Summary File 1 contains 100-percent United States decennial Census data, which is the information compiled from the questions asked of all people and about every housing unit. Population items include sex, age, race, Hispanic or Latino origin, household relationship, and group quarters occupancy. Housing items include occupancy status, vacancy status, and tenure (owner occupied or renter occupied). There are a total of 171 population tables ("P") and 56 housing tables ("H") provided down to the block level, and 59 population tables provided down to the census tract level ("PCT") for a total of 286 tables. In addition, 14 population tables and 4 housing tables at the block level and 4 population tables at the census tract level are repeated by major race and Hispanic or Latino groups. The data present population and housing characteristics for the total population, population totals for an extensive list of race (American Indian and Alaska Native tribes, Asian, Native Hawaiian, and Other Pacific Islander) and Hispanic or Latino groups, and population and housing characteristics for a limited list of race and Hispanic or Latino groups. Population and housing items may be crosstabulated. Selected aggregates and medians also are provided. Summary File 1 is released in the form of individual files for each of the 50 states, the District of Columbia, and Puerto Rico. (Source: downloaded from ICPSR 7/13/10)

Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR at https://doi.org/10.3886/ICPSR03194.v2. We highly recommend using the ICPSR version as they may make this dataset available in multiple data formats in the future.

Summary File 2 contains 100-percent United States decennial Census data, which is the information compiled from the questions asked of all people and about every housing unit. Population items include sex, age, race, Hispanic or Latino origin, household relationship, and group quarters occupancy. Housing items include occupancy status, vacancy status, and tenure (owner-occupied or renter- occupied). The 100-percent data are presented in 36 population tables ("PCT") and 11 housing tables ("HCT") down to the census tract level. Each table is iterated for 250 population groups: the total population, 132 race groups, 78 American Indian and Alaska Native tribe categories (reflecting 39 individual tribes), and 39 Hispanic or Latino groups. The presentation of tables for any of the 250 population groups is subject to a population threshold of 100 or more people, that is, if there were fewer than 100 people in a specific population group in a specific geographic area, their population and housing characteristics data are not available for that geographic area. (Source: downloaded from ICPSR 7/13/10)

Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR at https://doi.org/10.3886/ICPSR13265.v2. We highly recommend using the ICPSR version as they may make this dataset available in multiple data formats in the future.

How does your organization use this dataset? What other NYSERDA or energy-related datasets would you like to see on Open NY? Let us know by emailing OpenNY@nyserda.ny.gov. The Low- to Moderate-Income (LMI) New York State (NYS) Census Population Analysis dataset is resultant from the LMI market database designed by APPRISE as part of the NYSERDA LMI Market Characterization Study (https://www.nyserda.ny.gov/lmi-tool). All data are derived from the U.S. Census Bureau’s American Community Survey (ACS) 1-year Public Use Microdata Sample (PUMS) files for 2013, 2014, and 2015. Each row in the LMI dataset is an individual record for a household that responded to the survey and each column is a variable of interest for analyzing the low- to moderate-income population. The LMI dataset includes: county/county group, households with elderly, households with children, economic development region, income groups, percent of poverty level, low- to moderate-income groups, household type, non-elderly disabled indicator, race/ethnicity, linguistic isolation, housing unit type, owner-renter status, main heating fuel type, home energy payment method, housing vintage, LMI study region, LMI population segment, mortgage indicator, time in home, head of household education level, head of household age, and household weight. The LMI NYS Census Population Analysis dataset is intended for users who want to explore the underlying data that supports the LMI Analysis Tool. The majority of those interested in LMI statistics and generating custom charts should use the interactive LMI Analysis Tool at https://www.nyserda.ny.gov/lmi-tool. This underlying LMI dataset is intended for users with experience working with survey data files and producing weighted survey estimates using statistical software packages (such as SAS, SPSS, or Stata).

Summary File 3 contains sample data, which is the information compiled from the questions asked of a sample of all people and housing units in the United States. Population items include basic population totals as well as counts for the following characteristics: urban and rural, households and families, marital status, grandparents as caregivers, language and ability to speak English, ancestry, place of birth, citizenship status, year of entry, migration, place of work, journey to work (commuting), school enrollment and educational attainment, veteran status, disability, employment status, industry, occupation, class of worker, income, and poverty status. Housing items include basic housing totals and counts for urban and rural, number of rooms, number of bedrooms, year moved into unit, household size and occupants per room, units in structure, year structure built, heating fuel, telephone service, plumbing and kitchen facilities, vehicles available, value of home, and monthly rent and shelter costs. The Summary File 3 population tables are identified with a "P" prefix and the housing tables are identified with an "H," followed by a sequential number. The "P" and "H" tables are shown for the block group and higher level geography, while the "PCT" and "HCT" tables are shown for the census tract and higher level geography. There are 16 "P" tables, 15 "PCT" tables, and 20 "HCT" tables that bear an alphabetic suffix on the table number, indicating that they are repeated for nine major race and Hispanic or Latino groups. There are 484 population tables and 329 housing tables for a total of 813 unique tables. (Source: ICPSR, retrieved 06/15/2011)

Selected demographic, social, economic, and housing estimates data by community district/PUMA (Public Use Micro Data Sample Area). Three year estimates of population data from the Census Bureau's American Community Survey

Summary File 4 (SF 4) from the United States 2000 Census contains the sample data, which is the information compiled from the questions asked of a sample of all people and housing units. Population items include basic population totals: urban and rural, households and families, marital status, grandparents as caregivers, language and ability to speak English, ancestry, place of birth, citizenship status, year of entry, migration, place of work, journey to work (commuting), school enrollment and educational attainment, veteran status, disability, employment status, industry, occupation, class of worker, income, and poverty status. Housing items include basic housing totals: urban and rural, number of rooms, number of bedrooms, year moved into unit, household size and occupants per room, units in structure, year structure built, heating fuel, telephone service, plumbing and kitchen facilities, vehicles available, value of home, monthly rent, and shelter costs. In Summary File 4, the sample data are presented in 213 population tables (matrices) and 110 housing tables, identified with "PCT" and "HCT" respectively. Each table is iterated for 336 population groups: the total population, 132 race groups, 78 American Indian and Alaska Native tribe categories (reflecting 39 individual tribes), 39 Hispanic or Latino groups, and 86 ancestry groups. The presentation of SF4 tables for any of the 336 population groups is subject to a population threshold. That is, if there are fewer than 100 people (100-percent count) in a specific population group in a specific geographic area, and there are fewer than 50 unweighted cases, their population and housing characteristics data are not available for that geographic area in SF4. For the ancestry iterations, only the 50 unweighted cases test can be performed. See Appendix H: Characteristic Iterations, for a complete list of characteristic iterations.

Summary Tape File 2 (STF 2) files contain detailed complete-count tabulations for all persons and housing units in the United States. The STF 2B files provide summaries for states or state equivalents, state components, standard consolidated statistical areas (SCSAs) and the urban and rural portions of the SCSAs, standard metropolitan statistical areas (SMSAs) and the urban and rural portions of the SMSAs, urbanized areas, counties or county equivalents and the rural portion of the counties, minor civil divisions or Census county divisions, places of 1,000 people or more and the urban portions of any places that have been split into urban and rural components, American Indian reservations and their county portions, and Alaska Native villages. Population (or demographic) and housing items are contained in each type of file. The data are presented in two types of records. The first, record A, is presented once for each geographic area and summarizes total population and all housing units. The second, record B, is presented for the total population in each area and repeated for each race and Hispanic group in the area that meets nonsuppression criteria. Record B is presented for a maximum of 26 racial/Hispanic groups. If too few persons or housing units fall into an ethnic category in a census area, the data for that category are suppressed. (Source: ICPSR, accessed 06/14/2011)

The objective of this data collection was to examine inequalities of wealth and the geographic distribution of wealthy individuals in late 18th- and early 19th-century New York and to investigate wealth in relationship to occupation and location. For this study, the entire set of tax assessment records and United States Census records for New York City were computerized and occupational status was added for all entries. The collection addresses topics such as social class structure, demographic factors, occupational status and geographic distribution, property values and geographic distribution, and the relationship of these factors to the political system. Units of analysis were individual property owners and renters for the tax assessment data and heads of households for the census data. Data collected included the individual's name, address, occupation, sex, and race, the type, quantity, and value of real and personal property, and the type and occupancy of the structure at the address. Occupational data from city directories were used to supplement the tax and census data.

Graph and download economic data for Homeownership Rate (5-year estimate) for Monroe County, NY (HOWNRATEACS036055) from 2009 to 2023 about Monroe County, NY; Rochester; homeownership; NY; housing; 5-year; rate; and USA.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units and the group quarters population for states and counties..Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.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, 2019-2023 American Community Survey 5-Year Estimates.ACS data generally reflect the geographic boundaries of legal and statistical areas as of January 1 of the estimate year. For more information, see Geography Boundaries by Year..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..Users must consider potential differences in geographic boundaries, questionnaire content or coding, or other methodological issues when comparing ACS data from different years. Statistically significant differences shown in ACS Comparison Profiles, or in data users' own analysis, may be the result of these differences and thus might not necessarily reflect changes to the social, economic, housing, or demographic characteristics being compared. For more information, see Comparing ACS Data..The Hispanic origin and race codes were updated in 2020. For more information on the Hispanic origin and race code changes, please visit the American Community Survey Technical Documentation website..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

Four tables of ACS demographic profiles for 2012 to 2016 at the New York City and Borough level. Four profiles include demographics,economic, housing and sociological.

Four tables of ACS demographic profiles for 2012 to 2016 at the NTA level. Four profiles include demographics, economic, housing and sociological. Column headers in this database are abbreviated. Please see the data dictionary (shown in worksheet entitled “Dictionary”) for an explanation of these abbreviated headers.

All previously released versions of this data are available at BYTES of the BIG APPLE- Archive

In 2023, New York led all states in the United States with the highest population residing in public housing units. The number of residents in assisted houses in New York was more than *******, much higher than in other states. Other states with a high number of residents in government-aided accommodations included Pennsylvania and Puerto Rico, with both states having around 100,000 public housing residents. In contrast, Vermont recorded the lowest number of residents in public housing units, at just ***. North Dakota, Wyoming, and Idaho were also some of the states that had comparatively low populations, each reporting fewer than ***** people.

This data collection provides detailed tabulations of 100-percent data items from the 1990 Census of Population and Housing. These tabulations are presented for states and their subareas in hierarchical sequence down to the census tract or block numbering area (BNA) level. Population items include age, race, sex, marital status, Hispanic origin, household type, and household relationship. Population items for Puerto Rico include persons, families, households, sex, age, marital status, household size, and household type. Housing items include occupancy/vacancy status, tenure, units in structure, contract rent, meals included in rent, value, and number of rooms in housing unit. Crosstabulations include variables such as single year of age by sex, tenure by age of householder, age by group quarters, aggregate value by units in structure, and tenure by number of nonrelatives. The dataset contains both "A" and "B" records. "A" records are provided for each summary level in a geographic area, and are repeated for each geographic component. "B" records repeat the same data for each summary level/geographic component combination, but are tabulated for each of ten categories of race and Hispanic origin. (Source: ICPSR, retrieved 06/15/2011)

This file is an extract of Summary Tape File 1A from the 1980 Census. It contains numeric codes and names of geographic areas plus selected complete-count population, provisional population counts by race and Hispanic origin, the number of families, and the number of persons in group quarters. Also included are the number of one-person households, the total number of housing units, the number of occupied housing units, and the number of owner-occupied housing units. There are 51 files, one for each state and the District of Columbia. The format for each of the files is identical. The number of records varies by state. (Source: retrieved from ICPSR 06/15/2011)

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units and the group quarters population for states and counties..Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.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, 2023 American Community Survey 1-Year Estimates.ACS data generally reflect the geographic boundaries of legal and statistical areas as of January 1 of the estimate year. For more information, see Geography Boundaries by Year..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..Users must consider potential differences in geographic boundaries, questionnaire content or coding, or other methodological issues when comparing ACS data from different years. Statistically significant differences shown in ACS Comparison Profiles, or in data users' own analysis, may be the result of these differences and thus might not necessarily reflect changes to the social, economic, housing, or demographic characteristics being compared. For more information, see Comparing ACS Data..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

U.S. Census Bureau QuickFacts statistics for Seaford CDP, New York. QuickFacts data are derived from: Population Estimates, American Community Survey, Census of Population and Housing, Current Population Survey, Small Area Health Insurance Estimates, Small Area Income and Poverty Estimates, State and County Housing Unit Estimates, County Business Patterns, Nonemployer Statistics, Economic Census, Survey of Business Owners, Building Permits.

Demographic and income disparities may impact food accessibility. Research has not yet well documented the precise location of healthy and unhealthy food resources around children’s homes and schools. The objective of this study was to examine the food environment around homes and schools for all public school children, stratified by race/ethnicity and poverty status. This cross-sectional study linked data on the exact home and school addresses of a population-based sample of public school children in New York City from 2013 to all corner stores, supermarkets, fast-food restaurants, and wait-service restaurants. Two measures were created around these addresses for all children: 1) distance to the nearest outlet, and 2) count of outlets within 0.25 miles. The total analytic sample included 789,520 K-12 graders. The average age was 11.78 years (SD ± 4.0 years). Black, Hispanic, and Asian students live and attend schools closer to nearly all food outlet types than White students, regardless of poverty status. Among not low-income students, Black, Hispanic, and Asian students were closer from home and school to corner stores and supermarkets, and had more supermarkets around school than White students. The context in which children live matters, and more nuanced data is important for development of appropriate solutions for childhood obesity. Future research should examine disparities in the food environment in other geographies and by other demographic characteristics, and then link these differences to health outcomes like body mass index. These findings can be used to better understand disparities in food access and to help design policies intended to promote healthy eating among children.

This poll, fielded June 21-26, 2005, is part of a continuing series of monthly surveys that solicit public opinion on the current presidency and on a range of other political and social issues. The focus of this survey was the 2005 New York City mayoral race. Residents of the city were asked to give their opinions of the candidates running for mayor and how those candidates would deal with various issues. Their opinions were also sought about the New York City school system. The candidates mentioned in the survey included current Mayor Michael Bloomberg, Fernando Ferrer, Virginia Fields, Gifford Miller, Thomas Ognibene, and Anthony Weiner. A series of questions asked the respondents to give their opinion on the subject of the rebuilding of the World Trade Center site, whether they felt that current Mayor Bloomberg was doing a good job or not and if he was spending too much or too little effort on this issue. Respondents were also asked to rate the New York City economy and if they thought it was getting better or worse. Questions respondents were asked concerning New York City schools included if they were satisfied with the public school system and the schools located in their neighborhood, what type of school the respondents' children attended, and their opinion about the way Joe Klein was handling his job as the New York City School Chancellor. Respondents were asked to compare neighborhood safety at the time of the survey to that of four years previously, what their opinion was on the prospect of building new stadiums in the New York City area, and if they thought that a new stadium would help the city win its bid for the 2012 Olympics. Other general topics included quality of life in New York City, city services, the economy, crime, taxes, the transit system, and housing. Demographic variables include age, sex, race, household income, education level, political party affiliation, political philosophy, religious affiliation, marital status, borough of residence, and likely mayoral vote.

This poll, the first of two fielded April 2012, is a part of a continuing series of monthly surveys that solicits public opinion on a range of political and social issues. Respondents were asked how well Barack Obama was handling the presidency, terrorism, the economy, the war in Afghanistan, the housing market, and the issue of gasoline prices. Opinions were collected on whether respondents thought the country was headed in the right direction, the most important problem facing the nation, whether Congress was performing their job well, and the national economy. Respondents were also queried on their opinions of Barack Obama and Mitt Romney, as well as whether either of the two presidential candidates would be able to bring real change to Washington, whether they would be able to make the right decisions on various issues, and whether they would be an effective military leader. Additional topics included economic concerns, the suspension of Rick Santorum's presidential campaign, women's health issues, the future of the next generation of Americans, gasoline prices, the home mortgage crisis, federal income tax policies and the capital gains tax policy, the John Edwards trial, and the college education of the respondent's child. Finally, respondents were asked whether they voted in the 2008 presidential election and who they voted for, whether they supported the Tea Party movement, whether they usually vote Democratic or Republican, whether they planned to vote in a 2012 primary or caucus, how much attention they have paid to the 2012 presidential campaign, and whether they were registered to vote. Demographic information includes sex, age, race, social class, marital status, household makeup, education level, household income, employment status, religious preference, type of residential area (e.g., urban or rural), political party affiliation, political philosophy, and whether respondents thought of themselves as born-again Christians.