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.

Citywide street tree data from the 2005 Street Tree Census, conducted partly by volunteers organized by NYC Parks & Recreation. Trees were inventoried by address, and were collected from 2005-2006. Data collected includes tree species, diameter, condition.

About this dataset

Context

The dataset tabulates the New York population by gender and age. The dataset can be utilized to understand the gender distribution and demographics of New York.

Content

The dataset constitues the following two datasets across these two themes

• New York, NY Population Breakdown by Gender
• New York, NY Population Breakdown by Gender and Age

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/.

New York City’s tree inventory includes 592,130 publicly managed street trees. This represents 584,036 live trees and 8,036 standing dead trees tallied over the course of two summer inventory periods. The inventory contains 168 tree species with London planetree (Platanus acerifolia), Norway maple (Acer platanoides), callery pear (Pyrus calleryana), honeylocust (Gleditsia triacanthos) and pin oak (Quercus palustris) as the predominant species. 2015 Street Tree Census, conducted by volunteers and staff organized by NYC Parks & Recreation and partner organizations. Tree data collected includes tree species, diameter and perception of health. Ref: https://data.cityofnewyork.us/Environment/2015-Street-Tree-Census-Tree-Data/uvpi-gqnh/data See also: https://www.nycgovparks.org/trees/treescount

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. The Address Ranges Feature Shapefile (ADDRFEAT.dbf) contains the geospatial edge geometry and attributes of all unsuppressed address ranges for a county or county equivalent area. The term "address range" refers to the collection of all possible structure numbers from the first structure number to the last structure number and all numbers of a specified parity in between along an edge side relative to the direction in which the edge is coded. Single-address address ranges have been suppressed to maintain the confidentiality of the addresses they describe. Multiple coincident address range feature edge records are represented in the shapefile if more than one left or right address ranges are associated to the edge. The ADDRFEAT shapefile contains a record for each address range to street name combination. Address range associated to more than one street name are also represented by multiple coincident address range feature edge records. Note that the ADDRFEAT shapefile includes all unsuppressed address ranges compared to the All Lines Shapefile (EDGES.shp) which only includes the most inclusive address range associated with each side of a street edge. The TIGER/Line shapefile contain potential address ranges, not individual addresses. The address ranges in the TIGER/Line Files are potential ranges that include the full range of possible structure numbers even though the actual structures may not exist.

Context

There are a number of Kaggle datasets that provide spatial data around New York City. For many of these, it may be quite interesting to relate the data to the demographic and economic characteristics of nearby neighborhoods. I hope this data set will allow for making these comparisons without too much difficulty.

Exploring the data and making maps could be quite interesting as well.

Content

This dataset contains two CSV files:

1. nyc_census_tracts.csv

   This file contains a selection of census data taken from the ACS DP03 and DP05 tables. Things like total population, racial/ethnic demographic information, employment and commuting characteristics, and more are contained here. There is a great deal of additional data in the raw tables retrieved from the US Census Bureau website, so I could easily add more fields if there is enough interest.

   I obtained data for individual census tracts, which typically contain several thousand residents.

2. census_block_loc.csv

   For this file, I used an online FCC census block lookup tool to retrieve the census block code for a 200 x 200 grid containing New York City and a bit of the surrounding area. This file contains the coordinates and associated census block codes along
   with the state and county names to make things a bit more readable to users.

   Each census tract is split into a number of blocks, so one must extract the census tract code from the block code.

Acknowledgements

The data here was taken from the American Community Survey 2015 5-year estimates (https://factfinder.census.gov/faces/nav/jsf/pages/index.xhtml).

The census block coordinate data was taken from the FCC Census Block Conversions API (https://www.fcc.gov/general/census-block-conversions-api)

As public data from the US government, this is not subject to copyright within the US and should be considered public domain.

Census Tracts from the 2020 US Census for New York City clipped to the shoreline. These boundary files are derived from the US Census Bureau's TIGER project and have been geographically modified to fit the New York City base map. Because some census tracts are under water not all census tracts are contained in this file, only census tracts that are partially or totally located on land have been mapped in this file.

All previously released versions of this data are available at the DCP Website: BYTES of the BIG APPLE.

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. The Address Ranges Feature Shapefile (ADDRFEAT.dbf) contains the geospatial edge geometry and attributes of all unsuppressed address ranges for a county or county equivalent area. The term "address range" refers to the collection of all possible structure numbers from the first structure number to the last structure number and all numbers of a specified parity in between along an edge side relative to the direction in which the edge is coded. Single-address address ranges have been suppressed to maintain the confidentiality of the addresses they describe. Multiple coincident address range feature edge records are represented in the shapefile if more than one left or right address ranges are associated to the edge. The ADDRFEAT shapefile contains a record for each address range to street name combination. Address range associated to more than one street name are also represented by multiple coincident address range feature edge records. Note that the ADDRFEAT shapefile includes all unsuppressed address ranges compared to the All Lines Shapefile (EDGES.shp) which only includes the most inclusive address range associated with each side of a street edge. The TIGER/Line shapefile contain potential address ranges, not individual addresses. The address ranges in the TIGER/Line Files are potential ranges that include the full range of possible structure numbers even though the actual structures may not exist.

About this dataset

Context

The dataset tabulates the New Albion 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 New Albion 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 New Albion town was 1,940, a 0.67% decrease year-by-year from 2022. Previously, in 2022, New Albion town population was 1,953, a decline of 0.71% compared to a population of 1,967 in 2021. Over the last 20 plus years, between 2000 and 2023, population of New Albion town decreased by 130. In this period, the peak population was 2,070 in the year 2000. 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 New Albion town is shown in this column.
• Year on Year Change: This column displays the change in New Albion 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 New Albion town Population by Year. You can refer the same here

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. The Address Ranges Feature Shapefile (ADDRFEAT.dbf) contains the geospatial edge geometry and attributes of all unsuppressed address ranges for a county or county equivalent area. The term "address range" refers to the collection of all possible structure numbers from the first structure number to the last structure number and all numbers of a specified parity in between along an edge side relative to the direction in which the edge is coded. Single-address address ranges have been suppressed to maintain the confidentiality of the addresses they describe. Multiple coincident address range feature edge records are represented in the shapefile if more than one left or right address ranges are associated to the edge. The ADDRFEAT shapefile contains a record for each address range to street name combination. Address range associated to more than one street name are also represented by multiple coincident address range feature edge records. Note that the ADDRFEAT shapefile includes all unsuppressed address ranges compared to the All Lines Shapefile (EDGES.shp) which only includes the most inclusive address range associated with each side of a street edge. The TIGER/Line shapefile contain potential address ranges, not individual addresses. The address ranges in the TIGER/Line Files are potential ranges that include the full range of possible structure numbers even though the actual structures may not exist.

This data collection constitutes a portion of the historical data collected by the project "Early Indicators of Later Work Levels, Disease, and Death." With the goal of constructing datasets suitable for longitudinal analyses of factors affecting the aging process, the project is collecting military, medical, and socioeconomical data on a sample of white males mustered into the Union Army during the Civil War. The project seeks to examine the influence of environmental and host factors prior to recruitment on the health performance and survival of recruits during military service, to identify and show relationships between socioeconomic and biomedical conditions (including nutritional status) of veterans at early ages and mortality rates from diseases at middle and late ages, and to study the effects of health and pensions on labor force participation rates of veterans at ages 65 and over. This installment of the collection, Version C-3, supersedes all previous collections (Versions C-1 and C-2), and contains data from the censuses of 1850, 1860, 1900, and 1910 on veterans who were originally mustered into the Union Army in Connecticut, Delaware, District of Columbia, Illinois, Iowa, Kansas, Kentucky, Maine, Maryland, Massachusetts, Michigan, Minnesota, Missouri, New Hampshire, New Jersey, New York, Ohio, Pennsylvania, Vermont, and West Virginia. This version of the collection also contains observations from Wisconsin, Indiana, California, and New Mexico. Census Data, Part 1, includes place of residence, relationship to head of household, date and place of birth, number of children, education, disability status, employment status, number of years in the United States, literacy, marital status, occupation, parents' birthplace, and property/home ownership. The variables in Part 2, Linkage Data, indicate which document sources were located for each recruit.

In 1995, hundreds of volunteers joined the New York City (NYC) Department of Parks & Recreation staff to inventory the city's street tree population. These inventory efforts resulted in an unprecedented understanding of NYC’s urban forest, and catalyzed major advances in its urban forest management.

See: https://www.nycgovparks.org/trees/treescount/past-censuses and: https://data.cityofnewyork.us/Environment/1995-Street-Tree-Census/7gmq-dbas

Graph and download economic data for Resident Population in Jefferson County, NY (NYJEFF0POP) from 1970 to 2024 about Jefferson County, NY; NY; residents; population; and USA.

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. The Address Ranges Feature Shapefile (ADDRFEAT.dbf) contains the geospatial edge geometry and attributes of all unsuppressed address ranges for a county or county equivalent area. The term "address range" refers to the collection of all possible structure numbers from the first structure number to the last structure number and all numbers of a specified parity in between along an edge side relative to the direction in which the edge is coded. Single-address address ranges have been suppressed to maintain the confidentiality of the addresses they describe. Multiple coincident address range feature edge records are represented in the shapefile if more than one left or right address ranges are associated to the edge. The ADDRFEAT shapefile contains a record for each address range to street name combination. Address range associated to more than one street name are also represented by multiple coincident address range feature edge records. Note that the ADDRFEAT shapefile includes all unsuppressed address ranges compared to the All Lines Shapefile (EDGES.shp) which only includes the most inclusive address range associated with each side of a street edge. The TIGER/Line shapefile contain potential address ranges, not individual addresses. The address ranges in the TIGER/Line Files are potential ranges that include the full range of possible structure numbers even though the actual structures may not exist.

Summary Tape File 4B contains sample data weighted to represent the total United States population. The collection also contains 100-percent counts and unweighted sample counts for total persons and total housing units. Additional population and housing variables include items such as age, ancestry, disability, citizenship, education, income, marital status, race, sex, travel time to work, hours worked, rent, persons in household, acreage of property, tenure, value of housing unit, number of vehicles, and monthly owner costs. Data are provided for states (and the District of Columbia) and their county subareas. Within STF 4B, data for each state are represented in one "A" record file and 49 "B" record files. The "A" records contain 123 population tables and 80 housing tables. These include five population tables and one housing table showing 37 categories of race and five population tables and one housing table with 26 categories of Hispanic origin. Data are included for all persons for each summary level and geographic component level within a unit of geography. More detailed data are presented in 178 population and 85 housing tables in the "B" records. The "B" records include a separate file for all persons and up to 48 separate race and Hispanic-origin files. (Source: ICPSR, retrieved 06/15/2011)

Table of Census Demographics represented at the NTA level. NTAs are aggregations of census tracts that are subsets of New York City's 55 Public Use Micro data Areas (PUMAs)

The annual gentrification map for NYC was produced using the classification method proposed in this experiment to highlight the spatial and temporal distribution of gentrification. The time-series gentrification maps illustrate areas experienced gentrification since 2000. The data was aggregated to Census tract level for displaying a visually friendly result. The raw building level data is also provided but not presented in the paper since it is not readable using the static map.

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 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 map contains NYC administrative boundaries enriched with various demographics datasets.Learn more about Esri's Enrich Layer / Geoenrichment analysis tool.Learn more about Esri's Demographics, Psychographic, and Socioeconomic datasets.Search for a specific location or site using the search bar. Toggle layer visibility with the layer list. Click on a layer to see more information about the feature.