)Previously: West Bank/Gaza Stripe (2001-2012)

If a search in the StatBank does not return any result, this does not necessarily mean that there is no trade or that the country code is not valid in the particular period. A zero (0) could also imply that the figures are confidential or that the value is less than half of the unit used. From 2006 on the following countries had their belonging to continent changed - Cyprus from Asia to Europe, and Armenia, Georgia, Kyrgyzstan, Kazakhstan, Tajikistan, Turkmenistan and Uzbekistan from Europe to Asia. The total for Trade are/continent includes this change - while in the selections of countries in the pull-down menu for European/Asian countries it is the present classification that will be shown for the whole time period (Cypros belonging to Europe and the other countries to Asia). Statistics Norway do not publish figures for the trade region previously Comecon after 2011. For more information, see About the statisticsMonthly figures are released on the 15th of the month after the observation period (the previous month), or the first subsequent working day. These figures are preliminary. Corresponding yearly figures are published together with the monthly figures for December. With regard to the current year, all the monthly figures are updated in every publication. Final figures for the preceding year are released twice. For the first time in May the following year, while the corrected final figures are published in May one year later.countryEUCroatia is included in the trade with the EU from 2014 on.Palestine (2013-)Previously: West Bank/Gaza Stripe (2001-2012)

Methodological explanationsSymbols usedSource: State Statistical Office, Year 2018M12, preliminary data

Methodological explanationsSymbols usedSource: State Statistical OfficeYear2018preliminary data

The incidence rate is the average number of new cases of fatal occupational injury during the calendar year per 100,000 workers in the reference group. Data disaggregated by economic activity are provided according to the latest version of the International Standard Industrial Classification of All Economic Activities (ISIC) available for that year. Data may have been regrouped from national classifications, which may not be strictly compatible with ISIC. For more information, refer to the Occupational Safety and Health Statistics (OSH) database description.

The incidence rate is the average number of new cases of fatal occupational injury during the calendar year per 100,000 workers in the reference group. For more information, refer to the Occupational Safety and Health Statistics (OSH) database description.

The standard calendar quarters have been used, the first quarter (Q1) starts on January 1 and ends on March 31. The second quarter (Q2) goes through April 1 to June 30. The third quarter (Q3) is from July 1 to September 30, and the fourth quarter (Q4) is from October 1 to December 31

The National Risk Index is a dataset and online tool to help illustrate the U.S. communities most at risk for 18 natural hazards: Avalanche, Coastal Flooding, Cold Wave, Drought, Earthquake, Hail, Heat Wave, Hurricane, Ice Storm, Landslide, Lightning, Riverine Flooding, Strong Wind, Tornado, Tsunami, Volcanic Activity, Wildfire, and Winter Weather. The National Risk Index provides relative Risk Index scores and ratings based on data for Expected Annual Loss due to natural hazards, Social Vulnerability, and Community Resilience. Separate scores and ratings are also provided for Expected Annual Loss, Social Vulnerability, and Community Resilience. For the Risk Index and Expected Annual Loss, scores and ratings can be viewed as a composite score for all hazards or individually for each of the 18 hazard types.

.The all candidate summary file contains one record including summary financial information for all candidates who raised or spent money during the period no matter when they are up for election.

Data cited at: Statistics Finland http://www.stat.fi/index_en.html Publication: 004 -- International trade in services by region, 1 000 000 euros http://pxnet2.stat.fi/PXWeb/pxweb/en/StatFin/StatFin__kan__tpulk/statfin_tpulk_pxt_004.px License: http://creativecommons.org/licenses/by/4.0/ The statistics on international trade in goods and services cover international trade in balance of payments terms on the quarterly level. The statistics form a link for goods trade in customs and balance of payments terms, describe the breakdown of quarterly trade in services, and indicate the total exports of goods and services by area. . = Category not applicable. .. = Data not available or too uncertain for presentation, or subject to secrecy. Description of statistics Concepts and definitionsRegion Region and statesYear Year.Data Import The value of imports, 1 000 000 euros.Export The value of exports, 1 000 000 euros.

Month-by-month data for the number of firearms background checks initiated through the NICS from November 1998 to previous month.  The National Instant Criminal Background Check System, or NICS, is all about saving lives and protecting people from harm—by not letting guns fall into the wrong hands. It also ensures the timely transfer of firearms to eligible gun buyers.

Texas Freight Mobility Plan

Data cited at: Global Database of Events, Language, and Tone   The GDELT Event Database records over 300 categories of physical activities around the world, from riots and protests to peace appeals and diplomatic exchanges, georeferenced to the city or mountain top, across the entire planet dating back to January 1, 1979 and updated every 15 minutes. Essentially it takes a sentence like "The United States criticized Russia yesterday for deploying its troops in Crimea, in which a recent clash with its soldiers left 10 civilians injured" and transforms this blurb of unstructured text into three structured database entries, recording US CRITICIZES RUSSIA, RUSSIA TROOP-DEPLOY UKRAINE (CRIMEA), and RUSSIA MATERIAL-CONFLICT CIVILIANS (CRIMEA). Nearly 60 attributes are captured for each event, including the approximate location of the action and those involved. This translates the textual descriptions of world events captured in the news media into codified entries in a grand "global spreadsheet."

Every two years, the Commission publishes Federal Elections, a compilation of the official, certified federal election results obtained from each state’s election office and other official sources.

The maritime transport domain contains quarterly and annual data. Maritime transport data refer to gross weight of goods (in tonnes), passenger movements (in number of passengers) as well as for vessel traffic (in number of vessels and in gross tonnage of vessels). Data for transport of goods transported on Ro-Ro units or in containers are also expressed in number of units or number of TEUs (20 foot equivalent units). Data at regional level (NUTS 2, 1 and 0) are also available. The statistics on maritime transport are collected within Directive 2009/42/EC and Commission Decision 2008/861/EC, as amended by Commission Decision 2010/216/EU of the European Parliament and of the Council of 14 April 2010, by Regulation 1090/2010 of the European Parliament and of the Council of 24 November 2010 and by Commission Delegated Decision 2012/186/EU of 3 February 2012. Data are collected by the national competent authorities in the reporting countries using a variety of data sources, such as port administration systems, national maritime databases, customs databases or questionnaires to ports or shipping agents (see section 20.1). The maritime transport data have been calculated using data collected at port level. The data are displayed at port level, regional level, Maritime Coastal Area (MCA) level and country level. The data are presented in six collections, displaying main annual results, short sea shipping, passengers, goods vessel traffic and regional statistics.

The maritime transport domain contains quarterly and annual data. Maritime transport data refer to gross weight of goods (in tonnes), passenger movements (in number of passengers) as well as for vessel traffic (in number of vessels and in gross tonnage of vessels). Data for transport of goods transported on Ro-Ro units or in containers are also expressed in number of units or number of TEUs (20 foot equivalent units). Data at regional level (NUTS 2, 1 and 0) are also available. The statistics on maritime transport are collected within Directive 2009/42/EC and Commission Decision 2008/861/EC, as amended by Commission Decision 2010/216/EU of the European Parliament and of the Council of 14 April 2010, by Regulation 1090/2010 of the European Parliament and of the Council of 24 November 2010 and by Commission Delegated Decision 2012/186/EU of 3 February 2012. Data are collected by the national competent authorities in the reporting countries using a variety of data sources, such as port administration systems, national maritime databases, customs databases or questionnaires to ports or shipping agents (see section 18.1). The maritime transport data have been calculated using data collected at port level. The data are displayed at port level, regional level, Maritime Coastal Area (MCA) level and country level. The data are presented in six collections, displaying main annual results, short sea shipping, passengers, goods vessel traffic and regional statistics.

The maritime transport domain contains quarterly and annual data. Maritime transport data refer to gross weight of goods (in tonnes), passenger movements (in number of passengers) as well as for vessel traffic (in number of vessels and in gross tonnage of vessels). Data for transport of goods transported on Ro-Ro units or in containers are also expressed in number of units or number of TEUs (20 foot equivalent units). Data at regional level (NUTS 2, 1 and 0) are also available. The statistics on maritime transport are collected within Directive 2009/42/EC and Commission Decision 2008/861/EC, as amended by Commission Decision 2010/216/EU of the European Parliament and of the Council of 14 April 2010, by Regulation 1090/2010 of the European Parliament and of the Council of 24 November 2010 and by Commission Delegated Decision 2012/186/EU of 3 February 2012. Data are collected by the national competent authorities in the reporting countries using a variety of data sources, such as port administration systems, national maritime databases, customs databases or questionnaires to ports or shipping agents (see section 18.1). The maritime transport data have been calculated using data collected at port level. The data are displayed at port level, regional level, Maritime Coastal Area (MCA) level and country level. The data are presented in six collections, displaying main annual results, short sea shipping, passengers, goods vessel traffic and regional statistics.

The maritime transport domain contains quarterly and annual data. Maritime transport data refer to gross weight of goods (in tonnes), passenger movements (in number of passengers) as well as for vessel traffic (in number of vessels and in gross tonnage of vessels). Data for transport of goods transported on Ro-Ro units or in containers are also expressed in number of units or number of TEUs (20 foot equivalent units). Data at regional level (NUTS 2, 1 and 0) are also available. The statistics on maritime transport are collected within Directive 2009/42/EC and Commission Decision 2008/861/EC, as amended by Commission Decision 2010/216/EU of the European Parliament and of the Council of 14 April 2010, by Regulation 1090/2010 of the European Parliament and of the Council of 24 November 2010 and by Commission Delegated Decision 2012/186/EU of 3 February 2012. Data are collected by the national competent authorities in the reporting countries using a variety of data sources, such as port administration systems, national maritime databases, customs databases or questionnaires to ports or shipping agents (see section 20.1). The maritime transport data have been calculated using data collected at port level. The data are displayed at port level, regional level, Maritime Coastal Area (MCA) level and country level. The data are presented in six collections, displaying main annual results, short sea shipping, passengers, goods vessel traffic and regional statistics.

The maritime transport domain contains quarterly and annual data. Maritime transport data refer to gross weight of goods (in tonnes), passenger movements (in number of passengers) as well as for vessel traffic (in number of vessels and in gross tonnage of vessels). Data for transport of goods transported on Ro-Ro units or in containers are also expressed in number of units or number of TEUs (20 foot equivalent units). Data at regional level (NUTS 2, 1 and 0) are also available. The statistics on maritime transport are collected within Directive 2009/42/EC and Commission Decision 2008/861/EC, as amended by Commission Decision 2010/216/EU of the European Parliament and of the Council of 14 April 2010, by Regulation 1090/2010 of the European Parliament and of the Council of 24 November 2010 and by Commission Delegated Decision 2012/186/EU of 3 February 2012. Data are collected by the national competent authorities in the reporting countries using a variety of data sources, such as port administration systems, national maritime databases, customs databases or questionnaires to ports or shipping agents (see section 18.1). The maritime transport data have been calculated using data collected at port level. The data are displayed at port level, regional level, Maritime Coastal Area (MCA) level and country level. The data are presented in six collections, displaying main annual results, short sea shipping, passengers, goods vessel traffic and regional statistics.

The maritime transport domain contains quarterly and annual data. Maritime transport data refer to gross weight of goods (in tonnes), passenger movements (in number of passengers) as well as for vessel traffic (in number of vessels and in gross tonnage of vessels). Data for transport of goods transported on Ro-Ro units or in containers are also expressed in number of units or number of TEUs (20 foot equivalent units). Data at regional level (NUTS 2, 1 and 0) are also available. The statistics on maritime transport are collected within Directive 2009/42/EC and Commission Decision 2008/861/EC, as amended by Commission Decision 2010/216/EU of the European Parliament and of the Council of 14 April 2010, by Regulation 1090/2010 of the European Parliament and of the Council of 24 November 2010 and by Commission Delegated Decision 2012/186/EU of 3 February 2012. Data are collected by the national competent authorities in the reporting countries using a variety of data sources, such as port administration systems, national maritime databases, customs databases or questionnaires to ports or shipping agents (see section 20.1). The maritime transport data have been calculated using data collected at port level. The data are displayed at port level, regional level, Maritime Coastal Area (MCA) level and country level. The data are presented in six collections, displaying main annual results, short sea shipping, passengers, goods vessel traffic and regional statistics.

The maritime transport domain contains quarterly and annual data. Maritime transport data refer to gross weight of goods (in tonnes), passenger movements (in number of passengers) as well as for vessel traffic (in number of vessels and in gross tonnage of vessels). Data for transport of goods transported on Ro-Ro units or in containers are also expressed in number of units or number of TEUs (20 foot equivalent units). Data at regional level (NUTS 2, 1 and 0) are also available. The statistics on maritime transport are collected within Directive 2009/42/EC and Commission Decision 2008/861/EC, as amended by Commission Decision 2010/216/EU of the European Parliament and of the Council of 14 April 2010, by Regulation 1090/2010 of the European Parliament and of the Council of 24 November 2010 and by Commission Delegated Decision 2012/186/EU of 3 February 2012. Data are collected by the national competent authorities in the reporting countries using a variety of data sources, such as port administration systems, national maritime databases, customs databases or questionnaires to ports or shipping agents (see section 18.1). The maritime transport data have been calculated using data collected at port level. The data are displayed at port level, regional level, Maritime Coastal Area (MCA) level and country level. The data are presented in six collections, displaying main annual results, short sea shipping, passengers, goods vessel traffic and regional statistics.

Note-This dataset includes roadways owned by the State highway agency. Excludes roadways owned by State toll, State park and other State agencies. May include roadways not identified by ownership

Note- Federal-Aid Urbanized Area is an area with 50,000 or more persons 

The Impact of Travel on State Economies database contains data on total domestic and international travelers' direct travel spending in the U.S., as well as travel-generated employment, payroll and tax receipts, the estimates are broken out for the total U.S. overall, as well as for each state and the District of Columbia.   Impact of Travel on State Economies of U.S.: Current and Historical Estimates

Imputed observations are not based on national data, are subject to high uncertainty and should not be used for country comparisons or rankings. The inactivity rate is the number of persons of working age outside the labour force (that is, not employed or unemployed) expressed as a percentage of the working-age population. The series is part of the ILO modelled estimates and is harmonized to account for differences in national data and scope of coverage, collection and tabulation methodologies as well as for other country-specific factors. For more information, refer to the ILOSTAT pages on concepts and definitions and ILO modelled estimates and projections.

With the aim of promoting international comparability, statistics presented on ILOSTAT are based on standard international definitions wherever feasible and may differ from official national figures. This series is based on the 13th ICLS definitions. For time series comparability, it includes countries that have implemented the 19th ICLS standards, for which data are also available in the Work Statistics -- 19th ICLS (WORK) database. This indicator conveys the number of persons of working age outside the labour force (that is, not employed or unemployed) expressed as a percentage of the working-age population. For more information, refer to the Labour Force Statistics (LFS and STLFS) database description.

With the aim of promoting international comparability, statistics presented on ILOSTAT are based on standard international definitions wherever feasible and may differ from official national figures. This series is based on the 13th ICLS definitions. For time series comparability, it includes countries that have implemented the 19th ICLS standards, for which data are also available in the Work Statistics -- 19th ICLS (WORK) database. The incidence of part-time employment, also known as the part-time employment rate, represents the percentage of employment that is part time. Part time employment in this table is based on a common definition of less than 35 actual weekly hours worked. It is derived from the indicator on employment by sex and actual weekly hours worked. For more information, refer to the Wages and Working Time Statistics (COND) database description.

Inflow of migrants refer to the number of immigrants who changed their country of usual residence during the reference period. A person's country of usual residence is the country in which the person has a place to live where he or she normally spends the daily period of rest. Temporary travel abroad for purposes of recreation, holiday, business, medical treatment or religious pilgrimage does not entail a change in the country of usual residence. Data are disaggregated by sex and country of origin. A person's country of origin is that from which the person originates, i.e. the country of his or her citizenship (or, in the case of stateless persons, the country of usual residence).

This data deals with premiums written by classes of non-life insurance for the business written in the reporting country.

FIFA is the international governing body of association football, futsal and beach soccer. Its membership comprises 209 national associations. Its headquarters are in Zurich, Switzerland, and its president is Sepp Blatter. FIFA is responsible for the organisation of football's major international tournaments, notably the World Cup.

The international goods and services deficit was $74.6 billion in April, up $14.0 billion from $60.6 billion in March. April exports were $249.0 billion, $9.2 billion less than March exports. April imports were $323.6 billion, $4.8 billion more than March imports. 

The mission of the Internet Crime Complaint Center (IC3) is to provide the public with a reliable and convenient reporting mechanism to submit information to the FBI concerning suspected Internet-facilitated criminal activity and to develop effective alliances with industry partners. Information is processed for investigative and intelligence purposes for law enforcement and public awareness.

This dataset contains the number of first-time freshmen by the state of residence, along with data on the number who graduated from high school the previous year. Institutions with traditional academic year calendar systems (semester, quarter, trimester or 4-1-4) report their enrollment as of October 15 or the official fall reporting date of the institution. Institutions with calendar systems that differ by program or allow continuous enrollment report students that are enrolled at any time between August 1 and October 31. 

This dataset contains the graduation rate status as of 2021 for the cohort of full-time, first-time degree / certificate-seeking undergraduates in both four year and two year institutions. Data for four year institutions include the number of bachelor degree-seeking students who were enrolled in 2011, the number of bachelor degree seeking students who completed any degree / certificate within 150 percent of normal time, the number who completed a bachelor's degree within 100, 125 or 150 percent of normal time, and the number of bachelor's degree-seeking students who transferred out. Data for students seeking a degree / certificate other than a bachelor's degree are also included for four year institutions. Data for two year institutions include the number of full-time, first-time students who were enrolled in 2014, the number of students who completed any degree / certificate within 100 or 150 percent of normal time and the number of students who transferred out. This file has multiple records per institution. Records are uniquely defined by the variables IPEDS ID (UNITID), and the cohort and graduation status within the cohort (GRTYPE). Each record will contain the above data by gender and race / ethnicity. Note: The number of students who completed a degree / certificate within 100 percent of normal time is not available by race / ethnicity and gender. "This file contains the graduation rate status as of August 31, 2017 for the cohort of full-time, first-time degree / certificate-seeking undergraduates in both four year and two year institutions. Data for four year institutions include the number of bachelor degree-seeking students who were enrolled in 2011, the number of bachelor's degree seeking students who completed any degree / certificate within 150 percent of normal time, the number who completed a bachelor's degree within 100, 125 or 150 percent of normal time, and the number of bachelor's degree-seeking students who transferred out . Data for students seeking a degree / certificate other than a bachelor's degree are also included for four year institutions. Data for two year institutions include the number of full-time, first-time students who were enrolled in 2014, the number of students who completed any degree / certificate within 100 or 150 percent of normal time and the number of students who transferred out. This file has multiple records per institution. Records are uniquely defined by the variables IPEDS ID (UNITID), and the cohort and graduation status within the cohort (GRTYPE). Each record will contain the above data by gender and race / ethnicity. Note: The number of students who completed a degree / certificate within 100 percent of normal time is not available by race / ethnicity and gender.

Unduplicated head count: Unduplicated head count of students enrolled over a 12-month period for both undergraduate and graduate levels. These enrollment data are particularly valuable for institutions that use non-traditional calendar systems and offer short-term programs. Because this enrollment measure encompasses an entire year, it provides a more complete picture of the number of students these schools serve. Instructional activity: Instructional activity measured in total credit and/or contact hours delivered by institutions during a 12-month period.  The credit hour and contact hour activity data are used to derive 12-month full-time equivalent (FTE) enrollments for both undergraduate and graduate levels. The graduate level does not include credit hours for doctoral professional practice students.

Abridged Labor Force Survey Under Covid-19 

Imputed observations are not based on national data, are subject to high uncertainty and should not be used for country comparisons or rankings. The labour force comprises all persons of working age who furnish the supply of labour for the production of goods and services during a specified time-reference period. It refers to the sum of all persons of working age who are employed and those who are unemployed. The series is part of the ILO modelled estimates and is harmonized to account for differences in national data and scope of coverage, collection and tabulation methodologies as well as for other country-specific factors. For more information, refer to the ILOSTAT pages on concepts and definitions and ILO modelled estimates and projections.

With the aim of promoting international comparability, statistics presented on ILOSTAT are based on standard international definitions wherever feasible and may differ from official national figures. This series is based on the 13th ICLS definitions. For time series comparability, it includes countries that have implemented the 19th ICLS standards, for which data are also available in the Work Statistics -- 19th ICLS (WORK) database. The labour force is the sum of all persons of working age who are employed and those who are unemployed. For more information, refer to the Labour Force Statistics (LFS and STLFS) database description.

With the aim of promoting international comparability, statistics presented on ILOSTAT are based on standard international definitions wherever feasible and may differ from official national figures. This series is based on the 13th ICLS definitions. For time series comparability, it includes countries that have implemented the 19th ICLS standards, for which data are also available in the Work Statistics -- 19th ICLS (WORK) database. The labour force is the sum of all persons of working age who are employed and those who are unemployed. Data disaggregated by level of education are provided on the highest level of education completed, classified according to the International Standard Classification of Education (ISCED). Data may have been regrouped from national classifications, which may not be strictly compatible with ISCED. For more information, refer to the Education and Mismatch Indicators (EMI) database description.

The labour force comprises all persons of working age who furnish the supply of labour for the production of goods and services during a specified time-reference period. It refers to the sum of all persons of working age who are employed and those who are unemployed. Data are disaggregated by level of education, which refers to the highest level of education completed, classified according to the International Standard Classification of Education (ISCE). For more information, refer to the concepts and definitions page.

Imputed observations are not based on national data, are subject to high uncertainty and should not be used for country comparisons or rankings. The labour force comprises all persons of working age who furnish the supply of labour for the production of goods and services during a specified time-reference period. It refers to the sum of all persons of working age who are employed and those who are unemployed. The series is part of the ILO modelled estimates and is harmonized to account for differences in national data and scope of coverage, collection and tabulation methodologies as well as for other country-specific factors. For more information, refer to the ILOSTAT pages on concepts and definitions and ILO modelled estimates and projections.

With the aim of promoting international comparability, statistics presented on ILOSTAT are based on standard international definitions wherever feasible and may differ from official national figures. This series is based on the 13th ICLS definitions. For time series comparability, it includes countries that have implemented the 19th ICLS standards, for which data are also available in the Work Statistics -- 19th ICLS (WORK) database. The labour force participation rate is the labour force as a percent of the working-age population. The labour force is the sum of all persons of working age who are employed and those who are unemployed. For more information, refer to the Labour Force Statistics (LFS and STLFS) database description.

With the aim of promoting international comparability, statistics presented on ILOSTAT are based on standard international definitions wherever feasible and may differ from official national figures. This series is based on the 13th ICLS definitions. For time series comparability, it includes countries that have implemented the 19th ICLS standards, for which data are also available in the Work Statistics -- 19th ICLS (WORK) database. The labour force participation rate is the labour force as a percent of the working-age population. The labour force is the sum of all persons of working age who are employed and those who are unemployed. Data disaggregated by level of education are provided on the highest level of education completed, classified according to the International Standard Classification of Education (ISCED). Data may have been regrouped from national classifications, which may not be strictly compatible with ISCED. For more information, refer to the Education and Mismatch Indicators (EMI) database description.

Linguistic Diversity Index Data cited at: https://www.worldatlas.com/articles/the-most-linguistically-diverse-countries-in-the-world.html

The living wage shown is the hourly rate that an individual must earn to support their family, if they are the sole provider and are working full-time (2080 hours per year). All values are per adult in a family unless otherwise noted. The state minimum wage is the same for all individuals, regardless of how many dependents they may have. The poverty rate is typically quoted as gross annual income. We have converted it to an hourly wage for the sake of comparison.

Original data link: https://knoema.com/BLS_LA/local-area-unemployment-statistics-u-s

(CDC ID's: y6uv-t34t ,7pb7-w9us ,93k9-hy54) NNDSS - Table II. Lyme disease to Meningococcal - 2016. In this Table, provisional* cases of selected notifiable diseases (1,000 cases reported during the preceding year), and selected low frequency diseases are displayed. The Table includes total number of cases reported in the United States, by region and by states, in accordance with the current method of displaying MMWR data. Data on United States exclude counts from US territories. Note: These are provisional cases of selected national notifiable diseases, from the National Notifiable Diseases Surveillance System (NNDSS). NNDSS data reported by the 50 states, New York City, the District of Columbia, and the U.S. territories are collated and published weekly as numbered tables printed in the back of the Morbidity and Mortality Weekly Report (MMWR). Cases reported by state health departments to CDC for weekly publication are provisional because of ongoing revision of information and delayed reporting. Case counts in this table are presented as they were published in the MMWR issues. Therefore, numbers listed in later MMWR weeks may reflect changes made to these counts as additional information becomes available. Footnotes: C.N.M.I.: Commonwealth of Northern Mariana Islands. U: Unavailable. -: No reported cases. N: Not reportable. NN: Not Nationally Notifiable. NP: Nationally notifiable but not published. Cum: Cumulative year-to-date counts. Med: Median. Max: Maximum. * Case counts for reporting year 2015 and 2016 are provisional and subject to change. For further information on interpretation of these data, see http://wwwn.cdc.gov/nndss/document/ ProvisionalNationaNotifiableDiseasesSurveillanceData20100927.pdf. Data for TB are displayed in Table IV, which appears quarterly. Three low incidence conditions, rubella, rubella congenital, and tetanus, are in Table II to facilitate case count verification with reporting jurisdictions. Data for meningococcal disease, invasive caused by serogroups ACWY; serogroup B; other serogroup; and unknown serogroup are available in Table I.

The maritime transport domain contains quarterly and annual data. Maritime transport data refer to gross weight of goods (in tonnes), passenger movements (in number of passengers) as well as for vessel traffic (in number of vessels and in gross tonnage of vessels). Data for transport of goods transported on Ro-Ro units or in containers are also expressed in number of units or number of TEUs (20 foot equivalent units). Data at regional level (NUTS 2, 1 and 0) are also available. The statistics on maritime transport are collected within Directive 2009/42/EC and Commission Decision 2008/861/EC, as amended by Commission Decision 2010/216/EU of the European Parliament and of the Council of 14 April 2010, by Regulation 1090/2010 of the European Parliament and of the Council of 24 November 2010 and by Commission Delegated Decision 2012/186/EU of 3 February 2012. Data are collected by the national competent authorities in the reporting countries using a variety of data sources, such as port administration systems, national maritime databases, customs databases or questionnaires to ports or shipping agents (see section 20.1). The maritime transport data have been calculated using data collected at port level. The data are displayed at port level, regional level, Maritime Coastal Area (MCA) level and country level. The data are presented in six collections, displaying main annual results, short sea shipping, passengers, goods vessel traffic and regional statistics.

The maritime transport domain contains quarterly and annual data. Maritime transport data refer to gross weight of goods (in tonnes), passenger movements (in number of passengers) as well as for vessel traffic (in number of vessels and in gross tonnage of vessels). Data for transport of goods transported on Ro-Ro units or in containers are also expressed in number of units or number of TEUs (20 foot equivalent units). Data at regional level (NUTS 2, 1 and 0) are also available. The statistics on maritime transport are collected within Directive 2009/42/EC and Commission Decision 2008/861/EC, as amended by Commission Decision 2010/216/EU of the European Parliament and of the Council of 14 April 2010, by Regulation 1090/2010 of the European Parliament and of the Council of 24 November 2010 and by Commission Delegated Decision 2012/186/EU of 3 February 2012. Data are collected by the national competent authorities in the reporting countries using a variety of data sources, such as port administration systems, national maritime databases, customs databases or questionnaires to ports or shipping agents (see section 20.1). The maritime transport data have been calculated using data collected at port level. The data are displayed at port level, regional level, Maritime Coastal Area (MCA) level and country level. The data are presented in six collections, displaying main annual results, short sea shipping, passengers, goods vessel traffic and regional statistics.

The maritime transport domain contains quarterly and annual data. Maritime transport data refer to gross weight of goods (in tonnes), passenger movements (in number of passengers) as well as for vessel traffic (in number of vessels and in gross tonnage of vessels). Data for transport of goods transported on Ro-Ro units or in containers are also expressed in number of units or number of TEUs (20 foot equivalent units). Data at regional level (NUTS 2, 1 and 0) are also available. The statistics on maritime transport are collected within Directive 2009/42/EC and Commission Decision 2008/861/EC, as amended by Commission Decision 2010/216/EU of the European Parliament and of the Council of 14 April 2010, by Regulation 1090/2010 of the European Parliament and of the Council of 24 November 2010 and by Commission Delegated Decision 2012/186/EU of 3 February 2012. Data are collected by the national competent authorities in the reporting countries using a variety of data sources, such as port administration systems, national maritime databases, customs databases or questionnaires to ports or shipping agents (see section 20.1). The maritime transport data have been calculated using data collected at port level. The data are displayed at port level, regional level, Maritime Coastal Area (MCA) level and country level. The data are presented in six collections, displaying main annual results, short sea shipping, passengers, goods vessel traffic and regional statistics.

Mass Layoff StatisticsDimensionsData ElementRegionIndustryData SeriesIndustry Base

With the aim of promoting international comparability, statistics presented on ILOSTAT are based on standard international definitions wherever feasible and may differ from official national figures. This series is based on the 13th ICLS definitions. For time series comparability, it includes countries that have implemented the 19th ICLS standards, for which data are also available in the Work Statistics -- 19th ICLS (WORK) database. The earnings of employees relate to the gross remuneration in cash and in kind paid to employees, as a rule at regular intervals, for time worked or work done together with remuneration for time not worked, such as annual vacation, other type of paid leave or holidays. Earnings exclude employers' contributions in respect of their employees paid to social security and pension schemes and also the benefits received by employees under these schemes. Earnings also exclude severance and termination pay. This is a harmonized series: (1) data reported as weekly, monthly and yearly are converted to hourly using data on average weekly hours if available; and (2) data are converted to U.S. dollars as the common currency, using exchange rates or using purchasing power parity (PPP) rates for private consumption expenditures. The latter series allows for international comparisons by taking account of the differences in relative prices between countries. Data disaggregated by economic activity are provided according to the latest version of the International Standard Industrial Classification of All Economic Activities (ISIC) available for that year. Data may have been regrouped from national classifications, which may not be strictly compatible with ISIC. For more information, refer to the Wages and Working Time Statistics (COND) database description.

With the aim of promoting international comparability, statistics presented on ILOSTAT are based on standard international definitions wherever feasible and may differ from official national figures. This series is based on the 13th ICLS definitions. For time series comparability, it includes countries that have implemented the 19th ICLS standards, for which data are also available in the Work Statistics -- 19th ICLS (WORK) database. Data disaggregated by economic activity are provided according to the latest version of the International Standard Industrial Classification of All Economic Activities (ISIC) available for that year. Data may have been regrouped from national classifications, which may not be strictly compatible with ISIC. For more information, refer to the Labour Force Statistics (LFS and STLFS) database description.

With the aim of promoting international comparability, statistics presented on ILOSTAT are based on standard international definitions wherever feasible and may differ from official national figures. This series is based on the 13th ICLS definitions. For time series comparability, it includes countries that have implemented the 19th ICLS standards, for which data are also available in the Work Statistics -- 19th ICLS (WORK) database. Data on hours of work are presented, whenever possible, on the basis of the average number of hours of work per week, and with reference to hours worked in the main (paid) job regardless of working time arrangements (e.g. full-time and part-time). Data disaggregated by economic activity are provided according to the latest version of the International Standard Industrial Classification of All Economic Activities (ISIC) available for that year. Data may have been regrouped from national classifications, which may not be strictly compatible with ISIC. For more information, refer to the Labour Force Statistics (LFS and STLFS) database description.

With the aim of promoting international comparability, statistics presented on ILOSTAT are based on standard international definitions wherever feasible and may differ from official national figures. This series is based on the 13th ICLS definitions. For time series comparability, it includes countries that have implemented the 19th ICLS standards, for which data are also available in the Work Statistics -- 19th ICLS (WORK) database. Data on hours of work are presented, whenever possible, on the basis of the average number of hours of work per week, and with reference to hours worked in the main (paid) job regardless of working time arrangements (e.g. full-time and part-time). Data disaggregated by economic activity are provided according to the latest version of the International Standard Industrial Classification of All Economic Activities (ISIC) available for that year. Data may have been regrouped from national classifications, which may not be strictly compatible with ISIC. For more information, refer to the Labour Force Statistics (LFS and STLFS) database description.

Imputed observations are not based on national data, are subject to high uncertainty and should not be used for country comparisons or rankings. The median age marks the point where half the group is older than that age and half is younger. The labour force comprises all persons of working age who furnish the supply of labour for the production of goods and services during a specified time-reference period. It refers to the sum of all persons of working age who are employed and those who are unemployed. The series is part of the ILO modelled estimates and is harmonized to account for differences in national data and scope of coverage, collection and tabulation methodologies as well as for other country-specific factors. For more information, refer to the ILOSTAT pages on concepts and definitions and ILO modelled estimates and projections.

The Part D Prescriber PUF is based on information from CMS’s Prescription Drug Event Standard Analytic File, which has final-action claims that are submitted by Medicare Advantage Prescription Drug (MAPD) plans and by stand-alone Prescription Drug Plans (PDP).

The Access Ranking indicates how much access to mental health care exists within a state. The access measures include access to insurance, access to treatment, quality and cost of insurance, access to special education, and workforce availability. A high Access Ranking indicates that a state provides relatively more access to insurance and mental health treatment.

Australia's international merchandise trade statistics record goods which add to or subtract from the stock of material resources of Australia by entering (imports) or leaving (exports) its territory. Goods simply transported through Australia (goods in transit), or temporarily admitted or withdrawn, do not add to or subtract from Australia's stock of material resources and are not included in Australia's international merchandise trade statistics.

Prior to January 2003, merchandise trade data excludes Singapore's merchandise trade with Indonesia.

Data prior to 1999 are based on Standard International Trade Classification (SITC) 3. Data from 1999 onwards are based on SITC 4.1 and consistent with the ASEAN Harmonised Tariff Nomenclature (AHTN) 2017 version.

Australia's international merchandise trade statistics record goods which add to or subtract from the stock of material resources of Australia by entering (imports) or leaving (exports) its territory. Goods simply transported through Australia (goods in transit), or temporarily admitted or withdrawn, do not add to or subtract from Australia's stock of material resources and are not included in Australia's international merchandise trade statistics.

Immigration and emigration in the Netherlands and the administrative corrections by country of birth, sex, age and marital status. Data available from: 1995 Status of the figures: All data recorded in this publication are final data. Changes as from 18 June 2018: The final figures of 2017 have been added. Changes as from 26 April 2018: The underlying coding of classifications used in this table has been adjusted. It is now in line with the standard encoding defined by CBS. The structure and data of the table have been adjusted. The age classification has been simplified: the five-year groups have been removed. This makes the table better suited for the interface of the new StatLine. If you are missing these figures, please contact Infoservice (see section 5). When will new figures be published? The final figures of 2018 will be added in the second quarter of 2019 in this publication.

State Minimum Wage Laws - Basic Minimum Rate, United States

Public transit is a critical part of the economic and social fabric of metropolitan areas. Nearly 30 million trips are made every day using public transit. Almost all of these trips occur in the nation’s 100 largest metro areas, which account for over 95 percent of all transit passenger miles traveled. People take transit for any number of reasons, but one of the most common is to get to work.

We define our day as midnight-to-midnight, Pacific time. Cities represent usage in greater metropolitan areas and are stably defined during this period. In many countries/regions and cities, relative volume has increased since January 13th, consistent with normal, seasonal usage of Apple Maps. Day of week effects are important to normalize as you use this data. Data that is sent from users’ devices to the Maps service is associated with random, rotating identifiers so Apple doesn’t have a profile of your movements and searches. Apple Maps has no demographic information about our users, so we can’t make any statements about the representativeness of our usage against the overall population. This information will be available for a limited time during the COVID‑19 pandemic.

"Difference from national public (NP)" measures the spread between national and respective state or area scores. If a score is higher than the national level, then the difference is positive; and if it is lower than the national level, it is negative.

National Patterns of R&D Resources provides current data on the levels and key trends of the performance and funding of research and experimental development (R&D) in the United States. The National Patterns statistics draw primarily from NCSES's national surveys of the R&D expenditures and funding of the organizations that perform the bulk of U.S. R&D—including businesses, federal and nonfederal government, higher education, and other nonprofit organizations. Additional details on levels and trends are provided by type of R&D performed (i.e., basic research, applied research, and experimental development). The National Patterns data are reported in both current and inflation-adjusted dollars, with comparisons to the historical record for U.S. R&D (back to 1953) and to the corresponding pace of overall U.S. economic growth.

National Population Totals, 18+ years, State wise, U.S. Estimates of the Total Resident Population and Resident Population Age 18 Years and Older for the United States, States, and Puerto Rico

 Case counts for reporting years 2020 and 2021 are provisional and subject to change. Cases are assigned to the reporting jurisdiction submitting the case to e National Notifiable Diseases Surveillance System (NNDSS), if the case's country of usual residence is the U.S., a U.S. territory, unknown, or null (i.e. country not reported); otherwise, the case is assigned to the 'Non-U.S. Residents' category. Country of usual residence is currently not reported by all jurisdictions or for all conditions NNDSS data reported by the 50 states, New York City, the District of Columbia, and the U.S. territories are collated and published weekly asnumbered tables  TRANSLATE with xEnglishArabicHebrewPolishBulgarianHindiPortugueseCatalanHmong DawRomanianChinese SimplifiedHungarianRussianChinese TraditionalIndonesianSlovakCzechItalianSlovenianDanishJapaneseSpanishDutchKlingonSwedishEnglishKoreanThaiEstonianLatvianTurkishFinnishLithuanianUkrainianFrenchMalayUrduGermanMalteseVietnameseGreekNorwegianWelshHaitian CreolePersian  TRANSLATE with COPY THE URL BELOW BackEMBED THE SNIPPET BELOW IN YOUR SITEEnable collaborative features and customize widget: Bing Webmaster PortalBack

Table 2o - Typhoid fever; Vancomycin-intermediate Staphylococcus aureus; Vancomycin-resistant Staphylococcus aureus; Varicella morbidity; Varicella mortality; Vibriosis; Suggested Citation:  Centers for Disease Control and Prevention. National Notifiable Diseases Surveillance System, 2018 Annual Tables of Infectious Disease Data.  Atlanta, GA. CDC Division of Health Informatics and Surveillance, 2019.  Available at: https://www.cdc.gov/nndss/infectious-tables.html, https://www.cdc.gov/nndss/infectious-tables.html.

(CDC ID's: s5s8-d82d ,4y34-2pku) NNDSS - Table II. Babesiosis to Campylobacteriosis - 2016. In this Table, provisional* cases of selected notifiable diseases (1,000 cases reported during the preceding year), and selected low frequency diseases are displayed. The Table includes total number of cases reported in the United States, by region and by states, in accordance with the current method of displaying MMWR data. Data on United States exclude counts from US territories. Note: These are provisional cases of selected national notifiable diseases, from the National Notifiable Diseases Surveillance System (NNDSS). NNDSS data reported by the 50 states, New York City, the District of Columbia, and the U.S. territories are collated and published weekly as numbered tables printed in the back of the Morbidity and Mortality Weekly Report (MMWR). Cases reported by state health departments to CDC for weekly publication are provisional because of ongoing revision of information and delayed reporting. Case counts in this table are presented as they were published in the MMWR issues. Therefore, numbers listed in later MMWR weeks may reflect changes made to these counts as additional information becomes available. Footnotes: C.N.M.I.: Commonwealth of Northern Mariana Islands. U: Unavailable. -: No reported cases. N: Not reportable. NN: Not Nationally Notifiable. NP: Nationally notifiable but not published. Cum: Cumulative year-to-date counts. Med: Median. Max: Maximum. * Case counts for reporting years 2015 and 2016 are provisional and subject to change. For further information on interpretation of these data, see http://wwwn.cdc.gov/nndss/document/ProvisionalNationaNotifiableDiseasesSurveillanceData20100927.pdf. Data for TB are displayed in Table IV, which appears quarterly. Three low incidence conditions, rubella, rubella congenital, and tetanus, are in Table II to facilitate case count verification with reporting jurisdictions.

(CDC ID's: 9ix3-ryt6 ,mpdg-hf57 ,afja-b25e) NNDSS - Table II. Giardiasis to Haemophilus influenza - 2016. In this Table, provisional* cases of selected notifiable diseases (1,000 cases reported during the preceding year), and selected low frequency diseases are displayed. The Table includes total number of cases reported in the United States, by region and by states, in accordance with the current method of displaying MMWR data. Data on United States exclude counts from US territories. Note: These are provisional cases of selected national notifiable diseases, from the National Notifiable Diseases Surveillance System (NNDSS). NNDSS data reported by the 50 states, New York City, the District of Columbia, and the U.S. territories are collated and published weekly as numbered tables printed in the back of the Morbidity and Mortality Weekly Report (MMWR). Cases reported by state health departments to CDC for weekly publication are provisional because of ongoing revision of information and delayed reporting. Case counts in this table are presented as they were published in the MMWR issues. Therefore, numbers listed in later MMWR weeks may reflect changes made to these counts as additional information becomes available. Footnotes: C.N.M.I.: Commonwealth of Northern Mariana Islands. U: Unavailable. -: No reported cases. N: Not reportable. NN: Not Nationally Notifiable. NP: Nationally notifiable but not published. Cum: Cumulative year-to-date counts. Med: Median. Max: Maximum. * Case counts for reporting year 2015 and 2016 are provisional and subject to change. For further information on interpretation of these data, see http://wwwn.cdc.gov/nndss/document/ ProvisionalNationaNotifiableDiseasesSurveillanceData20100927.pdf. Data for TB are displayed in Table IV, which appears quarterly. Three low incidence conditions, rubella, rubella congenital, and tetanus, are in Table II to facilitate case count verification with reporting jurisdictions. Data for H. influenzae (age <5 years for serotype b, nonserotype b, and unknown serotype) are available in Table I.

NNDSS - Table II. Salmonellosis to Shigellosis - 2014.In this Table, all conditions with a 5-year average annual national total of more than or equals 1,000 cases but less than or equals 10,000 cases will be displayed ( 1,000 and _ 10,000). The Table includes total number of cases reported in the United States, by region and by states, in accordance with the current method of displaying MMWR data. Data on United States exclude counts from US territories. Note:These are provisional cases of selected national notifiable diseases, from the National Notifiable Diseases Surveillance System (NNDSS). NNDSS data reported by the 50 states, New York City, the District of Columbia, and the U.S. territories are collated and published weekly as numbered tables printed in the back of the Morbidity and Mortality Weekly Report (MMWR). Cases reported by state health departments to CDC for weekly publication are provisional because of ongoing revision of information and delayed reporting. Case counts in this table are presented as they were published in the MMWR issues. Therefore, numbers listed in later MMWR weeks may reflect changes made to these counts as additional information becomes available. Footnotes:C.N.M.I.: Commonwealth of Northern Mariana Islands. U: Unavailable. -: No reported cases. N: Not reportable. NN: Not Nationally Notifiable Cum: Cumulative year-to-date counts. Med: Median. Max: Maximum. * Case counts for reporting years 2013 and 2014 are provisional and subject to change. For further information on interpretation of these data, see http://wwwn.cdc.gov/nndss/document/ProvisionalNationaNotifiableDiseasesSurveillanceData20100927.pdf. Data for TB are displayed in Table IV, which appears quarterly. Includes E. coli O157:H7; Shiga toxin positive, serogroup non-O157; and Shiga toxin positive, not serogrouped.More information on NNDSS is available at http://wwwn.cdc.gov/nndss/.

These are weekly cases of selected infectious national notifiable diseases, from the National Notifiable Diseases Surveillance System (NNDSS). NNDSS data reported by the 50 states, New York City, the District of Columbia, and the U.S. territories are collated and published weekly as numbered tables. Cases reported by state health departments to CDC for weekly publication are subject to ongoing revision of information and delayed reporting. Therefore, numbers listed in later weeks may reflect changes made to these counts as additional information becomes available. Case counts in the tables are presented as published each week.  Note- https://wonder.cdc.gov/nndss/static/2021/31/2021-31-table1ii.html https://wonder.cdc.gov/nndss/static/2021/31/2021-31-table1kk.html  https://wonder.cdc.gov/nndss/static/2021/31/2021-31-table1ll.html   

Nonfatal cases involving days away from work: selected characteristicsDimensionsData TypeStateCaseCategoryAgeOwnership

Nonfatal cases involving days away from work: selected characteristicsDimensionsData TypeStateCaseCategoryDaytimeOwnership

Nonfatal cases involving days away from work: selected characteristicsDimensionsData TypeStateCaseCategoryGenderOwnership

Nonfatal cases involving days away from work: selected characteristicsDimensionsData TypeStateCaseCategoryHourOwnership

Nonfatal cases involving days away from work: selected characteristicsDimensionsData TypeStateCaseCategoryLosOwnership

Nonfatal cases involving days away from work: selected characteristicsDimensionsData TypeStateCaseCategoryNatureOwnership

Nonfatal cases involving days away from work: selected characteristicsDimensionsData TypeStateCaseCategoryOwnershipPob

Nonfatal cases involving days away from work: selected characteristicsDimensionsData TypeStateCaseCategoryOwnershipRace

Nonfatal cases involving days away from work: selected characteristicsDimensionsData TypeStateCaseCategoryOwnershipSource

Nonfatal cases involving days away from work: selected characteristicsDimensionsData TypeStateCaseCategoryOwnershipSpecial

Nonfatal cases involving days away from work: selected characteristicsDimensionsData TypeStateCaseCategoryOwnershipWeekday

Nonfatal cases involving days away from work: selected characteristicsDimensionsData TypeStateEventCaseCategoryOwnership

Nonfatal cases involving days away from work: selected characteristicsDimensionsData TypeStateIndustryCaseCategoryOwnership

Nonfatal cases involving days away from work: selected characteristicsDimensionsData TypeStateOccupationCaseCategoryOwnership

The incidence rate is the average number of new cases of non-fatal occupational injury during the calendar year per 100,000 workers in the reference group. Data disaggregated by economic activity are provided according to the latest version of the International Standard Industrial Classification of All Economic Activities (ISIC) available for that year. Data may have been regrouped from national classifications, which may not be strictly compatible with ISIC. For more information, refer to the Occupational Safety and Health Statistics (OSH) database description.

The incidence rate is the average number of new cases of non-fatal occupational injury during the calendar year per 100,000 workers in the reference group. For more information, refer to the Occupational Safety and Health Statistics (OSH) database description.

Independent Inventor Utility Patents by Country, State and Year An independent inventor patent is a patent that has ownership that is unassigned or assigned to an individual at the time of grant i.e. ownership of the patent is not assigned to an organization. some U.S. origin patents are assigned to foreign individuals while some foreign origin patents are assigned to U.S. individuals. Therefore, the sum of counts of U.S. origin independent inventor patents usually will not equal the sum of counts of patents owned by "U.S. individuals" and the sum of counts of "foreign origin" independent inventor patents usually will not equal the sum of counts of patents owned by foreign individuals.

A strike is a temporary work stoppage carried out by one or more groups of workers with a view to enforcing or resisting demands or expressing grievances, or supporting other workers in their demands or grievances. A lockout is a total or partial temporary closure of one or more places of employment, or the hindering of the normal work activities of employees, by one or more employers with a view to enforcing or resisting demands or expressing grievances, or supporting other employers in their demands or grievances. Data disaggregated by economic activity are provided according to the latest version of the International Standard Industrial Classification of All Economic Activities (ISIC) available for that year. Data may have been regrouped from national classifications, which may not be strictly compatible with ISIC. For more information, refer to the Industrial Relations data (IRdata) database description.

Occupation Employment StatisticsDimensionsData TypeArea TypeAreaStateSectorIndustryOccupationSeasonal

Occupational Injuries and Illnesses - Characteristics DataDimensionsData TypeStateCaseCategoryAgeOwnershipSeasonal

Occupational Injuries and Illnesses - Characteristics DataDimensionsData TypeStateCaseCategoryDaytimeOwnershipSeasonal

Occupational Injuries and Illnesses - Characteristics DataDimensionsData TypeStateCaseCategoryGenderOwnershipSeasonal

Occupational Injuries and Illnesses - Characteristics DataDimensionsData TypeStateCaseCategoryHourOwnershipSeasonal

Occupational Injuries and Illnesses - Characteristics DataDimensionsData TypeStateCaseCategoryLosOwnershipSeasonal

Occupational Injuries and Illnesses - Characteristics DataDimensionsData TypeStateCaseCategoryNatureOwnershipSeasonal

Occupational Injuries and Illnesses - Characteristics DataDimensionsData TypeStateCaseCategoryOwnershipPobSeasonal

Occupational Injuries and Illnesses - Characteristics DataDimensionsData TypeStateCaseCategoryOwnershipRaceSeasonal

Occupational Injuries and Illnesses - Characteristics DataDimensionsData TypeStateCaseCategoryOwnershipSourceSeasonal

Occupational Injuries and Illnesses - Characteristics DataDimensionsData TypeStateCaseCategoryOwnershipSpecialSeasonal

Occupational Injuries and Illnesses - Characteristics DataDimensionsData TypeStateCaseCategoryOwnershipWeekdaySeasonal

Occupational Injuries and Illnesses - Characteristics DataDimensionsData TypeStateEventCaseCategoryOwnershipSeasonal

Occupational Injuries and Illnesses - Characteristics DataDimensionsData TypeStateIndustryCaseCategoryOwnershipSeasonal

Occupational Injuries and Illnesses - Characteristics DataDimensionsData TypeStateOccupationCaseCategoryOwnershipSeasonal

Occupational Injuries and Illnesses Industry Data (IS)DimensionsData TypeAreaSupersectorIndustryCase TypeSeasonal

Citation:  Gundersen, C., A. Dewey, M. Kato, , A. Crumbaugh & M. Strayer. Map the Meal Gap 2019: A Report on County and Congressional District Food Insecurity and County Food Cost in the United States in 2017. Feeding America, 2019.   Together, federal nutrition programs and the charitable food system weave a comprehensive nutrition safety net reaching food insecure individuals at different income levels and in different settings. Child nutrition programs, in particular, play a critical role in providing quality nutritious meals to millions of children every day for free or at a reduced cost. So in addition to developing overall food insecurity estimates for every county and congressional district, Map the Meal Gap also estimates child food insecurity rates in every county and congressional district in every state in the United States. As with counties, it is important to note that no congressional district is free of food insecurity. It is our hope that food banks, partner agencies, policy makers, business leaders, community activists and concerned citizens will use this information to fully engage in the fight against hunger.

BRFSS: Table of Overweight and Obesity (BMI) Based on Behavioral Risk Factor Surveillance System (BRFSS) Prevalence Data (2011 to present) 2011 to present. BRFSS combined land line and cell phone prevalence data. BRFSS is a continuous, state-based surveillance system that collects information about modifiable risk factors for chronic diseases and other leading causes of death

Passenger (enplanement) and cargo data is extracted from the Air Carrier Activity Information System (ACAIS), a database that contains revenue passenger boarding and all-cargo data. The database supports the FAA's Airport Improvement Program (AIP) apportionment formula calculations. More about the collection and use of passenger and all-cargo data » Passenger boarding and all-cargo data is collected for a full calendar year and determines AIP entitlements for the next full fiscal year (i.e., calendar year 2018 data determines Fiscal Year 2020 entitlement funds).

The maritime transport domain contains quarterly and annual data. Maritime transport data refer to gross weight of goods (in tonnes), passenger movements (in number of passengers) as well as for vessel traffic (in number of vessels and in gross tonnage of vessels). Data for transport of goods transported on Ro-Ro units or in containers are also expressed in number of units or number of TEUs (20 foot equivalent units). Data at regional level (NUTS 2, 1 and 0) are also available. The statistics on maritime transport are collected within Directive 2009/42/EC and Commission Decision 2008/861/EC, as amended by Commission Decision 2010/216/EU of the European Parliament and of the Council of 14 April 2010, by Regulation 1090/2010 of the European Parliament and of the Council of 24 November 2010 and by Commission Delegated Decision 2012/186/EU of 3 February 2012. Data are collected by the national competent authorities in the reporting countries using a variety of data sources, such as port administration systems, national maritime databases, customs databases or questionnaires to ports or shipping agents (see section 20.1). The maritime transport data have been calculated using data collected at port level. The data are displayed at port level, regional level, Maritime Coastal Area (MCA) level and country level. The data are presented in six collections, displaying main annual results, short sea shipping, passengers, goods vessel traffic and regional statistics.

The maritime transport domain contains quarterly and annual data. Maritime transport data refer to gross weight of goods (in tonnes), passenger movements (in number of passengers) as well as for vessel traffic (in number of vessels and in gross tonnage of vessels). Data for transport of goods transported on Ro-Ro units or in containers are also expressed in number of units or number of TEUs (20 foot equivalent units). Data at regional level (NUTS 2, 1 and 0) are also available. The statistics on maritime transport are collected within Directive 2009/42/EC and Commission Decision 2008/861/EC, as amended by Commission Decision 2010/216/EU of the European Parliament and of the Council of 14 April 2010, by Regulation 1090/2010 of the European Parliament and of the Council of 24 November 2010 and by Commission Delegated Decision 2012/186/EU of 3 February 2012. Data are collected by the national competent authorities in the reporting countries using a variety of data sources, such as port administration systems, national maritime databases, customs databases or questionnaires to ports or shipping agents (see section 20.1). The maritime transport data have been calculated using data collected at port level. The data are displayed at port level, regional level, Maritime Coastal Area (MCA) level and country level. The data are presented in six collections, displaying main annual results, short sea shipping, passengers, goods vessel traffic and regional statistics.

The maritime transport domain contains quarterly and annual data. Maritime transport data refer to gross weight of goods (in tonnes), passenger movements (in number of passengers) as well as for vessel traffic (in number of vessels and in gross tonnage of vessels). Data for transport of goods transported on Ro-Ro units or in containers are also expressed in number of units or number of TEUs (20 foot equivalent units). Data at regional level (NUTS 2, 1 and 0) are also available. The statistics on maritime transport are collected within Directive 2009/42/EC and Commission Decision 2008/861/EC, as amended by Commission Decision 2010/216/EU of the European Parliament and of the Council of 14 April 2010, by Regulation 1090/2010 of the European Parliament and of the Council of 24 November 2010 and by Commission Delegated Decision 2012/186/EU of 3 February 2012. Data are collected by the national competent authorities in the reporting countries using a variety of data sources, such as port administration systems, national maritime databases, customs databases or questionnaires to ports or shipping agents (see section 18.1). The maritime transport data have been calculated using data collected at port level. The data are displayed at port level, regional level, Maritime Coastal Area (MCA) level and country level. The data are presented in six collections, displaying main annual results, short sea shipping, passengers, goods vessel traffic and regional statistics.

The maritime transport domain contains quarterly and annual data. Maritime transport data refer to gross weight of goods (in tonnes), passenger movements (in number of passengers) as well as for vessel traffic (in number of vessels and in gross tonnage of vessels). Data for transport of goods transported on Ro-Ro units or in containers are also expressed in number of units or number of TEUs (20 foot equivalent units). Data at regional level (NUTS 2, 1 and 0) are also available. The statistics on maritime transport are collected within Directive 2009/42/EC and Commission Decision 2008/861/EC, as amended by Commission Decision 2010/216/EU of the European Parliament and of the Council of 14 April 2010, by Regulation 1090/2010 of the European Parliament and of the Council of 24 November 2010 and by Commission Delegated Decision 2012/186/EU of 3 February 2012. Data are collected by the national competent authorities in the reporting countries using a variety of data sources, such as port administration systems, national maritime databases, customs databases or questionnaires to ports or shipping agents (see section 18.1). The maritime transport data have been calculated using data collected at port level. The data are displayed at port level, regional level, Maritime Coastal Area (MCA) level and country level. The data are presented in six collections, displaying main annual results, short sea shipping, passengers, goods vessel traffic and regional statistics.

The maritime transport domain contains quarterly and annual data. Maritime transport data refer to gross weight of goods (in tonnes), passenger movements (in number of passengers) as well as for vessel traffic (in number of vessels and in gross tonnage of vessels). Data for transport of goods transported on Ro-Ro units or in containers are also expressed in number of units or number of TEUs (20 foot equivalent units). Data at regional level (NUTS 2, 1 and 0) are also available. The statistics on maritime transport are collected within Directive 2009/42/EC and Commission Decision 2008/861/EC, as amended by Commission Decision 2010/216/EU of the European Parliament and of the Council of 14 April 2010, by Regulation 1090/2010 of the European Parliament and of the Council of 24 November 2010 and by Commission Delegated Decision 2012/186/EU of 3 February 2012. Data are collected by the national competent authorities in the reporting countries using a variety of data sources, such as port administration systems, national maritime databases, customs databases or questionnaires to ports or shipping agents (see section 20.1). The maritime transport data have been calculated using data collected at port level. The data are displayed at port level, regional level, Maritime Coastal Area (MCA) level and country level. The data are presented in six collections, displaying main annual results, short sea shipping, passengers, goods vessel traffic and regional statistics.

Imputed observations are not based on national data, are subject to high uncertainty and should not be used for country comparisons or rankings. Persons outside the labour force comprise all persons of working age who, during the specified reference period, were not in the labour force (that is, were not employed or unemployed). The series is part of the ILO modelled estimates and is harmonized to account for differences in national data and scope of coverage, collection and tabulation methodologies as well as for other country-specific factors. For more information, refer to the ILOSTAT pages on concepts and definitions and ILO modelled estimates and projections.

Imputed observations are not based on national data, are subject to high uncertainty and should not be used for country comparisons or rankings. The total population comprises persons of all ages who were living in the country during the reference period, regardless of residency status or citizenship. The source for the population figures used is World Population Prospects: The 2019 Revision and the rural urban distribution population source is World Urbanization Prospects: The 2014 Revision issued by the United Nations. For more information, refer to the concepts and definitions page.

Imputed observations are not based on national data, are subject to high uncertainty and should not be used for country comparisons or rankings. The total population comprises persons of all ages who were living in the country during the reference period, regardless of residency status or citizenship. The source for the population figures used is World Population Prospects: The 2019 Revision issued by the United Nations. For more information, refer to the concepts and definitions page.

Imputed observations are not based on national data, are subject to high uncertainty and should not be used for country comparisons or rankings. The total population comprises persons of all ages who were living in the country during the reference period, regardless of residency status or citizenship. The source for the population figures used is World Population Prospects: The 2019 Revision and the rural urban distribution population source is World Urbanization Prospects: The 2014 Revision issued by the United Nations. For more information, refer to the concepts and definitions page.

In the United States, state laws require birth certificates to be completed for all births, and Federal law mandates national collection and publication of births and other vital statistics data. The National Vital Statistics System, the Federal compilation of these data, is the result of the cooperation between the National Center for Health Statistics (NCHS) and the states to provide access to national statistical information from birth certificates. For more information, see Birth Data

Prisoners under jurisdiction of state or federal correctional authorities, by jurisdiction and sex, December 31, 2015, 2016, 2017 Prisoners in 2017 Presents final counts of prisoners under the jurisdiction of state and federal correctional authorities at year-end 2017 and includes findings on admissions, releases, and imprisonment rates.

Deaths involving coronavirus disease 2019 (COVID-19), pneumonia and influenza reported to NCHS by place of death and state, United States.

With the aim of promoting international comparability, statistics presented on ILOSTAT are based on standard international definitions wherever feasible and may differ from official national figures. This series is based on the 13th ICLS definitions. For time series comparability, it includes countries that have implemented the 19th ICLS standards, for which data are also available in the Work Statistics -- 19th ICLS (WORK) database. The total public sector employment covers all employment of general government sector as defined in System of National Accounts 1993 plus employment of publicly owned enterprises and companies, resident and operating at central, state (or regional) and local levels of government. It covers all persons employed directly by those institutions, without regard for the particular type of employment contract. See the working paper: Statistics on Public Sector Employment: Methodology, Structures and Trends. For more information, refer to the Labour Force Statistics (LFS and STLFS) database description.

Families are classified as per number of workers receiving food stamps/ SNAP in a Family 

Data prior to 1999 are based on Standard International Trade Classification (SITC) 3. Data from 1999 onwards are based on SITC 4.1 and consistent with the ASEAN Harmonised Tariff Nomenclature (AHTN) 2017 version.

Data cited at: Refugee Processing Center   FY - Fiscal Years have been used (since October until September). Data for 2017 include the last available values.  The Refugee Processing Center (RPC) is operated by the U.S Department of State (DOS) Bureau of Population, Refugees, and Migration (PRM) in the Rosslyn section of Arlington, Virginia USA.  At the RPC and at Resettlement Support Centers (RSCs), an interactive computer system called the Worldwide Refugee Admissions Processing System (WRAPS) is used to process and track the movement of refugees from various countries around the world to the U.S. for resettlement under the U.S. Refugee Admissions Program (USRAP). Fiscal years 2008 through 2019 as of june 30,2019. . Fiscal Years 2008 through 2019 as of june 30,2019. >> Annual data is Fiscal year data and October is the year starting 

Note:  The dataset is combination of two following datasets. https://www2.census.gov/programs-surveys/popest/tables/2020-2021/state/detail/https://knoema.com/USRAGE2013/ https://www2.census.gov/programs-surveys/popest/tables/2020-2021/state/detail/https://knoema.com/USRSD2013/  

EU-countries in Eastern Europe are transferred from group 2 to group 1 from the time of membership in the EU. 2003 Q2: 115 Estonia, 124 Latvia, 131 Polen, 136 Litauen, 146 Slovenia, 152 Hungary, 157 Slovakia, 158 Czech Republic 2007 Q1: 113 Bulgaria, 133 Romania. EU-countries in Eastern-Europe are transferred from group2 to group 1 from the time of membership of the EU: 2004 k2: 115 Estonia, 124 Latvia, 131 Poland, 136 Lithuania, 146 Slovenia, 152 Hungary, 157 Slovakia, 158 Czech Republic. 2007 k1: 113 Bulgaria, 133 Romania. Countries transferred from group 2 to group 1 from the time of membership of the EU: 2004 k2: 126 Malta, 500 Cyprus. Asia includes Turkey and Cypus. Figures updated December 5, 2018. There is a break in the time series on registered unemployed among immigrants from Q4 2018, so the figures are not directly comparable with previous years.country backgroundSerbia and MontenegroThe name changed from Yugoslavia to Serbia and Montenegro 14 February 2003. Note-Figures in absolute numbers and in per cent of the labor force 

Note: ACS 1-Year Estimates. United States: School Enrollment 

The Office for Civil Rights (OCR) , US Department of Education-collects a variety of information including student enrollment and educational programs and services, most of which is disaggregated by race/ethnicity, sex, limited English proficiency, and disability

Educational attainment in a science, engineering, or technology (SET) field gives people greater opportunities to work in higher-paying technical jobs than are generally available to those in other fields of study. Earning an associate's degree in an SET field also prepares an individual for more advanced technical education. This indicator represents the extent to which a state provides associate's level training in SET fields, controlling for the size of its college-age population. The cohort 18–24 years old was chosen to approximate the age range of most students who are pursuing an associate's degree. The National Center for Education Statistics counts the number of associate's degrees awarded in SET fields; these data include degrees in science and engineering technology fields that are not included with other similar indicators where only S&E fields are included. Associate's degrees are awarded at both 2-year and 4-year institutions in the United States, and there may be regional variations in the degree awards, based on the relationship of these institutions to each other in each state. Estimates of the population aged 18–24 years old are provided by the U.S. Census Bureau. Small differences in the indicator value between states or across time generally are not meaningful. Because students may move across state lines after receiving their associate's degrees, this indicator does not necessarily predict the qualifications of a state's future technical workforce.

Note: The year in dataset is FY The Survey of Science and Engineering Research Facilities is a congressional mandated, biennial survey that collects data on the amount, construction, repair, renovation, and funding of research facilities, as well as the computing and networking capacities at U.S. colleges and universities. The survey is an establishment-based survey completed by institutional coordinators at academic institutions and is a census of all research-performing colleges and universities in the United States that expended at least $1 million in research and development funds in the prior fiscal year.   Courtesy: National Science Foundation

The series is part of the ILO modelled estimates and is harmonized to account for differences in national data and scope of coverage, collection and tabulation methodologies as well as for other country-specific factors. This indicator conveys the annual growth rates of labour productivity. Labour productivity represents the total volume of output (measured in terms of Gross Domestic Product, GDP) produced per unit of labour (measured in terms of the number of employed persons) during a given time reference period. The indicator allows data users to assess GDP-to-labour input levels and growth rates over time, thus providing general information about the efficiency and quality of human capital in the production process for a given economic and social context, including other complementary inputs and innovations used in production. For more information, refer to the Labour Market-related SDG Indicators (ILOSDG) database description.

The series is part of the ILO modelled estimates and is harmonized to account for differences in national data and scope of coverage, collection and tabulation methodologies as well as for other country-specific factors. This indicator conveys the annual growth rates of labour productivity. Labour productivity represents the total volume of output (measured in terms of Gross Domestic Product, GDP) produced per unit of labour (measured in terms of the number of employed persons) during a given time reference period. The indicator allows data users to assess GDP-to-labour input levels and growth rates over time, thus providing general information about the efficiency and quality of human capital in the production process for a given economic and social context, including other complementary inputs and innovations used in production. For more information, refer to the Labour Market-related SDG Indicators (ILOSDG) database description.

Data provided refers to persons in paid employment in the non-agricultural sector as a percent of total non-agricultural employment.

Health Professional Shortage Area (HPSA) designations are used to identify areas and population groups within the United States that are experiencing a shortage of health professionals. There are three categories of HPSA designation based on the health discipline that is experiencing a shortage: 1) primary medical; 2) dental; and 3) mental health. The primary factor used to determine a HPSA designation is the number of health professionals relative to the population with consideration of high need. Federal regulations stipulate that, in order to be considered as having a shortage of providers, an area must have a population-to-provider ratio of a certain threshold. For mental health, the population to provider ratio must be at least 30,000 to 1 (20,000 to 1 if there are unusually high needs in the community). The number of mental health care HPSA designations includes HPSAs that are proposed for withdrawal and HPSAs that have no data. By statute, designations are not withdrawn until a Federal Register Notice is published, generally once a year on or around July 1.

State-level Data for Understanding Child Welfare in the United States. This dataset provides comprehensive information about child welfare resource provides state and national data on child maltreatment, foster care, adoption from foster care and kinship caregiving. The data are crucial to policymakers for understanding how many children and youth came in contact with the child welfare system, and why.  States can use this resource to ensure their child welfare systems support the safety, stability, and well-being of all families in their state.

Data cited at: Gallup and Sharecare The Gallup-Sharecare Well-Being Index, which includes more than 2.5 million surveys, captures how people feel about and experience their daily lives. As part of the GallupSharecare State of American Well-Being series, this report examines well-being across the nation, including how well-being varies by state and which states lead and lag across the five elements of well-being. The five elements are: • Purpose: liking what you do each day and being motivated to achieve your goals • Social: having supportive relationships and love in your life • Financial: managing your economic life to reduce stress and increase security • Community: liking where you live, feeling safe, and having pride in your community • Physical: having good health and enough energy to get things done daily Overall, 2017 was a challenging year for Americans’ well-being. The national Well-Being Index score for the U.S. in 2017 was 61.5 – a decline from 62.1 in 2016. This overall drop was characterized by declines in 21 states, easily the largest year-over-year decline in the 10-year history of the Well-Being Index. Not a single state showed statistically significant improvement compared to the previous year, which is also unprecedented in Well-Being Index measurement. In the state rankings, South Dakota and Vermont, followed by Hawaii, were the highest well-being states in 2017. South Dakota has ranked among the highest six states every year since 2013 and Vermont, which had the sixth highest well-being in 2016, shares the highest well-being score (64.1) in 2017. Neither state had scored at the top of the well-being state rankings before. Hawaii, which along with Colorado holds the distinction of ranking in the top 10 highest well-being states each year since 2008, ranked just below South Dakota and Vermont in 2017 with a score of 63.4. In 2016, Hawaii was ranked in first place with a 65.2 well-being score. Residents of West Virginia reported the lowest levels of well-being in 2017 for the ninth consecutive year with a well-being score of 58.8. Louisiana fell to its lowest rank ever, recording a score of 58.9, just above West Virginia.

American Community Survey 1-Year Estimates - State-to-State Migration Flows

The Justice Index is a snapshot of the degree to which each US state has adopted best practices for ensuring access to justice for all people. NCAJ identifies four key areas-- attorney access, support for self-represented litigants, language access and disability access. The index also examine the degree to which every state complies with these four key areas.

This Data set provide information about Federal Student Loan Portfolio by Borrower Location and Debt SizeThe office of Federal Student Aid is responsible for directly managing or overseeing an outstanding federal student loan portfolio comprised of billions of dollars in Title IV loans and representing millions of borrowers. This federal student loan portfolio includes Direct Loans, Federal Family Education Loans (FFEL), and Perkins Loans with outstanding balances.Includes outstanding principal and interest balances.

Data on Supplemental Nutrition Assistance Program (SNAP, formerly the Food Stamp Program) participation and costs. Nation-wide and state level program participation counts and recipiency rates; value of benefits issued and other costs. The US Food Stamp/SNAP program administered by the U.S. Department of Agriculture’s (USDA) Food and Nutrition Service, is the largest food assistance program in the country, reaching more poor individuals over the course of a year than any other public assistance program. Unlike many other public assistance programs, SNAP has few categorical requirements for eligibility, such as the presence of children, elderly, or disabled individuals in a household. As a result, the program offers assistance to a large and diverse population of needy persons, many of whom are not eligible for other forms of assistance.   All data except population estimates originate from USDA Food & Nutrition Service. Sources & notes:For the national-wide totals USDA Food & Nutrition Service national level annual summaries are used. Totals for national level include all states, District of Columbia and island areas, excluding Puerto Rico. Totals for 1975-1982 including Puerto Rico. Puerto Rico initiated Food Stamp operations during FY 1975 and participated through June of FY 1982. A separate Nutrition Assistance Grant began in July 1982.State-level data for 2010-2014 from theUSDA Food & Nutrition Service national level annual summaries. For 2001-2009 - data from USDA SNAP State Activity reports. For the previous years - USDA data from the US Department of Health & Human Services "Welfare Indicators and Risk Factors" annual reports to Congress. Resident population counts are US Census Bureau’s latest estimates; for Guam and Virgin Islands -World Bank Population Estimates & Projections. Totals for United States resident population DOES NOT include Puerto Rico & island areas. Recipiency rates expressed as percentages of total population have been correctly computed using corresponding summary population values

Supply Utilization Accounts and Food Balance Sheet present a comprehensive picture of the pattern of a country's food supply during a specified reference period. The food balance sheet shows for each food item - i.e. each primary commodity and a number of processed commodities potentially available for human consumption - the sources of supply and its utilization. The total quantity of foodstuffs produced in a country added to the total quantity imported and adjusted to any change in stocks that may have occurred since the beginning of the reference period gives the supply available during that period. On the utilization side a distinction is made between the quantities exported, fed to livestock, used for seed, put to manufacture for food use and non-food uses, losses during storage and transportation, and food supplies available for human consumption. The per caput supply of each such food item available for human consumption is then obtained by dividing the respective quantity by the related data on the population actually partaking of it. Data on per caput food supplies are expressed in terms of quantity and - by applying appropriate food composition factors for all primary and processed products - also in terms of caloric value and protein and fat content.

UNECE Clearing House on Migration Statistics is a platform for data exchange on migration statistics for countries of Eastern Europe, Caucasus and Central Asia (EECCA) established with the purpose of improving the understanding migration processes and the systems of measuring migration in the region. The data are presented as submitted by national statistical offices. For more information about the methodology of producing statistics on international migration in EECCA region, please refer to the UNECE Handbook on the Use of Administrative Sources and Sample Surveys to Measure International Migration in CIS Countries and the documentation of UNECE Workshops on Migration Statistics. Country: Armenia Data source: 2001, 2011 - population and housing census; 2015 and onwards - administrative source. Country: Azerbaijan Data source: population and housing census. Country: Belarus The sum of the age groups does not correspond to the ''Total'' since age was unknown for a number of persons. Data source: population and housing census. Country: Georgia Data source: 2002 - population and housing census; 2011 and onwards - administrative source. Country: Kyrgyzstan Data source: population and housing census. Country: Moldova, Republic of ''Other'' includes a number of migrants for which the country is unknown. Data source: population register. Country: Russian Federation In 2010, the sum of the age groups does not correspond to the ''Total'' since the age was unknown for a number of persons. Data source: 2010 - population and housing census. Country: Ukraine In 2001, the sum of the age groups does not correspond to the ''Total'' since age was unknown for a number of persons. The population count does not include the territory of the Autonomous Republic of Crimea and the city of Sevastopol. The General Assembly has addressed the status of the Autonomous Republic of Crimea and the city of Sevastopol in resolution 68/262 of 27 March 2014. Data source: 2001 - population and housing census; 2011 and onwards - the annual estimate of the number of permanent residents as of January 1 carried out by the State Statistics Committee.

UNECE Clearing House on Migration Statistics is a platform for data exchange on migration statistics for countries of Eastern Europe, Caucasus and Central Asia (EECCA) established with the purpose of improving the understanding migration processes and the systems of measuring migration in the region. The data are presented as submitted by national statistical offices. For more information about the methodology of producing statistics on international migration in EECCA region, please refer to the UNECE Handbook on the Use of Administrative Sources and Sample Surveys to Measure International Migration in CIS Countries and the documentation of UNECE Workshops on Migration Statistics. Country: Armenia Data source: 2001, 2011 - population and housing census; 2015 and onwards - administrative source. Country: Azerbaijan Data source: population and housing census. Country: Belarus The sum of the age groups does not correspond to the ''Total'' since age was unknown for a number of persons. Data source: population and housing census. Country: Georgia Data source: 2002 - population and housing census; 2011 and onwards - administrative source. Country: Kyrgyzstan Data source: population and housing census. Country: Moldova, Republic of ''Other'' includes a number of migrants for which the country is unknown. Data source: population register. Country: Russian Federation In 2010, the sum of the age groups does not correspond to the ''Total'' since the age was unknown for a number of persons. Data source: 2010 - population and housing census. Country: Tajikistan Data source: 2000, 2010 - population and housing census; 2011-2014 - source unspecified. Country: Ukraine In 2001, the sum of the age groups does not correspond to the ''Total'' since age was unknown for a number of persons. The population count does not include the territory of the Autonomous Republic of Crimea and the city of Sevastopol. The General Assembly has addressed the status of the Autonomous Republic of Crimea and the city of Sevastopol in resolution 68/262 of 27 March 2014. Data source: 2001 - population and housing census; 2011 and onwards - the annual estimate of the number of permanent residents as of January 1 carried out by the State Statistics Committee.

The total for ''All countries'' includes persons for whom the country of previous residence is unknown.UNECE Clearing House on Migration Statistics is a platform for data exchange on migration statistics for countries of Eastern Europe, Caucasus and Central Asia (EECCA) established with the purpose of improving the understanding migration processes and the systems of measuring migration in the region. The data are presented as submitted by national statistical offices. For more information about the methodology of producing statistics on international migration in EECCA region, please refer to the UNECE Handbook on the Use of Administrative Sources and Sample Surveys to Measure International Migration in CIS Countries and the documentation of UNECE Workshops on Migration Statistics. Definition: Unless noted otherwise, an international migrant is defined as any person who changes his or her country of usual residence. A long-term migrant is a person who moves to a country other than that of his or her usual residence for a period of at least a year. A short-term migrant is a person who moves to a country other than that of his or her usual residence for a period of at least 3 months but less than a year. Country: Armenia In 2001 and 2011 the registered data refer to the date of conducting the Population Census and the number exceeds the total foreign population living in Armenia. Data from 2014 onwards are based on administrative sources. Data source: 2001, 2011 - population and housing census; 2014 and onwards - population register. Country: Azerbaijan Data source: residence permits. Country: Belarus Data source: residence permits. Country: Georgia From 2013, long-term migration refers to those who have left or moved to Georgia for at least 6 months. Data source: 2002 - population and housing census; 2012 and onwards - administrative source. Country: Kazakhstan Data source: 2009 - population and housing census; 2010 and onwards - residence permits. Country: Kyrgyzstan Data source: administrative source. Country: Russian Federation 2011 break in series: the Russian Federation introduced a new methodology for estimating immigration. From 2011 onwards, the source of data on international migration (long-term immigration) is registration at the place of residence and at the place of stay for a period of 9 months or more in the bodies of the Ministry of Internal Affairs of Russia. In 2011 and 2012, the full break down by age and sex is not available for some countries of previous residence. The total flow from each country of previous residence is available. Data source: administrative source. Country: Tajikistan The sum of the age groups does not correspond to the ''Total'' since age was unknown for a number of persons. Data source: administrative source. Country: Ukraine 2001 data include all those who have ever moved. Data source: 2001 - population and housing census; 2011, 2012 - residence permits. Country: Uzbekistan Data from 2011 to 2014 include internal migrants within Uzbekistan. Data source: administrative source.

UNECE Clearing House on Migration Statistics is a platform for data exchange on migration statistics for countries of Eastern Europe, Caucasus and Central Asia (EECCA) established with the purpose of improving the understanding migration processes and the systems of measuring migration in the region. The data are presented as submitted by national statistical offices. For more information about the methodology of producing statistics on international migration in EECCA region, please refer to the UNECE Handbook on the Use of Administrative Sources and Sample Surveys to Measure International Migration in CIS Countries and the documentation of UNECE Workshops on Migration Statistics. The total for ''All countries'' includes persons for whom the country of next residence is unknown. Definition: Unless noted otherwise, an international migrant is defined as any person who changes his or her country of usual residence. A long-term migrant is a person who moves to a country other than that of his or her usual residence for a period of at least a year. A short-term migrant is a person who moves to a country other than that of his or her usual residence for a period of at least 3 months but less than a year. Country: Armenia Data source: 2001, 2011 - population and housing census; 2014 and onwards - population register. Country: Azerbaijan Data source: exit permits. Country: Belarus Data source: residence permits. Country: Georgia From 2013, long-term migration refers to those who have left or moved to Georgia for at least 6 months. Data source: 2002 - population and housing census; 2012 and onwards - administrative source. Country: Kazakhstan Data source: exit permits. Country: Kyrgyzstan For a number of persons the information on the country of next residence is missing in the source. Data source: administrative source. Country: Moldova, Republic of Data source: population register. Country: Russian Federation 2012 break in series: the Russian Federation introduced a new methodology for estimating emigration. From 2012 onwards, the source of data on international migration (long-term emigration) is registration at the place of residence and at the place of stay for a period of 9 months or more. In 2011 and 2012, the full break down by age and sex is not available for some countries of next residence. The total flow from each country of next residence is available. Data source: administrative source. Country: Tajikistan The sum of the age groups does not correspond to the ''Total'' since age was unknown for a number of persons. Data source: administrative source. Country: Ukraine Data source: administrative source. Country: Uzbekistan Data from 2011 to 2014 include internal migrants within Uzbekistan. Data source: administrative source.

UNECE Clearing House on Migration Statistics is a platform for data exchange on migration statistics for countries of Eastern Europe, Caucasus and Central Asia (EECCA) established with the purpose of improving the understanding migration processes and the systems of measuring migration in the region. The data are presented as submitted by national statistical offices. For more information about the methodology of producing statistics on international migration in EECCA region, please refer to the UNECE Handbook on the Use of Administrative Sources and Sample Surveys to Measure International Migration in CIS Countries and the documentation of UNECE Workshops on Migration Statistics. Definition: Unless noted otherwise, an international migrant is defined as any person who changes his or her country of usual residence. A long-term migrant is a person who moves to a country other than that of his or her usual residence for a period of at least a year. A short-term migrant is a person who moves to a country other than that of his or her usual residence for a period of at least 3 months but less than a year. Country: Armenia Data source: 2001, 2011 - population and housing census; 2015 and onwards - population register. Country: Azerbaijan Data indicate the number of persons who obtained a permanent residence permit in Azerbaijan. Azer citizens returning from abroad are not included in the total number. Data source: residence permits. Country: Belarus Data source: residence permits. Country: Georgia From 2013, long-term migration refers to those who have left or moved to Georgia for at least 6 months. Data source: 2002 - population and housing census; 2012 and onwards - border cards. Country: Kyrgyzstan Data source: administrative source. Country: Russian Federation 2011 break in series: the Russian Federation introduced a new methodology for estimating immigration. From 2011 onwards, the source of data on international migration (long-term immigration) is registration at the place of residence and at the place of stay for a period of 9 months or more in the bodies of the Ministry of Internal Affairs of Russia. Data source: administrative source. Country: Ukraine Data source: 2001 - population and housing census; 2011, 2012 - residence permits.

UNECE Clearing House on Migration Statistics is a platform for data exchange on migration statistics for countries of Eastern Europe, Caucasus and Central Asia (EECCA) established with the purpose of improving the understanding migration processes and the systems of measuring migration in the region. The data are presented as submitted by national statistical offices. For more information about the methodology of producing statistics on international migration in EECCA region, please refer to the UNECE Handbook on the Use of Administrative Sources and Sample Surveys to Measure International Migration in CIS Countries and the documentation of UNECE Workshops on Migration Statistics. Definition: Unless noted otherwise, an international migrant is defined as any person who changes his or her country of usual residence. A long-term migrant is a person who moves to a country other than that of his or her usual residence for a period of at least a year. A short-term migrant is a person who moves to a country other than that of his or her usual residence for a period of at least 3 months but less than a year. Country: Armenia Data source: 2011 - population and housing census; 2015 and onwards - population register. Country: Azerbaijan Data indicate the number of persons who obtained an exit permit in Azerbaijan. Azer citizens are not included in the total number. Data source: exit permits. Country: Belarus Data source: residence permits. Country: Georgia From 2013, long-term migration refers to those who have left or moved to Georgia for at least 6 months. Data source: 2002 - population and housing census; 2012 and onwards - border cards. Country: Kyrgyzstan Data source: administrative source. Country: Moldova, Republic of Data source: population register. Country: Russian Federation 2012 break in series: the Russian Federation introduced a new methodology for estimating emigration. From 2012 onwards, the source of data on international migration (long-term emigration) is registration at the place of residence and at the place of stay for a period of 9 months or more. Data source: administrative source. Country: Ukraine Data source: administrative source.

UNECE Clearing House on Migration Statistics is a platform for data exchange on migration statistics for countries of Eastern Europe, Caucasus and Central Asia (EECCA) established with the purpose of improving the understanding migration processes and the systems of measuring migration in the region. The data are presented as submitted by national statistical offices. For more information about the methodology of producing statistics on international migration in EECCA region, please refer to the UNECE Handbook on the Use of Administrative Sources and Sample Surveys to Measure International Migration in CIS Countries and the documentation of UNECE Workshops on Migration Statistics. Country: Azerbaijan Data source: residence permits. Country: Belarus Data source: administrative source. Country: Georgia Data source: civil register. Country: Kyrgyzstan Data source: administrative source. Country: Moldova, Republic of Data source: population register. Country: Russian Federation Data source: administrative source. Country: Ukraine Data source: administrative source.

The UNECE Clearing House on Migration Statistics is a platform for data exchange on migration statistics for countries of Eastern Europe, Caucasus and Central Asia (EECCA), established with the purpose of improving the understanding of migration processes and the systems of measuring migration in the region. The data are presented as submitted by national statistical offices. For more information about the methodology of producing statistics on international migration in EECCA region, please refer to the UNECE Handbook on the Use of Administrative Sources and Sample Surveys to Measure International Migration in CIS Countries and the documentation of UNECE Workshops on Migration Statistics. Country: Azerbaijan Data source: residence permits. Country: Belarus Data source: residence permits. Country: Moldova, Republic of Data source: population register. Country: Tajikistan Disaggregation by sex is only available for people who immigrated for work purposes. Data source: work permits.

The U. S. Environmental Protection Agency (EPA) has provided a scale called the Air Quality Index (AQI) for rating air quality. This scale is based on the National Ambient Air Quality Standards (NAAQS) and is described in the Code of Federal Regulations, Part 58, Appendix G. This report is based on the AQI standards. More information on the AQI can be found on the EPA's AirNow web site.

By 2030, at least 60 percent of Texans ages 25-34 will have a certificate or degree The 60x30TX (“60 by 30 Tex”) higher education strategic plan contains four broad goals. Each goal contains a set of targets that will move the state toward reaching one or more goals. Many stakeholders across Texas will need to develop and implement a wide range of strategies to meet each target.

Texas Primary Care Physicians & Psychiatrists by Health Region. Table 28: Infant, Neonatal, Fetal, Perinatal, and Maternal Deaths by Public Health Region, County and City of Residence Texas  (Rates, Ratios Per 1,000 Live Births).

This technical memorandum lists the deadliest tropical cyclones in the United States during 1851-2010 and the costliest tropical cyclones in the United States during 1900-2010. The compilation ranks damage, as expressed by monetary losses, in three ways: 1) contemporaneous estimates; 2) contemporaneous estimates adjusted by inflation to 2010 dollars; and 3) contemporaneous estimates adjusted for inflation and the growth of population and personal wealth (Pielke et al. 2008) to 2010 dollars. In addition, the most intense (i.e., major1 ) hurricanes to make landfall in the United States during the 160-year period are listed. Also presented are some additional statistics on United States hurricanes and tropical cyclones in general.

Rail Intermodal Keeps America Moving Containers accounted for 44 percent of intermodal volume in 1990, 69 percent in 2000, and a record 91 percent in 2016. Unlike trailers, containers can be “double stacked,” sharply increasing productivity and helping to ensure that there is sufficient traffic density to keep rail intermodal cost competitive with all truck movements. Containers can also be easily transferred to and from ships and trucks, further enhancing productivity. Source: AAR analysis of 2018 STB Waybill Sample

A medical career starts with finding the program that best fits your needs. With the U.S. News rankings of the top medical schools for research, narrow your search by location, tuition, school size and test scores.

The data or facts (facts are more than mere bragging) help to understand situation,How’s the economy? What about taxes? Debt? Personal wages? in Texas as compare to other Economy which help policymakers and taxpayers to make better policies and investment for future of Texas. The Comptroller of Public Accounts, Texas forecasts revenue for the state, making it vitally important that keep a finger on the pulse of the economy. Third-party sources compiled the source data for these rankings; our office has not independently verified the data. The Comptroller does not control or guarantee the accuracy, completeness or timeliness of any source data — provided as of the date indicated — or related website. When you access any third-party website, you will be leaving the Comptroller’s website.

Reporting of new Aggregate Case and Death Count data was discontinued on May 11, 2023, with the expiration of the COVID-19 public health emergency declaration. According to the source, this dataset will receive a final update on June 1, 2023, to reconcile historical data.

The taxes and other fees on retail gasoline and diesel fuel, in cents per gallon, as of January 1, 2023   Federal taxes include excises taxes of 18.3 cents per gallon on gasoline and 24.3 cents per gallon on diesel fuel, and a Leaking Underground Storage Tank fee of 0.1 cents per gallon on both fuels. State taxes include rates of general application including, but not limited to, excise taxes, environmental taxes, special taxes, and inspection fees, but exclude state taxes based on gross or net receipts. State taxes do not include county and local taxes. This information is for general informational purposes only. Sources: State and Territorial statutes and government agencies.

US Firearms Trace Data

US Funding Awarded By State / Territory 

Courtesy: National Science Foundation

The Yearbook of Immigration Statistics is a compendium of tables that provides data on foreign nationals who, during a fiscal year, were granted lawful permanent residence (i.e., admitted as immigrants or became legal permanent residents), were admitted into the United States on a temporary basis (e.g., tourists, students, or workers), applied for asylum or refugee status, or were naturalized.

These are  weekly  cases of selected infectious national notifiable diseases, from the National Notifiable Diseases Surveillance System (NNDSS). NNDSS data reported by the 50 states, New York City, the District of Columbia, and the US territories are collated and published weekly as numbered tables. Cases reported by state health departments to CDC for weekly publication are subject to the ongoing revision of information and delayed reporting. Therefore, numbers listed in later weeks may reflect changes made to these counts as additional information becomes available.    TRANSLATE with xEnglishArabicHebrewPolishBulgarianHindiPortugueseCatalanHmong DawRomanianChinese SimplifiedHungarianRussianChinese TraditionalIndonesianSlovakCzechItalianSlovenianDanishJapaneseSpanishDutchKlingonSwedishEnglishKoreanThaiEstonianLatvianTurkishFinnishLithuanianUkrainianFrenchMalayUrduGermanMalteseVietnameseGreekNorwegianWelshHaitian CreolePersian  TRANSLATE with COPY THE URL BELOW BackEMBED THE SNIPPET BELOW IN YOUR SITEEnable collaborative features and customize widget: Bing Webmaster PortalBack

U.S. Road and Bridge statistics by State

Data cited at:  Kauffman Indicators of Entrepreneurship Kauffman Indicators of Entrepreneurship The Kauffman Indicators of Entrepreneurship offers in-depth measures, reports, and accompanying interactive data visualizations that present entrepreneurial trends in the United States.

Note: This dataset presents the weekly unemployment insurance (UI) claims reported by each state's unemployment insurance program offices. These claims may be used for monitoring workload volume. Where the claimant claims the claim is filed directly with the claimant. These are the basis for the initial claims and continued claims reported each week. These data come from ETA 538, Advance Weekly Initial and Continued Claims Report. The following week initial claims and continuing claims are based on a second reporting by the state of residence. These data come from the ETA 539, Weekly Claims and Extended Benefits Trigger Data Report.

Active Pilot - A pilot who holds a pilot certificate and a valid medical certificate (except for sport pilots). Airman - A pilot, mechanic, or other licensed aviation technician. The term refers to men and women. Airman Certificate - A document issued by the Administrator of the Federal Aviation Administration The Airman Certificate certifies that the holder complies with the regulations governing the capacity in which the certificate authorizes the holder to act as an airman in connection with an aircraft.

Hospitals across the country show a lot of variation when it comes to patient safety. Here, states are ranked based on the number of “A” hospitals they have compared to the total number of graded hospitals on the Fall 2020 Leapfrog Hospital Safety Grade. State rankings from Fall 2019 are also displayed.

Imputed observations are not based on national data, are subject to high uncertainty and should not be used for country comparisons or rankings. The unemployment rate is the number of persons who are unemployed as a percent of the total number of employed and unemployed persons (i.e., the labour force). The series is part of the ILO modelled estimates and is harmonized to account for differences in national data and scope of coverage, collection and tabulation methodologies as well as for other country-specific factors. For more information, refer to the ILOSTAT pages on concepts and definitions and ILO modelled estimates and projections.

With the aim of promoting international comparability, statistics presented on ILOSTAT are based on standard international definitions wherever feasible and may differ from official national figures. This series is based on the 13th ICLS definitions. For time series comparability, it includes countries that have implemented the 19th ICLS standards, for which data are also available in the Work Statistics -- 19th ICLS (WORK) database. The unemployed comprise all persons of working age who were: a) without work during the reference period, i.e. were not in paid employment or self-employment; b) currently available for work, i.e. were available for paid employment or self-employment during the reference period; and c) seeking work, i.e. had taken specific steps in a specified recent period to seek paid employment or self-employment. For more information, refer to the Labour Force Statistics (LFS and STLFS) database description.

With the aim of promoting international comparability, statistics presented on ILOSTAT are based on standard international definitions wherever feasible and may differ from official national figures. This series is based on the 13th ICLS definitions. For time series comparability, it includes countries that have implemented the 19th ICLS standards, for which data are also available in the Work Statistics -- 19th ICLS (WORK) database. The unemployed comprise all persons of working age who were: a) without work during the reference period, i.e. were not in paid employment or self-employment; b) currently available for work, i.e. were available for paid employment or self-employment during the reference period; and c) seeking work, i.e. had taken specific steps in a specified recent period to seek paid employment or self-employment. For more information, refer to the Labour Force Statistics (LFS and STLFS) database description.

With the aim of promoting international comparability, statistics presented on ILOSTAT are based on standard international definitions wherever feasible and may differ from official national figures. This series is based on the 13th ICLS definitions. For time series comparability, it includes countries that have implemented the 19th ICLS standards, for which data are also available in the Work Statistics -- 19th ICLS (WORK) database. The unemployed comprise all persons of working age who were: a) without work during the reference period, i.e. were not in paid employment or self-employment; b) currently available for work, i.e. were available for paid employment or self-employment during the reference period; and c) seeking work, i.e. had taken specific steps in a specified recent period to seek paid employment or self-employment. Data disaggregated by economic activity are provided according to the latest version of the International Standard Industrial Classification of All Economic Activities (ISIC) available for that year. Data may have been regrouped from national classifications, which may not be strictly compatible with ISIC. For more information, refer to the Labour Force Statistics (LFS and STLFS) database description.

With the aim of promoting international comparability, statistics presented on ILOSTAT are based on standard international definitions wherever feasible and may differ from official national figures. This series is based on the 13th ICLS definitions. For time series comparability, it includes countries that have implemented the 19th ICLS standards, for which data are also available in the Work Statistics -- 19th ICLS (WORK) database. The unemployed comprise all persons of working age who were: a) without work during the reference period, i.e. were not in paid employment or self-employment; b) currently available for work, i.e. were available for paid employment or self-employment during the reference period; and c) seeking work, i.e. had taken specific steps in a specified recent period to seek paid employment or self-employment. Data disaggregated by occupation are provided according to the latest version of the International Standard Classification of Occupations (ISCO). Data may have been regrouped from the national classifications, which may not be strictly compatible with ISCO. For more information, refer to the Labour Force Statistics (LFS and STLFS) database description.

Data may differ from nationally reported figures and the Global SDG Indicators Database due to differences in sources and/or reference years. The unemployment rate conveys the number of persons who are unemployed as a percent of the labour force (i.e., the employed plus the unemployed). The unemployed comprise all persons of working age who were: a) without work during the reference period, i.e. were not in paid employment or self-employment; b) currently available for work, i.e. were available for paid employment or self-employment during the reference period; and c) seeking work, i.e. had taken specific steps in a specified recent period to seek paid employment or self-employment. For more information, refer to the Labour Market-related SDG Indicators (ILOSDG) database description.

Imputed observations are not based on national data, are subject to high uncertainty and should not be used for country comparisons or rankings. The unemployment rate is the number of persons who are unemployed as a percent of the total number of employed and unemployed persons (i.e., the labour force). The series is part of the ILO modelled estimates and is harmonized to account for differences in national data and scope of coverage, collection and tabulation methodologies as well as for other country-specific factors. For more information, refer to the ILOSTAT pages on concepts and definitions and ILO modelled estimates and projections.

With the aim of promoting international comparability, statistics presented on ILOSTAT are based on standard international definitions wherever feasible and may differ from official national figures. This series is based on the 13th ICLS definitions. For time series comparability, it includes countries that have implemented the 19th ICLS standards, for which data are also available in the Work Statistics -- 19th ICLS (WORK) database. The unemployment rate conveys the number of persons who are unemployed as a percent of the labour force (i.e., the employed plus the unemployed). The unemployed comprise all persons of working age who were: a) without work during the reference period, i.e. were not in paid employment or self-employment; b) currently available for work, i.e. were available for paid employment or self-employment during the reference period; and c) seeking work, i.e. had taken specific steps in a specified recent period to seek paid employment or self-employment. For more information, refer to the Labour Force Statistics (LFS and STLFS) database description.

The unemployment rate is the number of persons who are unemployed as a percent of the total number of employed and unemployed persons (i.e., the labour force). The series is part of the ILO estimates and is harmonized to account for differences in national data and scope of coverage, collection and tabulation methodologies as well as for other country-specific factors. For more information, refer to the indicator description and the ILO estimates and projections methodological note.

Enrolled-Number of beneficiaries enrolled by contract in the state/county United States: Enrollment Data for Medicare Advantage.

Pedestrians Killed in Single Vehicle Crashes, by Vehicle Type and Initial Point of Impact - State : USA Pedestrians Killed, by Related Factors - State : USA

The National survey of Unbanked and Underbanked households is conducted biennially since 2009 and is administered in partnership with the U.S. Census Bureau. An estimated 4.5 percent of U.S. households (approximately 5.9 million) were “unbanked” in 2021.

The Urban Mobility Report provides a comprehensive analysis of traffic conditions in 494 urban areas across the United States. The report points to the need to consider a full range of mobility improvement strategies. TTI’s 2019 edition uses crowd sourced data from INRIX on urban streets and highways, along with highway inventory data from the Federal Highway Administration. The report was sponsored by the Texas Department of Transportation.

US Fiscal Stability Report (Fiscal Year)

This dataset aggregated sum for below mentioned datasets. https://knoema.com/USFLSMGS2021/ https://knoema.com/USINGRS2021/ https://knoema.com/USIAGRS2021/ https://knoema.com/MOGFR2021/ https://knoema.com/USMIGS2021/ https://knoema.com/USMSGGR2021/ https://knoema.com/USNJDGEGRS2021/ https://knoema.com/USOKGHR2021/ https://knoema.com/USWVVLSW2021/ https://knoema.com/USMOGFS2021/ https://knoema.com/USILTRI2021/ https://knoema.com/USKSLGFR2021/ https://knoema.com/USMECRS2021/ https://knoema.com/USNYCGS2021/ https://knoema.com/USMOGR2021/ https://knoema.com/UAPASRS2021/ https://knoema.com/UAPASIGRS2021/ https://knoema.com/USPATGRS2021/ The aggregation calculated by sum of each states casino Total Revenue.

Note: Effective September 27, 2023, this dataset will no longer be updated. Provisional counts of deaths by the week the deaths occurred, by state of occurrence, and by select underlying causes of death. The dataset also includes weekly provisional counts of death for COVID-19, coded to ICD-10 code U07.1 as an underlying or multiple cause of death.  

Estimates on the use of water, sanitation and hygiene by country (2000-2020)

Workers involved in strikes and lockouts represents the number of workers implicated directly or indirectly at any time during a strike or lockout, whether the involvement was for the full duration of the strike or lockout or only part of it. Workers who are unable to work as a result of the secondary effects of strikes or lockouts should not be included. Data disaggregated by economic activity are provided according to the latest version of the International Standard Industrial Classification of All Economic Activities (ISIC) available for that year. Data may have been regrouped from national classifications, which may not be strictly compatible with ISIC. For more information, refer to the Industrial Relations data (IRdata) database description.

With the aim of promoting international comparability, statistics presented on ILOSTAT are based on standard international definitions wherever feasible and may differ from official national figures. This series is based on the 13th ICLS definitions. For time series comparability, it includes countries that have implemented the 19th ICLS standards, for which data are also available in the Work Statistics -- 19th ICLS (WORK) database. The working-age population is commonly defined as persons aged 15 years and older, but this varies from country to country. For more information, refer to the Labour Force Statistics (LFS and STLFS) database description.

With the aim of promoting international comparability, statistics presented on ILOSTAT are based on standard international definitions wherever feasible and may differ from official national figures. This series is based on the 13th ICLS definitions. For time series comparability, it includes countries that have implemented the 19th ICLS standards, for which data are also available in the Work Statistics -- 19th ICLS (WORK) database. The working-age population is commonly defined as persons aged 15 years and older, but this varies from country to country. Data disaggregated by level of education are provided on the highest level of education completed, classified according to the International Standard Classification of Education (ISCED). Data may have been regrouped from national classifications, which may not be strictly compatible with ISCED. For more information, refer to the Education and Mismatch Indicators (EMI) database description.

The ease of doing business score helps assess the absolute level of regulatory performance over time. It captures the gap of each economy from the best regulatory performance observed on each of the indicators across all economies in the Doing Business sample since 2005. One can both see the gap between a particular economy’s performance and the best performance at any point in time and assess the absolute change in the economy’s regulatory environment over time as measured by Doing Business. An economy’s ease of doing business score is reflected on a scale from 0 to 100, where 0 represents the lowest and 100 represents the best performance. For example, an ease of doing business score of 75 in Doing Business 2019 means an economy was 25 percentage points away from the best regulatory performance constructed across all economies and across time. A score of 80 in Doing Business 2020 would indicate the economy is improving   NOTE- The source discontinued this dataset; Reference-Doing Business Legacy (worldbank.org)