Connecticut

30-day hospital readmissions among adults ages 18–64 with employer-sponsored insurance, per 1,000 enrollees.

This Wide-Area Perspective on the August 21, 2017 Total Solar Eclipse document was created in order to evaluate potential reliability consequences of the total solar eclipse on the BPS. This assessment focuses specifically on impacts of system loading and potential reliability implications when an area experiences a large reduction of distributed energy resource (DER) capacity due to a total solar eclipse. Ramping is a specific concern for areas with large amounts of variable generation in their resource mix. The areas that have ramping issues will need further evaluation by the Regions and include areas that are not in the direct path of the eclipse. An example of such an area is California, where the transmission (utility) installed nameplate capacity for solar generation is 11,444 MW. Some areas in Northern California are projected to experience up to 95 percent of the obscuration of the Sun from the August 21, 2017 eclipse.

Post Secondary Education of United States, 2015

Adults ages 18–64 who report fair or poor health (%)

Note- "Amount of water used for irrigation per acre of cropland" is calculate as follows: Total - Acre-feet of water applied divided by  Total cropland - Acres

The Clean Air Act (CAA) authorizes EPA to regulate air pollution from stationary sources like chemical plants, utilities, and steel mills. EPA delegates much of its CAA authority to state, local, and tribal agencies. To help manage the national CAA stationary source compliance monitoring and enforcement program, EPA requires that delegated agencies regularly report data on types of facilities within their jurisdiction and activities conducted, such as compliance evaluations, compliance determinations, and enforcement actions.  This dataset presents a summary of High Priority Violations (HPVs) by Lead Agency and facilities with HPV by Permitting Agency

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

The National Center for Education Statistics (NCES) is now conducting the Academic Libraries Survey as part of the Integrated Postsecondary Education Data System (IPEDS). The Academic Libraries component for IPEDS replaced the previous Academic Libraries Survey, which was collected from degree-granting postsecondary institutions every other year in even-numbered years. The new Academic Libraries component is mandatory and will be collected annually in the spring starting with the 2014-15 data collection cycle.

The National Center for Education Statistics (NCES) is now conducting the Academic Libraries Survey as part of the Integrated Postsecondary Education Data System (IPEDS). The Academic Libraries component for IPEDS replaced the previous Academic Libraries Survey, which was collected from degree-granting postsecondary institutions every other year in even-numbered years. The new Academic Libraries component is mandatory and will be collected annually in the spring starting with the 2014-15 data collection cycle.

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

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(DP05- ACS)

Note: ACS 1-Year Estimates 

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

American Community Survey 1-Year Estimates Table S2802 - TYPES OF INTERNET SUBSCRIPTIONS BY SELECTED CHARACTERISTICS

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. Economic Characteristics – class of worker, commute to work, employment status, health insurance, income and benefits, industry,occupation, and poverty.

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. Information from the survey generates data that help determine how more than $400 billion in federal and state funds are distributed each year. Social Characteristics – ancestry, disability, educational attainment, fertility, grandparents, household, language spoken, marital status, place of birth, region of birth, relationships, residence, school enrollment, US citizenship status, veteran status, and year of entry

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

The SAHIE program updated its methodology to incorporate the estimates of health insurance coverage from the American Community Survey (ACS). The incorporation of the ACS into the modeling procedures has allowed for more detailed income group data as well as a higher level of precision in the estimates.

The American Dream Prosperity Index provides a comprehensive picture of prosperity in 50 states and Washington D.C.The Index, comprising over 200 indicators gathered from more than 80 separate data sources are divided into 3 main domains namely Inclusive Societies, Open Economies, and the Empowered People, under these 11 pillars and 48 sub-components. It is a transformational tool designed to help policymakers, investors, philanthropists, and community leaders strengthen the pathways from poverty to prosperity across the nation, enabling all Americans to achieve their dream. It also provides journalists, researchers, and citizens access to meaningful data to better understand the impact of decisions being made that affect their communities.  

The AHS survey is the most comprehensive national housing survey in the United States. Note: https://www.census.gov/programs-surveys/ahs/about/upcoming-releases/2023-release.html

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

The 10th biennial TEConomy/BIO report focuses on the economic footprint of the industry geographically including the latest trends in the bioscience industry for the nation, states, and metropolitan areas. 

Behavioral Risk Factor Data: Tobacco Use (2011 to present) 2011-2019. Centers for Disease Control and Prevention (CDC). State Tobacco Activities Tracking and Evaluation (STATE) System. BRFSS Survey Data. The BRFSS is a continuous, state-based surveillance system that collects information about modifiable risk factors for chronic diseases and other leading causes of death. The data for the STATE System were extracted from the annual BRFSS surveys from participating states. Tobacco topics included are cigarette and e-cigarette use prevalence by demographics, cigarette and e-cigarette use frequency, and quit attempts. NOTE: these data are not to be compared with BRFSS data collected 2010 and prior, as the methodologies were changed.

Forbes' annual Best States For Business ranks U.S. states based on measures of six categories relevant to businesses: costs, labor supply, regulatory environment, current economic climate, growth prospects and quality of life. Forbes factors in 40 metrics from 17 sources to determine the ranks across the six main areas. The overall scores are based on a combination of ranks in the six main categories.

In conjunction with the Centers for Disease Control and Prevention's Healthy Community Design Initiative, the Alliance publishes the biennial Benchmarking Report to collect and analyze data on bicycling and walking in all 50 states, the 52 largest U.S. cities, and a select number of midsized cities. The Report combines original research with over 20 government data sources to compile data on bicycling and walking levels and demographics, safety, funding, policies, infrastructure, education, public health indicators, and economic impacts. It's an essential go-to resource for public officials, advocates, decision makers, and researchers.

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/

New Privately-Owned Housing Units Authorized Unadjusted Units by State, Regions and Metropolitan Area

.

US : NAICS Sectors, Small Employment Sizes An enterprise is a business organisation consisting of one or more domestic establishments that were specified under common ownership or control. The enterprise and the establishment are the same for single-establishment firms. Each multi-establishment company forms one enterprise - the enterprise employment and annual payroll are summed from the associated establishments.

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 dataset provides detailed trade statistics on iron and steel commodities using the Harmonized System (HS) classification of goods (based on the 6-digit commodity level).

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. 

Estimates of Annual Fossil-Fuel CO2 Emitted for Each State in the U.S.A. and the District of Columbia for Each Year from 1960 through 2001. Consumption data for coal, petroleum, and natural gas are multiplied by their respective thermal conversion factors, which are in units of heat energy per unit of fuel consumed (i.e., per cubic foot, barrel, or ton), to calculate the amount of heat energy derived from fuel combustion. Results are expressed in terms of heat energy obtained from each fuel type. These energy consumption data were multiplied by their respective carbon dioxide emission factors, which are called carbon content coefficients by the U.S. Environmental Protection Agency (EPA). These factors quantify the mass of oxidized carbon per unit of energy released from a fuel. In the U.S.A., they are typically expressed in units of teragrams of carbon (Tg-C = 10^12 grams of carbon) per quadrillion British thermal units (quadrillion Btu = 10^15 Btu, or "quad"), and are highest for coal and lowest for natural gas. Our results are given in teragrams of carbon emitted. To convert to carbon dioxide, multiply by 44/12 (= 3.67).

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

Census: U.S. Regional Hispanic or Latino Population

Chance for Success Index Indicators, United States

Change-of-Address Stats on USPS FOIA Website

This dataset has indicators related to Characteristics of Children's Families of United States

  Definitions: The number of children and youth in the foster care system by race or Hispanic origin. Some states allow children to remain in the foster care system until their 18th birthday while other states have age limits that extend a few years beyond this. The current indicator includes children of all ages. Percent estimates of children in each race/Hispanic group are based on the total number of children in foster care with race/ethnicity data. A small number of AFCARS records across many states were missing information on the child’s race/Hispanic group and were also not included in the “unable to determine” category. These missing data are excluded from percentage and frequency distributions. Youth are categorized as being in foster care if they entered prior to the end of the current fiscal year and have not been discharged from their latest foster care spell by the end of the current fiscal year. Race or Hispanic origin are mutually exclusive categories. Children who are of Hispanic origin are not classified as any other race. National estimates include Puerto Rico. Data Source: Child Trends analysis of data from the Adoption and Foster Care Analysis and Reporting System (AFCARS), made available through the National Data Archive on Child Abuse and Neglect. Note - In source <.5% used for missing data we take that  as 0.5

City and Town Population Totals: 2010-2022, U.S.

Climate Change Knowledge Portal: CMIP6 Mean Projections

The Federal Reserve Bank of Philadelphia produces a monthly coincident index for each of the 50 states. The indexes are released a few days after the Bureau of Labor Statistics (BLS) releases the employment data for the states. The Bank issues a release each month describing recent trends in the state indexes, with special coverage of the three states in the Third District: Pennsylvania, New Jersey, and Delaware. The coincident indexes combine four state-level indicators to summarize current economic conditions in a single statistic. The four state-level variables in each coincident index are nonfarm payroll employment, average hours worked in manufacturing by production workers, the unemployment rate, and wage and salary disbursements plus proprietors' income deflated by the consumer price index (U.S. city average). The trend for each state’s index is set to the trend of its gross domestic product (GDP), so long-term growth in the state’s index matches long-term growth in its GDP. A dynamic single-factor model is used to create the state indexes. James Stock and Mark Watson developed the basic model for constructing a coincident index for the U.S. Theodore Crone and Alan Clayton-Matthews adapted the basic model for the states. The method involves a system of five major equations: one equation for each input variable and one equation for an underlying (latent) factor that is reflected in each of the indicator (input) variables. The underlying factor represents the state coincident index. The model and the input variables are consistent across the 50 states, so the state indexes are comparable to one another.

2019-20 year consider as 2020 and 2018-19 year consider as 2019

Combined Statistical Area Population Estimates, U.S.

U.S. Regional Data (County Wise) from Federal Financial Institutions Examination Council (US) Note: These data series are discontinued at source after 2020 Q3

Common Core of Data: State Dropout and Completion Data The report draws on a wide array of surveys and administrative datasets to present statistics on high school dropout and completion rates at the state and national levels. The report includes estimates of the percentage of students who drop out in a given 12-month period (event dropout rates), the percentage of young people in a specified age range who are high school dropouts (status dropout rates), and the percentage of young people in a specified age range who hold high school credentials (status completion rates). In addition, the report includes data on the percentage of students who graduate with a regular diploma within four years of starting ninth grade (adjusted cohort graduation rates).  

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.        

Comparison of State and Local Government Revenue in the United States

Comparison of State and Local Government Spending in the United States -5yr -1yr Fiscal Year 2028

Data cited at: Federal Financial Institutions Examination Council (US), Allocated Transfer Risk Reserves for Commercial Banks Federal Reserve Bank of St. Louis. FRED Data from Federal Financial Institutions Examination Council (US)

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  

Note: The year is Calendar year 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 US 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 2019 loan limits have been set under the HERA formula.  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

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. 

Congressional Districts 2012 Census Results, U.S. Census Bureau

States Affected and Category by States Affected: The impact of the hurricane on individual U.S. states based upon the Saffir-Simpson Hurricane Wind Scale (through the estimate of the maximum sustained [1-min] surface [10 m] winds at each state). TX S-South Texas, TX C-Central Texas, TX N-North Texas, LA-Louisiana, MS-Mississippi, AL-Alabama, FL NW-Northwest Florida, FL SW-Southwest Florida, FL SE-Southeast Florida, FL NE-Northeast Florida, GA-Georgia, SC-South Carolina, NC-North Carolina, VA-Virginia, MD-Maryland, DE-Delaware, NJ-New Jersey, NY-New York, PA-Pennsylvania, CT-Connecticut, RI-Rhode Island, MA-Massachusetts, NH-New Hampshire, ME-Maine. In Texas, south refers to the area from the Mexican border to Corpus Christi; central spans from north of Corpus Christi to Matagorda Bay and north refers to the region from north of Matagorda Bay to the Louisiana border. In Florida, the north-south dividing line is from Cape Canaveral [28.45N] to Tarpon Springs [28.17N]. The dividing line between west-east Florida goes from 82.69W at the north Florida border with Georgia, to Lake Okeechobee and due south along longitude 80.85W.) Occasionally, a hurricane will cause a hurricane impact (estimated maximum sustained surface winds) in an inland state. To differentiate these cases versus coastal hurricane impacts, these inland hurricane strikes are denoted with an "I" prefix before the state abbreviation. States that have been so impacted at least once during this time period include Alabama (IAL), Georgia (IGA), North Carolina (INC), Virginia (IVA), and Pennsylvania (IPA). The Florida peninsula, by the nature of its relatively landmass, is all considered as coastal in this database. Highest U.S. Saffir-Simpson Category: The highest Saffir-Simpson Hurricane Wind Scale impact in the United States based upon estimated maximum sustained (1-min) surface (10 m) winds produced at the coast. ("TS" indicates that the system caused only tropical storm conditions in the United States, though it was a hurricane at landfall. See "&" below.) Central Pressure: The observed or estimated central pressure of the hurricane at landfall. Maximum Winds: Estimated maximum sustained (1-min) surface (10 m) winds to occur along the U. S. coast. Winds are estimated to the nearest 10 kt for the period of 1851 to 1885 and to the nearest 5 kt for the period of 1886 to date. (1 kt = 1.15 mph.) * - Indicates that the hurricane center did not make a U.S. landfall (or substantially weakened before making landfall), but did produce the indicated hurricane-force winds over land. In this case, central pressure is given for the time that the hurricane winds along the coast were the strongest. & - Indicates that the hurricane center did make a direct landfall, but that the strongest winds likely remained offshore. Thus the winds indicated here are lower than in HURDAT. # - Indicates that the hurricane made landfall over Mexico, but also caused sustained hurricane force surface winds in Texas. The strongest winds at landfall impacted Mexico, while the weaker maximum sustained winds indicated here were conditions estimated to occur in Texas. Indicated central pressure given is that at Mexican landfall. Additional Note: Because of the sparseness of towns and cities before 1900 in some coastal locations along the United States, the above list is not complete for all states. Before the Gulf of Mexico and Atlantic coasts became settled, hurricanes may have been underestimated in their intensity or missed completely for small-sized systems (i.e., 2004's Hurricane Charley). The following list provides estimated dates when accurate tropical cyclone records began for specified regions of the United States based upon U.S Census reports and other historical analyses. Years in parenthesis indicate possible starting dates for reliable records before the 1850s that may be available with additional research: Texas-south > 1880, Texas-central > 1851, Texas-north > 1860, Louisiana > 1880, Mississippi > 1851, Alabama < 1851 (1830), Florida-northwest > 1880, Florida-southwest > 1900, Florida-southeast > 1900, Florida-northeast > 1880, Georgia < 1851 (1800), South Carolina < 1851 (1760), North Carolina < 1851 (1760), Virginia < 1851 (1700), Maryland < 1851 (1760), Delaware < 1851 (1700), New Jersey < 1851 (1760), New York < 1851 (1700), Connecticut < 1851 (1660), Rhode Island < 1851 (1760), Massachusetts < 1851 (1660), New Hampshire < 1851 (1660), and Maine < 1851 (1790).

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.

Data cited at: County Health Rankings-  https://www.countyhealthrankings.org/explore-health-rankings/texas/data-and-resources

County Population Totals: 2010-2019, U.S.

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/

Overview of Variants in Countries: This dataset contains, the proportion of total number of sequences (not cases), over time, that fall into defined variant groups. Countries are displayed if they have at least 70 sequences in any variant being tracked, over a period of at least 4 weeks. Countries are ordered by total number of sequences in tracked variants.   It is worth interpreting with caution:Not all samples are representative - sometimes some samples are more likely to be sequenced than others (for containing a particular mutation, for example)The last data point - this often has incomplete data and may change as more sequences come inFrequencies that are very 'jagged' - this often indicates low sequencing numbers and so may not be truly representative of the countryIn many places, sampling may not be equal across the region: samples may only cover one area or certain areas. It's important not to assume frequencies shown are necessarily representative.

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

FRED Data from CredAbility Nonprofit Credit Counseling & Education

Data cited at: Numbeo Methodology: The Index has been calculated twice per year by considering the latest 36 months. A). Beginning of the Year and B). Mid Year Crime Index is an estimation of the overall level of crime in a given city or a country. We consider crime levels lower than 20 as very low, crime levels between 20 and 40 as being low, crime levels between 40 and 60 as being moderate, crime levels between 60 and 80 as being high and finally crime levels higher than 80 as being very high. Safety index is, on the other way, quite the opposite of crime index. If the city has a high safety index, it is considered very safe.

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

The Sentencing Project Facts: State-by-State Data

The EPA Green Book’s Criteria Pollutant Nonattainment Summary Report provides summary information about population living in an area that is in nonattainment for at least one of the National Ambient Air Quality Standards (NAAQS).

Since high ambient temperatures can lead to negative health outcomes such as heat cramps, heat exhaustion, heat syncope, and heat stroke. Monitoring health conditions associated with extreme heat requires temperature and relative-humidity data at highly resolved spatio-temporal scales. This dataset presents the data on daily estimates of heat index and extreme temperature days during the summer months.

Deaths involving coronavirus disease 2019 (COVID-19), pneumonia, and influenza reported to NCHS by race, age, and state.   Number of deaths reported in this dataset are the total number of 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.

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 Veteran Population Projection Model 2020 (VetPop2020) provides the latest official Veteran population projection from the Department of Veterans Affairs (VA).  VetPop2020 is a deterministic projection model developed by the office of Predictive Analytics to estimate and project the Veteran Population from Fiscal Year (FY) 2020 to FY2050. Using the best available Veteran data at the end of FY2020 as the base population. VetPop2020 projects living and deceased Veteran counts by key demographic characteristics such as age, gender, period of service, and race/ethnicity at various geographic levels for the next 30 years

Fatality Analysis Reporting System (FARS) Source - https://crashstats.nhtsa.dot.gov/Api/Public/ViewPublication/813435

FRED Data from Weber, Warren E., Dwyer, Gerald P., Hafer, R.W.

Deaths from drug overdose have been identified as a significant public health burden in the United States in recent years. This report uses data from the National Vital Statistics System (NVSS) to highlight recent trends in drug overdose deaths, describing demographic and geographic patterns as well as the types of drugs involved.

Early-Childhood Education of United States

US General Election Early Vote Statistics 

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.

AdvaMed advocates for a legal, regulatory and economic environment that advances global health care by assuring worldwide patient access to the benefits of medical technology. It promotes policies that foster the highest ethical standards, rapid product approvals, appropriate reimbursement, and access to international markets. Medical technology innovators are committed to providing physicians the best tools to diagnose and treat patients. This commitment drives over 6,000 companies in the U.S. to create medical miracles everyday—leading to an 80 percent increase in patents for breakthrough medical technologies in the last decade

Education Accountability of United States, 2012

Education Achievement United States

Education Demographics Indicators United States. The data for each year is a cumulative sum of the values from the past five years. For example, the data for 2021 includes the sum of the values from 2017 to 2021.

United States : Finance Statistics

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.

Education Technology United States, 2007

Educational Attainment, U.S.

Data cited at: Rt.live-https://rt.live/ These are up-to-date values for Rt, a key measure of how fast the virus is growing. It’s the average number of people who become infected by an infectious person. If Rt is above 1.0, the virus will spread quickly. When Rt is below 1.0, the virus will stop spreading. The reason historical values change is that source is not producing a single point each day, but rather a single curve. One of the constraints of the model is that this curve be connected and smooth. So, if new data suggests that R~t~ should be higher, it will pull up previous values so that the newest point is connected. Imagine a rope lying on the ground. If you pick up the end of that rope, the rope needs to slope up to your hand. The same thing is roughly happening with the model. If all of a sudden a testing center releases far more tests than were expected, the R~t~ curve increases which drags up previous values of R~t~. Since case data is staggered in its arrival, a bunch of new cases will sometimes rewrite its view of history given the new data. 

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.

Indicator Details are as Below:Advanced Meters – This file, compiled from data collected on both Forms EIA-861 and EIA-861S, contains information on Automated Meter Readings (AMR) and Advanced Metering Infrastructure (AMI). (Formerly File 8)Balancing Authority – This file, contains the list of Balancing Authorities and the states they operate in, for the EIA-861 and EIA-861S. (Formerly File 1_cao)Demand Response (2013 forward) – This file, compiled from data collected on Form EIA-861 only, contains the number of customers enrolled, energy savings, potential and actual peak savings, and associated costs.Distribution Systems (2013 forward) – This file, compiled from data collected on Form EIA-861 only, contains the number of distribution circuits and circuits with voltage optimization.Dynamic Pricing (2013 forward) – This file, compiled from data collected on Form EIA-861 only, contains the number of customers enrolled in various programs, i.e. time of use, real time, variable peak and critical peak pricing, and critical peak rebate programs.Energy Efficiency (2013 forward) – This file, compiled from data collected on Form EIA-861 only, contains incremental and life cycle data on energy savings, peak demand savings, weighted average life, and associated costs.Mergers (2007 forward) – This file, compiled from data collected on Form EIA-861 only, contains information on mergers and acquisitions. (Formerly File 7)Net Metering (2007 forward) – This file, compiled from data collected on Form EIA-861 only, contains number of customers and displaced energy, by sector and state. For 2010 forward, it contains capacity, customer count, and energy sold back (an optional question on the survey) by sector and state and by technology type, i.e. photovoltaic, wind, and/or other.Non Net Metering Distributed – This file, compiled from data collected on Form EIA-861 only, contains information on utility or customer-owned distributed generators such as the number, capacity, and technology type of generators. Capacities by photovoltaic and storage generation types were added in 2010, fuel cells were added in 2016. Starting in 2016, this data is now collected at the sector level. (Formerly Distributed Generation, Formerly File 6)Operational Data – This file, compiled from data collected on Form EIA-861 only, contains aggregate operational data for the source and disposition of energy and revenue information from each electric utility in the country, including power marketers and federal power marketing administrations. (Formerly File 1)Reliability (2013 forward) – This file, compiled from data collected on Form EIA-861 only, contains SAIDI and SAIFI data.Sales to Ultimate Customers – This file, compiled from data collected on the Form EIA-861 and an estimate from Form EIA-861S for data by customer sector, contains information on retail revenue, sales, and customer counts by state, balancing authority, and class of service (including the transportation sector which was added in 2003) for each electric distribution utility or energy service provider. (Formerly File 2)Sales to Ultimate Customers, Customer Sited – This file, compiled from data collected on the Form EIA-923 only, contains information on retail revenue, sales, and customer counts by state and balancing authority. This includes retail sales from any units located at a customer site.Utility Data (2007 forward) – This file, compiled from data collected on Form EIA-861 only, contains information on the types of activities each utility engages in, the NERC regions of operation, whether the utility generates power, whether it operates alternative-fueled vehicles, and, beginning in 2010, the ISO or RTO region in which the entity conducts operations. (Formerly File 1_a)Demand-Side Management (discontinued after 2012) – This file, compiled from data collected on both Form EIA-861 and, for time-based rate programs, Form EIA-861S, contains information on electric utility demand-side management programs, including energy efficiency and load management effects and expenditures. Beginning in 2007, it also contains the number of customers in time-based rate programs. (Formerly File 3)Green Pricing (discontinued after 2012) – This file, compiled from data collected on Form EIA-861 only, contains number of customers, sales, and revenue, by sector and state. (Formerly File 5)  

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

Employee total potential out-of-pocket medical costs (premium contribution + deductible), as a share of state median income (%)

employer-sponsored insurance spending per enrollee

U.S. Employment by Sector -  Monthly data

US Employment Situation of Veterans, 2018

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.

English-language learners (ELL) United States

The Emergency Broadband Benefit (EBB) Program ended on December 31, 2021 with 9,048,536 households enrolled. The EBB Program was replaced by the Affordable Connectivity Program (ACP) on December 31, 2021.

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 Environmental Scanning and Program Characteristics (ESPC) Database, is intended to facilitate cross-State analyses. Information from the ESPC database can be linked to the Medicaid Analytic eXtract (MAX) files and other Medicaid data to support program and comparative effectiveness research (CER), policy studies, and program evaluations. The ESPC database and companion User Guide can serve as a stand-alone tool to facilitate intra–and inter–state analysis stemming from the implementation of health reform.

All States provided estimates for public supply, domestic, irrigation, livestock, aquaculture, industrial,mining, and thermoelectric power water use. All States also provided estimates of public supply deliveries for domestic use.All States will have estimates of the total population served by public supply. States optionally may have estimated public supply population served by groundwater and surface water.All States will have estimates of total irrigation. States optionally may have estimated subtotals for crop irrigation and golf-course irrigation.No consumptive-use data were collected nationally for any of the categories for 2010.No commercial water-use data were collected nationally for 2010.No wastewater release data were collected nationally for 2010.No hydroelectric power instream use data were collected nationally for 2010.Public-supply deliveries for commercial, industrial, and thermoelectric power were not collected nationally for 2010.

Estimates of excess deaths can provide information about the burden of mortality potentially related to COVID-19, beyond the number of deaths that are directly attributed to COVID-19. Excess deaths are typically defined as the difference between observed numbers of deaths and expected numbers. This visualization provides weekly data on excess deaths by jurisdiction of occurrence. Counts of deaths in more recent weeks are compared with historical trends to determine whether the number of deaths is significantly higher than expected. Estimates of excess deaths can be calculated in a variety of ways, and will vary depending on the methodology and assumptions about how many deaths are expected to occur. Estimates of excess deaths presented in this web page were calculated using Farrington surveillance algorithms (1). For each jurisdiction, a model is used to generate a set of expected counts, and the upper bound of the 95% Confidence Intervals (95% CI) of these expected counts is used as a threshold to estimate excess deaths. Observed counts are compared to these upper bound estimates to determine whether a significant increase in deaths has occurred. Provisional counts are weighted to account for potential under reporting in the most recent weeks. However, data for the most recent week(s) are still likely to be incomplete. Only about 60% of deaths are reported within 10 days of the date of death, and there is considerable variation by jurisdiction.

The Higher Education Research and Development Survey, successor to the Survey of Research and Development Expenditures at Universities and Colleges, is the primary source of information on R&D expenditures at U.S. colleges and universities. The survey collects information on R&D expenditures by field of research and source of funds and also gathers information on types of research and expenses and headcounts of R&D personnel. The survey is an annual census of institutions that expended at least $150,000 in separately budgeted R&D in the fiscal year.   Courtesy: National Science Foundation

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. 

Exports from Manufacturing Establishments includes estimates for the value of manufactured exports and related employment. This report shows estimates at the national and state level for "direct" exports (exports manufactured in the United States (U.S.) and consumed in foreign markets), supporting shipments (intermediate goods and services required to manufacture exported goods), and related employment for the manufacturing sector. In addition, supporting employment outside the manufacturing sector associated with manufactured exports is provided. The data in this report also include estimates of employment associated with transporting manufactured goods for export from the plant of manufacture to the port of export. 1. Manufacturing and Non-manufacturing employment computation is based on state-based input-output tables from the Bureau of Economic Analysis 2. "Other" Employment related to manufactured exports include forestry, agriculture, and business services. 3. Civilian Employment represents state data from the State and Area Employment, Hours, and Earnings series from the Bureau of Labor Statistics, plus the difference between the total civilian labor force employment and the sum of the private nonagricultural wage and salary workers from the Bureau of Labor Statistics' series "Geographic Profile of Employment and Unemployment. 4. Private Sector Employment represents the figure for civilian employment less the total number of government workers from the Bureau of Labor Statistics State and Area Employment, Hours, and Earnings series. 5. Export-related employment data shown do not include jobs involved in the exports of nonmanufactured goods, such as farm products, minerals, and services sold to foreign buyers. Indirect exports exclude imported items.

FCA US, Ford and General Motors Supporting Jobs & Economic Activity Across America

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.

FHIR: Fast Healthcare Interoperability Resources HRR: Healthcare Referral Region

.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.

This dataset presents internationally comparable data on expenditure per student on educational institutions at sub-national level. Expenditure per student on educational institutions at a particular level of education is calculated by dividing total expenditure on educational institutions at that level by the corresponding full-time equivalent enrolment. Expenditure per student are converted into equivalent USD by using national purchasing power parities (PPPs) for GDP. Further work on the cost of living at subnational level is required to fully adjust expenditure per student available in this dataset.

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.

The activities of multinational enterprises statistics available here provide a picture of the overall activities of US affiliates of foreign parents and contain a wide variety of indicators of their financial structure and operations. These statistics cover items that are needed in analyzing the characteristics, performance, and economic impact of MNEs, and are obtained from mandatory surveys of US affiliates of foreign parents conducted by BEA.

The FMHPI provides a measure of typical price inflation for houses within the United States. Values are calculated monthly and released at the end of the following month. For example, the FMHPI for March is published in late April. Seasonally and non-seasonally adjusted series are available at three levels of geographical aggregation: Metropolitan Statistical Area (MSA), state, and national. All series begin in January 1975. The national index is defined as a weighted average of the 50 states and Washington, D.C. indices. The FMHPI is based on an ever-expanding database of loans purchased by either Freddie Mac or Fannie Mae. Data cited at: Freddie Mac-http://www.freddiemac.com/research/indices/house-price-index.page#:~:text=Freddie%20Mac%20House%20Price%20Index,is%20published%20in%20late%20April

The Freight Analysis Framework (FAF) creates a comprehensive picture of freight movement among states and major metropolitan areas by all modes of transportation. The FAF integrates data from a variety of sources. Starting with data from the Commodity Flow Survey (CFS) and international trade data from the Census Bureau, FAF incorporates data from agriculture, extraction, utility, construction, service, and other sectors. The FAF is produced by BTS with support from FHWA.

Update - New Version FAF5.5 - The new version of the Freight Analysis Framework (FAF) provides estimates for tonnage, value, and ton-miles by origin-destination pair of FAF regions, commodity type, and mode for:Base year (2017)Annual estimates (2018–2021)Forecast year estimates (2023–2050)State-level historical trend estimates (1997–2012)

Texas Freight Mobility Plan

Definition: The Uniform Crime Reporting (UCR) Program defines law enforcement officers as individuals who ordinarily carry a firearm and a badge, have full arrest powers, and are paid from governmental funds set aside specifically for sworn law enforcement representatives. User’s note:  Because of law enforcement’s varied service requirements and functions, as well as the distinct demographic traits and characteristics of each jurisdiction, readers should use caution when drawing comparisons between agencies’ staff levels based on police employment data from the UCR Program. In addition, the data presented here reflect existing staff levels and should not be interpreted as preferred officer strengths recommended by the FBI. Lastly, it should be noted that the totals given for sworn officers for any particular agency reflect not only the patrol officers on the street but also the officers assigned to various other duties such as those in administrative and investigative positions and those assigned to special teams. Data collection: Each year, law enforcement agencies across the United States report to the UCR Program the total number of sworn law enforcement officers and civilians in their agencies as of October 31. Civilian employees include personnel such as clerks, radio dispatchers, meter attendants, stenographers, jailers, correctional officers, and mechanics provided that they are full-time employees of the agency.

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.

Geographic Profile series are taken from the Current Population Survey (CPS; see the Labor Force survey), conducted by the Bureau of the Census, which produces information about employment and unemployment in States, classified by a variety of demographic and economic characteristics.

Government Revenue and Expenditure by Category, Texas (Annual Report)

Graduation Indicators of United States, 2013

Green Goods and ServicesDimensionsData ElementAreaIndustryAlt EnergyGreen QuartileOwnRate LevelSizeSeasonal

1. https://worldpopulationreview.com/states/gun-ownership-by-state/ 2.TheDailyBeast - http://www.thedailybeast.com/articles/2010/06/28/states-with-the-most-guns.html 2.USliberals - http://usliberals.about.com/od/Election2012Factors/a/Gun-Owners-As-Percentage-Of-Each-States-Population.htm 3.WashingtonPost - http://www.washingtonpost.com/wp-srv/health/interactives/guns/ownership.html 4.FBI - http://www.fbi.gov/about-us/cjis/nics/reports/1998_2014_state_program_to_date_purpose_ids.pdf

This dataset covers historical hate crime statistics through 2019. For the latest Hate Crime Statistics, please visit https://knoema.com/USHCSAT2020/hate-crime-statistics-of-u-s  

The Health, United States series presents an annual overview of national trends in health statistics. The report contains a Chartbook that assesses the nation's health by presenting trends and current information on selected measures of morbidity, mortality, health care utilization and access, health risk factors, prevention, health insurance, and personal health care expenditures. This year's Chartbook includes a Special Feature on the health of adults aged 55–64. The report also contains 123 Trend Tables organized around four major subject areas: health status and determinants, health care utilization, health care resources, and health care expenditures. A companion report—Health, United States: In Brief—featuresinformation extracted from the full report. The complete report, In Brief, and related data products are available on the Health, United States website.

Health Indicators on US States

Health Insurance in the United States

Global Burden of Disease Study 2016 (GBD 2016) Healthcare Access and Quality Index Based on Amenable Mortality 1990–2016. Global Burden of Disease Study 2016 (GBD 2016) estimates were used in an analysis of personal healthcare access and quality for 195 countries and territories, as well as selected subnational locations, over time. This dataset includes the following global, regional, national, and selected subnational estimates for 1990-2016: age-standardized risk-standardized death rates from 24 non-cancer causes considered amenable to healthcare; age-standardized mortality-to-incidence ratios for 8 cancers considered amenable to healthcare; and the Healthcare Access and Quality (HAQ) Index and individual scores for each of the 32 causes on a scale of 0 to 100. Code used to produce the estimates is also included. Results were published in The Lancet in May 2018 in "Measuring performance on the Healthcare Access and Quality Index for 195 countries and territories and selected subnational locations: a systematic analysis from the Global Burden of Disease Study 2016

Healthy Marketplace Index (HMI) project is an initiative of HCCI, it tracks drivers of health care spending across 186 cities in the U.S. 

This dataset presents estimates to determine population exposure to extreme heat.

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 

Annual Vehicle Distance Traveled. The dataset provides information on annual highway travel in the United States. This is broken down by State, functional system, highway category, vehicle type, and other variables.

This dataset presents county-level estimates of temperature and heat index.

Note that values are given for marketing years, e.g. 2016 corresponds to 2015/2016 marketing year, 2015 refers to 2014/2015 marketing year, etc.   Market year starts in December and ends in November of the following year.

In December 2022, IHME paused its COVID-19 modeling. IHME has developed projections for total and daily deaths, daily infections and testing, hospital resource use, and social distancing due to COVID-19 for a number of countries. Forecasts at the subnational level are included for select countries. The projections for total deaths, daily deaths, and daily infections and testing each include a reference scenario: Current projection, which assumes social distancing mandates are re-imposed for 6 weeks whenever daily deaths reach 8 per million (0.8 per 100k). They also include two additional scenarios: Mandates easing, which reflects continued easing of social distancing mandates, and mandates are not re-imposed; and Universal Masks, which reflects 95% mask usage in public in every location. Hospital resource use forecasts are based on the Current projection scenario. Social distancing forecasts are based on the Mandates easing scenario. These projections are produced with a model that incorporates data on observed COVID-19 deaths, hospitalizations, and cases, information about social distancing and other protective measures, mobility, and other factors. They include uncertainty intervals and are being updated daily with new data. These forecasts were developed in order to provide hospitals, policy makers, and the public with crucial information about how expected need aligns with existing resources, so that cities and countries can best prepare. Dataset contains Observed and Projected data

30-day hospital readmissions among Medicare beneficiaries age 65 and older per 1,000 beneficiaries, by income

These annual national indexes should be considered developmental. As with the standard FHFA HPIs, revisions to these indexes may reflect the impact of new data or technical adjustments. Indexes are calibrated using appraisal values and sales prices for mortgages bought or guaranteed by Fannie Mae and Freddie Mac. Index values always reflect data from that year. Three HPI values are provided and, since the indexes reflect cumulative appreciation since a certain period, the values reflect the base year being used (annual appreciations are the same). 

Note: The date in the dataset has been considered as the last date of the surveys, for example, "Week 13 Household Pulse Survey: August 19 – August 31" , so 31st August is considered as the dataset date.- https://www.census.gov/programs-surveys/household-pulse-survey/data.html ttps://www.census.gov/data-tools/demo/hhp/assets/data/hhp.json  

US Regional Households

Annual Estimates of Housing Units for the United States and States: April 1, 2010 to July 1, 2019

Housing Vacancies and Homeownership in US https://www.census.gov/housing/hvs/data/ann19ind.html 

Knoema modified the original dataset to include calculated indicators of "Total county population per ICU bed" and "Number of ICU beds per 100,000 population.”   Notes: This dataset includes the most recent reports, from FY 2018 and 2019. Some hospitals may have closed since then, and some hospitals may have made errors in their reporting. In some cases, beds in small satellite hospitals are reported in the main hospital's filing. Hospitals for veterans run by the Department of Defense are not included in this dataset.  

Disconnected youth, also referred to as opportunity youth, are teenagers and young adults between the ages of 16 and 24 who are neither in school nor working Research reveals that being disconnected as a young person has long-term consequences; it’s associated with lower earnings, less education, worse health, and even less happiness in later adulthood. The duration i.e. how long a young person is disconnected also matters, with longer spells of disconnection associated with worse outcomes. This dataset shows the impact of Covid-19 on disconnected youth rate in the USA.

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

Year represents, for any particular company, the time series of that particular company. For example xyz company has data for 10 years (2007-2016) then in "year" it shows 10, if another company ABC has time series of 5 years (2007-2011) then it shows 5.   Note: Before 2007, data is not available but it has been counted under "Year".

The dataset contains selected income and tax items classified by State, ZIP Code, and size of adjusted gross income. The data are based on individual income tax returns filed with the IRS. The dataset includes following items:Number of Returns, which approximates the number of HouseholdsNumber of Personal Exemptions, which approximates the PopulationAdjusted Gross Income Wages and SalariesDividends Before ExclusionInterest Received 

Industry Productivity and CostsDimensionsMeasureAreaSectorIndustryDurationTypeSeasonal

The data are from the linked infant birth and death files. To create linked data files, death certificates are linked with corresponding birth certificates for infants who die in the U.S. before their first birthday. The linked file is used for calculating infant mortality rates by race and ethnicity because these variables are more accurately collected on the birth certificate than the death certificate. For this table, the period linked file is used (the numerator of the mortality rates includes the deaths occurring in a given calendar year whether the birth occurred in that year or the preceding year).

In the United States, state laws require death certificates to be completed for all deaths, and Federal law mandates national collection and publication of deaths 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 death certificates.

The ILR rankings aim to quantify how corporate attorneys, as significant participants in state courts, view the state systems by measuring and synthesizing their perceptions of key elements of each state’s liability system. The states are ranked on a scale of 1-50, where 1 refers to best litigation environment.

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 students enrolled in the fall, by distance education status and level of student. 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 file has multiple records per institution. Records are uniquely defined by the variables IPEDS ID (UNITID), and level of student (EFDELEV). Each record will contain the total students enrolled, students enrolled exclusively in distance education courses, students enrolled in some education distance education courses and students not enrolled in any distance education courses. The number of students enrolled in exclusively distance education courses are also reported by the following location categories: located in the same state/jurisdiction as the institution; in a different state/jurisdiction than the institution; in the U.S. but the state/jurisdiction is unknown; and residing outside the U.S..  

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 data on the total entering class, first-year retention rates and the student-to-faculty ratio. The total entering class is the number of incoming students (students enrolling for the first time in a postsecondary institution versus students transferring in from another postsecondary institution) at an institution. This measure permits the calculation of the graduation rate cohort as a proportion of the total entering student body. This dataset contains data on the total entering class, first-year retention rates and the student-to-faculty ratio. The total entering class is the number of incoming students (students enrolling for the first time in a postsecondary institution versus students transferring in from another postsecondary institution) at an institution. This measure permits the calculation of the graduation rate cohort as a proportion of the total entering student body. The first-year retention rate data measure the percentage of first-year students who had persisted in or completed their educational program a year later (began in fall 2016 and persisted or completed in fall 2017). Institutions can exclude the number of students from the first-time cohort who left the institution for any of the following reasons: died or were totally and permanently disabled; to serve in the armed forces (including those called to active duty); to serve with a foreign aid service of the Federal Government (e.g. Peace Corps); or to serve on official church missions. Beginning with the fall 2016 data, instititions can include first-time bachelor’s-seeking (or equivalent) study abroad students who were excluded from the first-time cohort  but who have re-enrolled at the institution their second year. Student-to-faculty ratio is defined as  total FTE students (not in graduate or professional programs) divided by total FTE instructional staff (not teaching in graduate or professional programs). All data on this file is applicable only to institutions with undergraduate students. Institutions with traditional academic year calendar systems (semester, quarter, trimester or  4-1-4) report their enrolment as of October 15 or the official fall reporting date of the institution (academic year). Institutions with calendar systems that differ by program or allow continuous enrolment report students that are enrolled at any time between August 1 and October 31 (program year).  Only academic year institutions report entering class data. Institutions with short programs (less-than-one-year) will not have data on retention.

This dataset contains institutional finance data for institutions that use accounting standards established by the Financial Accounting Standards Board (FASB) . All private not-for-profit institutions are included in this file. There are some public institutions that use the FASB model and are also included. Finance data includes institutional revenues by source, expenditures by functional categories, expenditures by natural classification categories, endowments, and assets and liabilities. This information provides context for understanding the cost and resources of providing postsecondary education. It is used to calculate the contribution of postsecondary education to the gross national product. Beginning with fiscal year 2016 detailed expenditures by function and the natural classifications of fringe benefits, operations and maintenance of plant, depreciation and interest are no longer available.

This data file contains institutional finance data for private for-profit institutions that use accounting standards established by the Financial Accounting Standards Board (FASB). Finance data includes institutional revenues by source, expenditures by functional categories, expenditures by natural classification categories, and assets and liabilities. This information provides context for understanding the cost and resources of providing post secondary education. It is used to calculate the contribution of post secondary education to the gross national product. Beginning with fiscal year 2016 detailed expenditures by function and the natural classifications of fringe benefits, operations and maintenance of plant, depreciation and interest are no longer available.

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.

This dataset contains the number of staff, total salary outlays and average salaries of full-time, nonmedical, instructional staff by academic rank, number of months worked, and gender. The categories for number of months worked are 9-, 10-, 11- and 12-months. Number of staff working less than 9 months are also available, but salary data are not available for this group. Equated 9-month salary outlays and equated 9-month average salaries are also available by academic rank and gender. For details see the variables listed in the description tab. This data file has multiple records for each institution. Each record is uniquely defined by the variables IPEDS ID (UNITID), and the variable academic rank (ARANK) of full-time instructional staff. "This dataset contains the number of staff, total salary outlays and average salaries of full-time, nonmedical, instructional staff by academic rank, number of months worked, and gender. The categories for number of months worked are 9-, 10-, 11- and 12-months. Number of staff working less than 9 months are also available, but salary data are not available for this group. Equated 9-month salary outlays and equated 9-month average salaries are also available by academic rank and gender. For details see the variables listed in the description tab. This data file has multiple records for each institution. Each record is uniquely defined by the variables IPEDS ID (UNITID), and the variable academic rank (ARANK) of full-time instructional staff. Number of staff working less than 9 months are also available, but salary data are not available for this group. Equated 9-month salary outlays and equated 9-month average salaries are also available by academic rank and gender. For details see the variables listed in the description tab. This data file has multiple records for each institution. Each record is uniquely defined by the variables IPEDS ID (UNITID), and the variable academic rank (ARANK) of full-time instructional staff. Number of staff working less than 9 months are also available, but salary data are not available for this group. Equated 9-month salary outlays and equated 9-month average salaries are also available by academic rank and gender. For details see the variables listed in the description tab. This data file has multiple records for each institution. Each record is uniquely defined by the variables IPEDS ID (UNITID), and the variable academic rank (ARANK) of full-time instructional staff. Between 2012 and 2015 salary information were not available by number of months worked. Equated 9-month average salaries were available, but because of the lack of detailed salary data by the number of months worked, it is not consistent with equated 9-month salary data generated in 2016.  Prior to 2012, number of staff and salary information were available for 9/10 months worked and 11/12 months worked. Equated 9-month average salaries and equated 9-month salary outlays were available and is more consistent with the 2016 equated salaries. Prior to 2016 the number of months worked were referred to as contract lengths. In 2016, the salary survey collection screens used the "" number of months worked "" terminology.    This dataset also contains the number and salary outlays for full-time, nonmedical, non-instructional staff by occupational category

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.

Jobs with a future of United States, 2005

Data cited at: Prof.Prof. Lauren Gardner; Center for Systems Science and Engineering at John Hopkins University, blog Post -  https://systems.jhu.edu/research/public-health/ncov/   On December 31, 2019, the World Health Organization (WHO) was informed of an outbreak of “pneumonia of unknown cause” detected in Wuhan City, Hubei Province, China – the seventh-largest city in China with 11 million residents. As of February 04, 2020, there are over 24,502 cases confirmed globally, including cases in at least 30 regions in China and 30 countries.  Interests: In-Market Segments Knoema All Users   Knoema modified the original dataset to include calculations per million.   https://knoema.com/WBPEP2018Oct https://knoema.com/USICUBDS2020 https://knoema.com/NBSCN_P_A_A0301 https://knoema.com/IMFIFSS2017Nov https://knoema.com/AUDSS2019 https://knoema.com/UNAIDSS2017 https://knoema.com/UNCTADPOPOCT2019Nov https://knoema.com/WHOWSS2018 https://knoema.com/KPMGDHC2019

Dataset allows to conduct comparison of US state Kentucky with other states, comparison of Eastern and Western Kentucky and comparison of Kentucky counties.

Wage and salary workers paid hourly rates with earnings at/below the prevailing federal minimum wage, U.S.

NCHS - Leading Causes of Death: United States This dataset presents the age-adjusted death rates for the 10 leading causes of death in the United States beginning in 1999. Data are based on information from all resident death certificates filed in the 50 states and the District of Columbia using demographic and medical characteristics. Age-adjusted death rates (per 100,000 population) are based on the 2000 U.S. standard population. Populations used for computing death rates after 2010 are postcensal estimates based on the 2010 census, estimated as of July 1, 2010. Rates for census years are based on populations enumerated in the corresponding censuses. Rates for non-census years before 2010 are revised using updated intercensal population estimates and may differ from rates previously published. Causes of death classified by the International Classification of Diseases, Tenth Revision (ICD–10) are ranked according to the number of deaths assigned to rankable causes. Cause of death statistics are based on the underlying cause of death. 

Characteristics of same sex couple households from 2005 till 2017. Notes: -Beginning with 2013 data products, tables reflect edit/processing changes which show same-sex married couples along with all married couples. Tables that have a line for "married couples" will include same-sex married couples, unless otherwise noted, and the marital status for those adults will be shown as "now married" or "married, spouse present." -For 2008, changes in the questionnaire format and data capture procedures between explanation, see the note on the Same-sex page: http://www.census.gov/hhes/samesex/data/acs.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

Data citation:International Long Term Care Policy Network, Avik Roy, The Foundation for Research on Equal Opportunity retrieved from The Foundation for Research on Equal Opportunity with approval dated 25th August 2020.

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 .

(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.

Mass Layoff StatisticsDimensionsData ElementRegionIndustryData SeriesIndustry Base

Note: For 2022 data is as of July 1 2022 This dataset provides provides eligibility levels in each state for key coverage groups that use Modified Adjusted Gross Income (MAGI), as of July 1, 2022. The data represent the principal, but not all, MAGI coverage groups in Medicaid, the Children’s Health Insurance Program (CHIP), and the Basic Health Program (BHP). All income standards are expressed as a percentage of the federal poverty level (FPL). The MAGI-based rules generally include adjusting an individual’s income by an amount equivalent to a 5% FPL disregard. Other eligibility criteria also apply, such as citizenship, immigration status, and state residency.

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.

Metropolitan and Micropolitan Statistical Area Population Estimates, U.S.

Highway Travel: Functional System Length and Federal-AID Highway length

The USGS Mineral Resources Program (MRP) provides scientific information for objective resource assessments and unbiased research results on mineral potential, production, consumption, and environmental effects. The MRP is the sole Federal source for this information. Values of 2019 are estimated.

Data cited at: (https://www.numbeo.com/cost-of-living/historical-prices-by-city?displayCurrency=USD&year=2016&itemId=13)

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.

Note: The source has discontinued this dataset with note-"With the discontinuation of the database that is the input for the MEI, we will no longer update the index after March 31, 2021. For questions, please contact Tyler Atkinson ( [email protected] < [email protected]>;)"   The Dallas Fed Mobility and Engagement Index (formerly the “Social Distancing Index”) summarizes the information in seven different variables based on geolocation data collected from a large sample of mobile devices to gain insight into the economic impact of the pandemic. The Mobility and Engagement Index measures the deviation from normal mobility behaviors induced by COVID-19. The updated name recognizes that social distancing, or the limiting of close contact with others outside your household, can be practiced while mobility and engagement improve. Along with revising the index’s name, we also changed the sign of the index to make it more intuitive as a measure of mobility and engagement. The underlying data is provided by SafeGraph. The national series is aggregated from county-level data with device counts as weights. Similar for the states. In the county files, the county name is in the first row, with FIPS code in the variable name. MSA data are for metro statistical areas (MSA), aggregated from county data using the March 2020. MSA names are in the first row, and CBSA codes in the variable name. The index is scaled so that the average of January-February is zero, and the lowest weekly value (week ended April 11) is -100. File names including 'weekly' are averages of the daily data. The data corresponds to the last day of the calendar week.

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.

In the United States, state laws require death certificates to be completed for all deaths, and Federal law mandates national collection and publication of deaths 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 death certificates

In the United States, State laws require death certificates to be completed for all deaths, and Federal law mandates national collection and publication of data on deaths. 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 statistical information from death certificates

Data on motor vehicle registrations from The Highway Statistics Series (table MV1)

"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 Center for Education Statistics Four-Year Adjusted Cohort Graduation Rates (%), by Race/Ethnicity and State

The 2020 Index is the seventh in a series of annual releases of data and analysis on national health security and preparedness. The first two Index releases in December 2013 and December 2014 were supported by the U.S. Centers for Disease Control and Prevention; beginning with the third release in April 2016, support for the Index was provided by the Robert Wood Johnson Foundation, with the Program Management Office located at the University of Kentucky. Expert workgroups provide input and feedback on Index production throughout the year, while a National Advisory Committee provides guidance to the Foundation and Program Management Office on strategic issues.

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.

U.S. Census Bureau - National Population Totals, State wise, U.S

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

This dataset presents the six-year college completion rates nationally and by state, by tracking the enrollment and completion outcomes for the fall 2015 cohort of beginning college students through June 2021. It accounts for all students who enter postsecondary education for the first time each fall, enrolling full-time or part-time at two-year or four-year institutions, and completing at any U.S. degree-granting institution. It includes those who complete after transfer, not just completions at the starting institution. Thus, the results more fully capture diverse pathways to success, which increasingly involve mobility across institutions and across state lines, re-entry after stop-out, and changes in enrollment intensities.

U.S. Regional Data (County Wise) from U.S. Patent and Trademark Office

 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

This entry gives the total number of airports or airfields recognizable from the air. The runway(s) may be paved (concrete or asphalt surfaces) or unpaved (grass, earth, sand, or gravel surfaces) and may include closed or abandoned installations. Airports or airfields that are no longer recognizable (overgrown, no facilities, etc.) are not included. Note that not all airports have accommodations for refueling, maintenance, or air traffic control.

Data cited at: AllClear.App-https://home.allclear.app/  

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.

Number of schools, students, and teachers in regular schools with membership for the 100 largest metropolitan statistical areas in the United States Note: Membership is the count of students enrolled on October 1 of the reported school year. Analysis includes only regular schools with membership greater than zero. Data include all 50 states and the District of Columbia. Operating schools include all those providing services during the reported school year. New schools are schools opened for the first time within the school year reported. Continuing operations schools include schools that provided services in the prior school year. Counts of students and teachers for closed schools are for the prior school year. For example, counts of students for schools closed in school year 2002–03 are based on enrollments for these schools in school year 2001–02. Source: U.S. Department of Education, National Center for Education Statistics, Common Core of Data (CCD), "Public Elementary/Secondary School Universe Survey," 1999–2000, Version 1b; 2000–01, Version 1a; 2001–02, Version 1a; 2002–03, Version 1a; 2003–04, Version 1a; 2004–05, Version 1b; 2005–06, Version 1a; 2006–07, Version 1c; 2007–08, Version 1b; 2008–09, Version 1b; 2009–10, Version Provisional 2a; and 2010–11, Version Provisional 2a.

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

The FBI's Crime Data Explorer (CDE) aims to provide transparency, create easier access, and expand awareness of criminal, and noncriminal, law enforcement data sharing; improve accountability for law enforcement; and provide a foundation to help shape public policy with the result of a safer nation. 

Index Period: January 4th - January 31st Indexing Type: Seasonally adjusted change since January 2020. Data is indexed in 2019 and 2020 as the change relative to the January index period. We then seasonally adjust by dividing year-over-year, which represents the difference between the change since January observed in 1 2020 compared to the change since January observed since 2019. We account for differences in the dates of federal holidays between 2019 and 2020 by shifting the 2019 reference data to align the holidays before performing the year-over-year division.

BR = Bedroom. FMR = Fiscal Year 2020 Fair Market Rent. The higher of the state or federal minimum wage is used in calculations. Local minimum wages are not used.

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).

This dataset presents the measure of participation and performance that shows success on the Advanced Placement(AP) Exam. It represents only U.S. public school students. Source: https://www.fldoe.org/core/fileparse.php/5673/urlt/21FLAPCohortDataReport.pdf

Data cited: SHADAC analysis of [DATA SOURCE], State Health Compare, SHADAC, University of Minnesota, statehealthcompare.shadac.org, Accessed [DATE]: 1st July 2021.Notes: Dollar amount represents state per capita public health funding during the fiscal year. Figures represent state funding only. Data not available for 2006.