United States Unemployment Rate: American Indian or Alaska Native data was reported at 5.500 % in Apr 2025. This records a decrease from the previous number of 6.600 % for Mar 2025. United States Unemployment Rate: American Indian or Alaska Native data is updated monthly, averaging 9.150 % from Jan 2000 (Median) to Apr 2025, with 304 observations. The data reached an all-time high of 28.600 % in Apr 2020 and a record low of 3.900 % in Mar 2024. United States Unemployment Rate: American Indian or Alaska Native data remains active status in CEIC and is reported by U.S. Bureau of Labor Statistics. The data is categorized under Global Database’s United States – Table US.G: Current Population Survey: Unemployment Rate.

Graph and download economic data for Unemployment Rate - Native Born, Men (LNU04073414) from Jan 2007 to Jul 2025 about native born, males, 16 years +, household survey, unemployment, rate, and USA.

United States Unemployment: American Indian or Alaska Native data was reported at 103.000 Person th in Apr 2025. This records a decrease from the previous number of 128.000 Person th for Mar 2025. United States Unemployment: American Indian or Alaska Native data is updated monthly, averaging 132.500 Person th from Jan 2000 (Median) to Apr 2025, with 304 observations. The data reached an all-time high of 491.000 Person th in Apr 2020 and a record low of 64.000 Person th in Sep 2000. United States Unemployment: American Indian or Alaska Native data remains active status in CEIC and is reported by U.S. Bureau of Labor Statistics. The data is categorized under Global Database’s United States – Table US.G: Current Population Survey: Unemployment.

United States Unemployment Rate: Native Born data was reported at 3.900 % in Apr 2025. This records a decrease from the previous number of 4.200 % for Mar 2025. United States Unemployment Rate: Native Born data is updated monthly, averaging 5.150 % from Jan 2007 (Median) to Apr 2025, with 220 observations. The data reached an all-time high of 14.000 % in Apr 2020 and a record low of 3.100 % in Apr 2023. United States Unemployment Rate: Native Born data remains active status in CEIC and is reported by U.S. Bureau of Labor Statistics. The data is categorized under Global Database’s United States – Table US.G: Current Population Survey: Unemployment Rate.

This research paper builds on previous literature and documents general changes in the labor market for Native American women that occurred during the Great Recession using extracts of data from the Current Population Survey Annual Earnings file, known as the Merged Outgoing Rotation Groups (MORG). Wages, unemployment, and other labor market variables for Native American women are contrasted with those of Native American men and white women to determine the relative change in labor market inequality that occurred during the Great Recession.

Percentage of unemployment insurance claimants filing continued claims who are American Indian or Alaska Native.

Number of persons in the labour force (employment and unemployment) and not in the labour force, unemployment rate, participation rate and employment rate by Atlantic region, Central provinces, Western provinces, Indigenous population (First Nations or Métis) and Non-Indigenous population, sex, and age group, last 5 years.

In 2024, the estimated youth unemployment rate in India was at 16.03 percent. According to the source, the data are ILO estimates. For the past decade, India’s youth unemployment rate has been hovering around the 22 percent mark. What is the youth unemployment rate?The youth unemployment rate refers to those in the workforce who are aged 15 to 24 years and without a job, but actively seeking one. Generally, youth unemployment rates are higher than the adult unemployment rates, and India is no exception: youth unemployment in India is significantly higher than the national unemployment rate. The Indian workforce, young and oldIndia’s unemployment rate in general is not remarkably high when compared to those of other countries. Both India’s unemployment rate and youth unemployment rate are below their global equivalents. In a comparison of the Asia-Pacific region countries, India ranks somewhere in the middle, with Cambodia’s unemployment rate being estimated to be below one percent, and Afghanistan’s the highest at 8.8 percent.

Unemployment Rate in Indian River County, FL was 4.10% in January of 2024, according to the United States Federal Reserve. Historically, Unemployment Rate in Indian River County, FL reached a record high of 13.80 in January of 1992 and a record low of 3.20 in January of 2006. Trading Economics provides the current actual value, an historical data chart and related indicators for Unemployment Rate in Indian River County, FL - last updated from the United States Federal Reserve on August of 2025.

United States Unemployment Rate: Native Hawaiian or Other Pacific Islander data was reported at 4.100 % in Apr 2025. This records a decrease from the previous number of 5.400 % for Mar 2025. United States Unemployment Rate: Native Hawaiian or Other Pacific Islander data is updated monthly, averaging 5.850 % from Jan 2003 (Median) to Apr 2025, with 268 observations. The data reached an all-time high of 15.600 % in Oct 2010 and a record low of 1.100 % in Feb 2019. United States Unemployment Rate: Native Hawaiian or Other Pacific Islander data remains active status in CEIC and is reported by U.S. Bureau of Labor Statistics. The data is categorized under Global Database’s United States – Table US.G: Current Population Survey: Unemployment Rate.

Unemployment Rate (Average Indian states unemployment data from 2016 to 2019 )

United States Unemployment Rate: Native Born: Male data was reported at 4.300 % in Apr 2025. This records a decrease from the previous number of 4.600 % for Mar 2025. United States Unemployment Rate: Native Born: Male data is updated monthly, averaging 5.400 % from Jan 2007 (Median) to Apr 2025, with 220 observations. The data reached an all-time high of 12.800 % in Apr 2020 and a record low of 3.300 % in Oct 2022. United States Unemployment Rate: Native Born: Male data remains active status in CEIC and is reported by U.S. Bureau of Labor Statistics. The data is categorized under Global Database’s United States – Table US.G: Current Population Survey: Unemployment Rate.

Unemployment Rate in India decreased to 5.20 percent in July from 5.60 percent in June of 2025. This dataset provides - India Unemployment Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Although 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..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2017-2021 American Community Survey 5-Year Estimates.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Employment and unemployment estimates may vary from the official labor force data released by the Bureau of Labor Statistics because of differences in survey design and data collection. For guidance on differences in employment and unemployment estimates from different sources go to Labor Force Guidance..Workers include members of the Armed Forces and civilians who were at work last week..Industry titles and their 4-digit codes are based on the North American Industry Classification System (NAICS). The Census industry codes for 2018 and later years are based on the 2017 revision of the NAICS. To allow for the creation of multiyear tables, industry data in the multiyear files (prior to data year 2018) were recoded to the 2017 Census industry codes. We recommend using caution when comparing data coded using 2017 Census industry codes with data coded using Census industry codes prior to data year 2018. For more information on the Census industry code changes, please visit our website at https://www.census.gov/topics/employment/industry-occupation/guidance/code-lists.html..Logical coverage edits applying a rules-based assignment of Medicaid, Medicare and military health coverage were added as of 2009 -- please see https://www.census.gov/library/working-papers/2010/demo/coverage_edits_final.html for more details. Select geographies of 2008 data comparable to the 2009 and later tables are available at https://www.census.gov/data/tables/time-series/acs/1-year-re-run-health-insurance.html. The health insurance coverage category names were modified in 2010. See https://www.census.gov/topics/health/health-insurance/about/glossary.html#par_textimage_18 for a list of the insurance type definitions..Beginning in 2017, selected variable categories were updated, including age-categories, income-to-poverty ratio (IPR) categories, and the age universe for certain employment and education variables. See user note entitled "Health Insurance Table Updates" for further details..Several means of transportation to work categories were updated in 2019. For more information, see: Change to Means of Transportation..Between 2018 and 2019 the American Community Survey retirement income question changed. These changes resulted in an increase in both the number of households reporting retirement income and higher aggregate retirement income at the national level. For more information see Changes to the Retirement Income Question ..The categories for relationship to householder were revised in 2019. For more information see Revisions to the Relationship to Household item..Occupation titles and their 4-digit codes are based on the Standard Occupational Classification (SOC). The Census occupation codes for 2018 and later years are based on the 2018 revision of the SOC. To allow for the creation of the multiyear tables, occupation data in the multiyear files (prior to data year 2018) were recoded to the 2018 Census occupation codes. We recommend using caution when comparing data coded using 2018 Census occupation codes with data coded using Census occupation codes prior to data year 2018. For more information on the Census occupation code changes, please visit our website at https://www.census.gov/topics/employment /industry-occupation/guidance/code-lists.html..In 2019, methodological changes were made to the class of worker question. These changes involved modifications to the question wording, the category wording, a...

This statistic presents the results of a survey on perceived unemployment rate among working age population in India as of ************. According to data published by Ipsos, Indian respondents overestimated the level of unemployment in their country. On average, the respondents thought that around ** out of every 100 Indians of working age were unemployed and looking for work, when the actual unemployment rate was **** percent in the country.

Lotteries and Native American casinos are rapidly evolving, reflecting broader shifts in consumer behavior and digital adoption. Recent years have brought record revenues, thanks to increased discretionary spending, surging travel activity and improving unemployment rates. Yet regulatory uncertainty, cyber threats, supply chain disruptions and intense competition from online betting platforms continue challenging casinos and lotteries. Despite this, the resilience and adaptability of gaming remain evident, as both lotteries and casinos will strengthen their digital presence and modernize their offerings. Over the last few years, revenue expanded at a CAGR of 4.9% to $180.0 billion, including an uptick of 2.0% in 2025. Over the past few years, lotteries and Native American casinos have experienced modest growth. Lotteries have integrated rapidly with e-commerce and social media, meeting consumers where they spend most of their digital time and transforming ticket buying into a routine online purchase. Meanwhile, Native American casinos have capitalized on rising domestic and inbound travel, driving foot traffic and gaming revenues to new highs, with 2023 marking a record $41.9 billion in gaming revenue. Native American casinos are limited in their online expansion because of federal regulations. State lotteries remain governed by a patchwork of rules that slow the nationwide rollout of digital sales. Controversies around lottery courier services and cyberattacks on casinos highlight ongoing vulnerabilities as the industry digitizes. As state regulations catch up, the expansion of online lottery sales is expected to drive significant growth, with private lottery management firms playing an increasingly prominent role. Native American casinos will keep pushing digital innovation by investing in networked gaming, mobile apps and data-driven marketing to stay competitive while prioritizing cybersecurity in response to escalating threats. Legal battles over land eligibility and federal oversight will continue to shape the operating landscape and persistent tariff and supply chain pressures may drive further investment in tribal food production and internal supply networks. Ultimately, adaptability, digital savvy and regulatory clarity will dictate who thrives over the next few years. Revenue is anticipated to climb at a CAGR of 1.8% to reach an estimated $196.6 billion in 2030.

Overall, the unemployment rate in Indian Bay, NL is declining at a rate of 4.81% per year over the past 15 years from 2001 to 2016.

Graph and download economic data for Unemployment Rate in Indian River County, FL (FLINDI0URN) from Jan 1990 to Jun 2025 about Indian River County, FL; Sebastian; FL; unemployment; rate; and USA.

Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Data and Documentation section...Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Tell us what you think. Provide feedback to help make American Community Survey data more useful for you..Although 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..Explanation of Symbols:An ''**'' 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..An ''-'' 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..An ''-'' following a median estimate means the median falls in the lowest interval of an open-ended distribution..An ''+'' following a median estimate means the median falls in the upper interval of an open-ended distribution..An ''***'' 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..An ''*****'' entry in the margin of error column indicates that the estimate is controlled. A statistical test for sampling variability is not appropriate. .An ''N'' 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 ''(X)'' means that the estimate is not applicable or not available..Estimates of urban and rural population, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..While the 2011-2015 American Community Survey (ACS) data generally reflect the February 2013 Office of Management and Budget (OMB) definitions of metropolitan and micropolitan statistical areas; in certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB definitions due to differences in the effective dates of the geographic entities..Logical coverage edits applying a rules-based assignment of Medicaid, Medicare and military health coverage were added as of 2009 -- please see https://www.census.gov/library/working-papers/2010/demo/coverage_edits_final.html for more details. The 2008 data table in American FactFinder does not incorporate these edits. Therefore, the estimates that appear in these tables are not comparable to the estimates in the 2009 and later tables. Select geographies of 2008 data comparable to the 2009 and later tables are available at https://www.census.gov/data/tables/time-series/acs/1-year-re-run-health-insurance.html. The health insurance coverage category names were modified in 2010. See https://www.census.gov/topics/health/health-insurance/about/glossary.html#par_textimage_18 for a list of the insurance type definitions..Industry codes are 4-digit codes and are based on the North American Industry Classification System (NAICS). The Census industry codes for 2013 and later years are based on the 2012 revision of the NAICS. To allow for the creation of 2011-2015 tables, industry data in the multiyear files (2011-2015) were recoded to 2013 Census industry codes. We recommend using caution when comparing data coded using 2013 Census industry codes with data coded using Census industry codes prior to 2013. For more information on the Census industry code changes, please visit our website at https://www.census.gov/people/io/methodology/..Occupation codes are 4-digit codes and are based on Standard Occupational Classification 2010..Workers include members of the Armed Forces and civilians who were at work last week..Employment and unemployment estimates may vary from the official labor force data released by the Bureau of Labor Statistics because of differences in survey design and data collection. For guidance on differences in employment and unemployment estimates from different sources go to Labor Force Guidance..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the us...

US Census Bureau American Community Survey 2013-2017 Estimates in the Keys the Valley Region for Race/Ethnicity, Educational Attainment, Unemployment, Health Insurance, Disability and Vehicle Access.

The American Community Survey (ACS) is a nationwide survey designed to provide communities with reliable and timely social, economic, housing, and demographic data every year. Because the ACS is based on a sample, rather than all housing units and people, ACS estimates have a degree of uncertainty associated with them, called sampling error. In general, the larger the sample, the smaller the level of sampling error. Data associated with a small town will have a greater degree of error than data associated with an entire county. To help users understand the impact of sampling error on data reliability, the Census Bureau provides a “margin of error” for each published ACS estimate. The margin of error, combined with the ACS estimate, give users a range of values within which the actual “real-world” value is likely to fall.

Single-year and multiyear estimates from the ACS are all “period” estimates derived from a sample collected over a period of time, as opposed to “point-in-time” estimates such as those from past decennial censuses. For example, the 2000 Census “long form” sampled the resident U.S. population as of April 1, 2000. The estimates here were derived from a sample collected over time from 2013-2017.

Race/Ethnicity

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WPop: Total population of those who identify as white alone (B01001A).

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PWPop: Percentage of total population that identifies as white alone (B01001A).

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BPop: Total population of those who identify as black or African American alone (B01001B).

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PWPop: Percentage of total population that identifies as black or African American alone (B01001B).

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AmIPop: Total population of those who identify as American Indian and Alaska Native alone (B01001C).

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PAmIPop: Percentage of total population that identifies as American Indian and Alaska Native alone (B01001C).

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APop: Total population of those who identify as Asian alone (B01001D).

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PAPop: Percentage of total population that identifies as Asian alone (B01001D).

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PacIPop: Total population of those who identify as Native Hawaiian and Other Pacific Islander alone (B01001E).

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PPacIPop: Percentage of total population that identifies as Native Hawaiian and Other Pacific Islander alone (B01001E).

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OPop: Total population of those who identify as Some Other Race alone (B01001F).

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POPop: Percentage of total population that identifies as Some Other Race alone (B01001F).

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MPop: Total population of those who identify as Two or More Races (B01001G).

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PMPop: Percentage of total population that identifies as Two or More Races (B01001G).

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WnHPop: Total population of those who identify as White alone, not Hispanic or Latino (B01001H).

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PWnHPop: Percentage of total population that identifies as White alone, not Hispanic or Latino (B01001H).

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LPop: Total population of those who identify as Hispanic or Latino (B01001I).

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PLPop: Percentage of total population that identifies as Hispanic or Latino (B01001I).

Educational Attainment

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EdLHS1824: Total population between the ages of 18 and 24 that has not received a High School degree (S1501).

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PEdLHS1824: Percentage of population between the ages of 18 and 24 that has not received a High School degree (S1501).

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EdLHS1824: Total population between the ages of 18 and 24 that has received a High School degree or equivalent (S1501).

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PEdLHS1824: Percentage of population between the ages of 18 and 24 that has received a High School degree or equivalent (S1501).

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EdSC1824: Total population between the ages of 18 and 24 that has received some amount of college education or an associate’s degree (S1501).

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PEdSC1824: Percentage of population between the ages of 18 and 24 that has received some amount of college education or an associate’s degree (S1501).

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EdB1824: Total population between the ages of 18 and 24 that has received bachelor’s degree or higher (S1501).

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PEdB1824: Percentage of the population between the ages of 18 and 24 that has received bachelor’s degree or higher (S1501).

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EdL9: Total population ages 25 and over that has received less than a ninth grade education (S1501).

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PEdL9: Percentage of population ages 25 and over that has received less than a ninth grade education (S1501).

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Ed912nD: Total population ages 25 and over that has received some degree of education between grades 9 and 12 but has not received a high school degree (S1501).

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PEd912nD: Percentage of population ages 25 and over that has received some degree of education between grades 9 and 12 but has not received a high school degree (S1501).

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EdHS: Total population ages 25 and over that has received a high school degree or equivalent (S1501).

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PEdHS: Percentage of population ages 25 and over that has received a high school degree or equivalent (S1501).

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EdSC: Total population ages 25 and over with some college education but no degree (S1501).

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PEdSC: Percentage of population ages 25 and over with some college education but no degree (S1501).

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EdAssoc: Total population ages 25 and over with an associate’s degree (S1501).

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PEdAssoc: Percentage of population population ages 25 and over with an associate’s degree (S1501).

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EdB: Total population ages 25 and over with bachelor’s degree (S1501).

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PEdB: Percentage of population ages 25 and over with bachelor’s degree (S1501).

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EdG: Total population ages 25 and over with a graduate or professional degree (S1501).

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PEdG: Percentage of population ages 25 and over with a graduate or professional degree (S1501).

Unemployment, Health Insurance, Disability

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UnempR: Unemployment rate among the population ages 16 and over (S2301).

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UnIn: Total non-institutionalized population without health insurance (B27001).

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PUnIn: Percentage of non-institutionalized populations without health insurance (B27001).

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Disab: Total non-institutionalized population with a disability (S1810).

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PDisab: Percentage of non-institutionalized populations with a disability (B27001).

Vehicle Access

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OwnNV: Total number of owner-occupied households without a vehicle (B25044).

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POwnNV: Percentage of owner-occupied households without a vehicle (B25044).

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OwnnV: Total number of owner-occupied households with n numbers of vehicles (B25044).

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POwnnV: Percentage of owner-occupied households with n numbers of vehicles (B25044).

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RentNV: Total number of renter-occupied households without a vehicle (B25044).

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PRentNV: Percentage of renter-occupied households without a vehicle (B25044).

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RentnV: Total number of renter-occupied households with n numbers of vehicles (B25044).

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POwnnV: Percentage of renter-occupied households with n numbers of vehicles (B25044).