Chart and table of population level and growth rate for the state of New York from 1900 to 2024.

New York City Population By Community Districts The data was collected from Census Bureaus' Decennial data dissemination (SF1) for the years 1970, 1980, 1990, 2000 and 2010. Compiled by the Population Division – New York City Department of City Planning

Unadjusted decennial census data from 1950-2000 and projected figures from 2010-2040: summary table of New York City population numbers and percentage share by Borough, including school-age (5 to 17), 65 and Over, and total population.

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)

This data collection, taken from the 1980 census, contains sample data inflated to represent the total population. The entire Summary Tape File 4 (STF 4) has identical tables and format but differs in geographic coverage. Population items include age, sex, race, marital status, Spanish origin, child information, and employment information. Housing items include size and condition of the housing unit as well as information on value, age, water, sewage and heating, vehicles, and monthly owner costs. STF 4B provides summaries for the State or State equivalent; State urban/rural and standard metropolitan statistical area (SMSA) components; standard consolidated statistical areas (SCSA's) and the urban, rural, and rural farm portions of the SCSA; SMSA's and the urban, rural, and rural farm portions of the SMSA; urbanized areas (UA's); counties or county equivalents and the rural and rural farm portions of the county; minor civil divisions (MCD's) or census county divisions (CCD's), places of 2,500 or more inhabitants and the urban portion of any places that have been split into urban and rural components; American Indian reservations and their county portions; and Alaska Native villagers.

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)

About this dataset

Context

The dataset tabulates the Hadley town population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Hadley town across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2022, the population of Hadley town was 1,979, a 0.35% decrease year-by-year from 2021. Previously, in 2021, Hadley town population was 1,986, an increase of 0.30% compared to a population of 1,980 in 2020. Over the last 20 plus years, between 2000 and 2022, population of Hadley town decreased by 7. In this period, the peak population was 2,181 in the year 2009. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2022

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2022)
• Population: The population for the specific year for the Hadley town is shown in this column.
• Year on Year Change: This column displays the change in Hadley town population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Hadley town Population by Year. You can refer the same here

This data collection contains data from the "complete count" or "100-percent" questions included on the 1980 Census questionnaire. All four groups of files within the STF 1 series (1A-1D) have identical record formats and technical characteristics and differ only in the types of geographical areas for which the summarized data items are presented. Data are presented in 59 "tables" consisting of 321 cells. Population data include age, race, sex, marital status, Spanish origin, household type, and household relationship. Housing data include occupancy/vacancy status, tenure, contract rent, value, condominium status, number of rooms, and plumbing facilities. STF 1A provides summaries for state or state equivalent, county or county equivalent, minor civil division/census county division (MCD/CCD), place or place segment within MCD/CCD or remainder of MCD/CCD, census tract or block numbering area (BNA) or untracted segment within place, place segment or remainder or MCD/CCD, and block group (BG) or BG segment or enumeration district (ED).

Congressional districts of the 99th Congress are matched to census geographic areas in this file. The areas used are those from the 1980 census. Each record contains geographic data, a congressional district code, and the total 1980 population count. Ten states were redistricted for the 99th Congress: California, Hawaii, Louisiana, Maine, Mississippi, Montana, New Jersey, New York, Texas, and Washington. The data for the other 40 states and the District of Columbia are identical to that for the 98th Congress. (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/ICPSR08404.v1. We highly recommend using the ICPSR version as they may make this dataset available in multiple data formats in the future.

About this dataset

Context

The dataset tabulates the Antwerp town population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Antwerp town across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Antwerp town was 1,669, a 0.65% decrease year-by-year from 2022. Previously, in 2022, Antwerp town population was 1,680, a decline of 0.59% compared to a population of 1,690 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Antwerp town decreased by 120. In this period, the peak population was 1,980 in the year 2009. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Antwerp town is shown in this column.
• Year on Year Change: This column displays the change in Antwerp town population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Antwerp town Population by Year. You can refer the same here

About this dataset

Context

The dataset tabulates the Antwerp town population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Antwerp town across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2022, the population of Antwerp town was 1,680, a 0.77% decrease year-by-year from 2021. Previously, in 2021, Antwerp town population was 1,693, an increase of 0.77% compared to a population of 1,680 in 2020. Over the last 20 plus years, between 2000 and 2022, population of Antwerp town decreased by 109. In this period, the peak population was 1,980 in the year 2009. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2022

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2022)
• Population: The population for the specific year for the Antwerp town is shown in this column.
• Year on Year Change: This column displays the change in Antwerp town population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Antwerp town Population by Year. You can refer the same here

This file contains demographic, social, economic, and housing information from the "complete count" or "100-percent" data and sample data from the 1980 census for locally defined neighborhoods. The Neighborhood Publication Area (NPA) is the total area within which neighborhoods were defined by each participant in the Neighborhood Statistics Program (NSP), which was developed by the Census Bureau. Population items include age, race, sex, marital status, Spanish origin, household type, and household relationship. Housing items include occupancy/vacancy status, tenure, contract rent, value, condominium status, number of rooms, and plumbing facilities. Selected aggregates, means, and medians are also provided. Data are presented in 59 tables consisting of 321 cells.

Summary Tape File (STF) 1 consists of six sets of computer-readable data files containing detailed tabulations of the nation's population and housing characteristics produced from the 1980 Census. This series is comprised of STF 1A, STF 1B, STF 1C, STF 1D, STF 1E, and STF 1F. All six groups of files in the STF 1 have identical tables and formats presented in 59 tables consisting of 321 cells. The data items contained in the STF 1 files were also tabulated from the complete count or "100-percent" questions included on the 1980 Census. The data files differ only in geographic coverage. STF 1F, the School Districts file, is a special tabulation that provides summary level data for school districts by state (summary level 40) including the District of Columbia, and by county or county equivalent (summary level 41). Population items tabulated include age, race (provisional data), sex, marital status, Spanish origin (provisional data), household type, and household relationship. Housing items tabulated include occupancy/vacancy status, tenure, contract rent, value, condominium status, number of rooms, and plumbing facilities. Selected aggregates, means, and medians are also provided. (Source: ICPSR, accessed on 06/14/2011)

About this dataset

Context

The dataset tabulates the Prattsburgh town population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Prattsburgh town across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2022, the population of Prattsburgh town was 1,970, a 0.00% decrease year-by-year from 2021. Previously, in 2021, Prattsburgh town population was 1,970, a decline of 0.51% compared to a population of 1,980 in 2020. Over the last 20 plus years, between 2000 and 2022, population of Prattsburgh town decreased by 123. In this period, the peak population was 2,150 in the year 2005. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2022

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2022)
• Population: The population for the specific year for the Prattsburgh town is shown in this column.
• Year on Year Change: This column displays the change in Prattsburgh town population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Prattsburgh town Population by Year. You can refer the same here

This is a hybrid gridded dataset of demographic data for the world, given as 5-year population bands at a 0.5 degree grid resolution. This dataset combines the NASA SEDAC Gridded Population of the World version 4 (GPWv4) with the ISIMIP Histsoc gridded population data and the United Nations World Population Program (WPP) demographic modelling data. Demographic fractions are given for the time period covered by the UN WPP model (1950-2050) while demographic totals are given for the time period covered by the combination of GPWv4 and Histsoc (1950-2020) Method - demographic fractions Demographic breakdown of country population by grid cell is calculated by combining the GPWv4 demographic data given for 2010 with the yearly country breakdowns from the UN WPP. This combines the spatial distribution of demographics from GPWv4 with the temporal trends from the UN WPP. This makes it possible to calculate exposure trends from 1980 to the present day. To combine the UN WPP demographics with the GPWv4 demographics, we calculate for each country the proportional change in fraction of demographic in each age band relative to 2010 as: (\delta_{year,\ country,age}^{\text{wpp}} = f_{year,\ country,age}^{\text{wpp}}/f_{2010,country,age}^{\text{wpp}}) Where: - (\delta_{year,\ country,age}^{\text{wpp}}) is the ratio of change in demographic for a given age and and country from the UN WPP dataset. - (f_{year,\ country,age}^{\text{wpp}}) is the fraction of population in the UN WPP dataset for a given age band, country, and year. - (f_{2010,country,age}^{\text{wpp}}) is the fraction of population in the UN WPP dataset for a given age band, country for the year 2020. The gridded demographic fraction is then calculated relative to the 2010 demographic data given by GPWv4. For each subset of cells corresponding to a given country c, the fraction of population in a given age band is calculated as: (f_{year,c,age}^{\text{gpw}} = \delta_{year,\ country,age}^{\text{wpp}}*f_{2010,c,\text{age}}^{\text{gpw}}) Where: - (f_{year,c,age}^{\text{gpw}}) is the fraction of the population in a given age band for given year, for the grid cell c. - (f_{2010,c,age}^{\text{gpw}}) is the fraction of the population in a given age band for 2010, for the grid cell c. The matching between grid cells and country codes is performed using the GPWv4 gridded country code lookup data and country name lookup table. The final dataset is assembled by combining the cells from all countries into a single gridded time series. This time series covers the whole period from 1950-2050, corresponding to the data available in the UN WPP model. Method - demographic totals Total population data from 1950 to 1999 is drawn from ISIMIP Histsoc, while data from 2000-2020 is drawn from GPWv4. These two gridded time series are simply joined at the cut-over date to give a single dataset covering 1950-2020. The total population per age band per cell is calculated by multiplying the population fractions by the population totals per grid cell. Note that as the total population data only covers until 2020, the time span covered by the demographic population totals data is 1950-2020 (not 1950-2050). Disclaimer This dataset is a hybrid of different datasets with independent methodologies. No guarantees are made about the spatial or temporal consistency across dataset boundaries. The dataset may contain outlier points (e.g single cells with demographic fractions >1). This dataset is produced on a 'best effort' basis and has been found to be broadly consistent with other approaches, but may contain inconsistencies which not been identified. {"references": ["UN. (2019). World Population Prospects 2019: Data Booklet. Retrieved from https://population.un.org/wpp/Publications/Files/WPP2019_DataBooklet.pdf", "NASA SEDAC, & CIESIN. (2016). Gridded Population of the World, Version 4 (GPWv4): Population Count. New York, New York, USA: Columbia University. Retrieved from http://dx.doi.org/10.7927/H4X63JVC", "ISIMIP. (2018). ISIMIP Project Design and Simulation Protocol. Retrieved from https://www.isimip.org/gettingstarted/input-data-bias-correction/details/31/"]}

Functioning general-purpose governmental units were the focus of this dataset. This aggregate data collection includes the name of each governmental unit, per capita income in 1979, total population as of April 1, 1980, per capita income estimates for 1981, and July 1, 1982, population estimates. Information is included for all counties, incorporated places, and functioning minor civil divisions (MCDs) in Connecticut, Illinois, Indiana, Kansas, Maine, Massachusetts, Michigan, Minnesota, Missouri, Nebraska, New Hampshire, New Jersey, New York, North Dakota, Ohio, Pennsylvania, Rhode Island, South Dakota, Vermont, and Wisconsin.

Functioning general-purpose governmental units were the focus of this dataset. This aggregate data collection includes the name of each governmental unit, per capita income in 1979, total population as of April 1, 1980, per capita income estimates for 1981, and July 1, 1982, population estimates. Information is included for all counties, incorporated places, and functioning minor civil divisions (MCDs) in Connecticut, Illinois, Indiana, Kansas, Maine, Massachusetts, Michigan, Minnesota, Missouri, Nebraska, New Hampshire, New Jersey, New York, North Dakota, Ohio, Pennsylvania, Rhode Island, South Dakota, Vermont, and Wisconsin. (Source: ICPSR, retrieved 06/28/2011)

The Public Use Microdata Samples (PUMS) contain person- and household-level information from the "long-form" questionnaires distributed to a sample of the population enumerated in the 1980 Census. The A Sample identifies every state, county groups, and most individual counties with 100,000 or more inhabitants (350 in all). In many cases, individual cities or groups of places with 100,000 or more inhabitants are also identified. As a percentage of the 5-Percent Public Use Microdata Sample (A Sample) [CENSUS OF POPULATION AND HOUSING, 1980 [UNITED STATES]: PUBLIC USE MICRODATA SAMPLE (A SAMPLE): 5-PERCENT SAMPLE (ICPSR 8101)], this file constitutes a 1-in-1000 sample, and contains all household- and person-level variables from the original A Sample. Household-level variables include housing tenure, year structure was built, number and types of rooms in dwelling, plumbing facilities, heating equipment, taxes and mortgage costs, number of children, and household and family income. Person-level variables include sex, age, marital status, race, Spanish origin, income, occupation, transportation to work, and education. (Source: retrieved from ICPSR 06/15/2011)

Public Law 94-171, enacted in 1975, directs the United States Census Bureau to make special preparations to provide redistricting data needed by the 50 states. It specifies that within one year following the Census Day (i.e., for Census 2000 by April 1, 2001), the Census Bureau must send the governor and legislature in each state the data they need to redraw districts for the United States Congress and state legislatures. This file contains a count of the total population, as well as provisional figures for five racial categories (White; Black; American Indian, Eskimo, and Aleut; Asian and Pacific Islander; and Other) and for persons of Spanish/Hispanic origin. The file provides summaries for the State, counties, minor civil districts (MCD's) or census county divisions (CCD's), incorporated places or place segments within MCD's/CCD's and remainders of MCD's/CCD's, election precincts in certain States or portions of certain States, census tracts or block numbering areas, block groups and blocks, or enumeration districts in unblocked areas.

About 50.4 percent of the household income of private households in the U.S. were earned by the highest quintile in 2023, which are the upper 20 percent of the workers. In contrast to that, in the same year, only 3.5 percent of the household income was earned by the lowest quintile. This relation between the quintiles is indicative of the level of income inequality in the United States. Income inequalityIncome inequality is a big topic for public discussion in the United States. About 65 percent of U.S. Americans think that the gap between the rich and the poor has gotten larger in the past ten years. This impression is backed up by U.S. census data showing that the Gini-coefficient for income distribution in the United States has been increasing constantly over the past decades for individuals and households. The Gini coefficient for individual earnings of full-time, year round workers has increased between 1990 and 2020 from 0.36 to 0.42, for example. This indicates an increase in concentration of income. In general, the Gini coefficient is calculated by looking at average income rates. A score of zero would reflect perfect income equality and a score of one indicates a society where one person would have all the money and all other people have nothing. Income distribution is also affected by region. The state of New York had the widest gap between rich and poor people in the United States, with a Gini coefficient of 0.51, as of 2019. In global comparison, South Africa led the ranking of the 20 countries with the biggest inequality in income distribution in 2018. South Africa had a score of 63 points, based on the Gini coefficient. On the other hand, the Gini coefficient stood at 16.6 in Azerbaijan, indicating that income is widely spread among the population and not concentrated on a few rich individuals or families. Slovenia led the ranking of the 20 countries with the greatest income distribution equality in 2018.