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.

Of the five boroughs of New York City, Stanten Island has the highest rate of coronavirus cases per 100,000 people. Brooklyn – the most populous borough – has around 36,008 cases per 100,000 people, and only Manhattan has a lower case rate.

Brooklyn hit hard by COVID-19 Towards the middle of December 2022, there had been almost 6.37 million positive infections in New York State, and Kings was the county with the highest number of coronavirus cases. Kings County, which has the same boundaries as the borough of Brooklyn, had also recorded the highest number of deaths due to the coronavirus in New York State. Since the start of the pandemic in the U.S., densely populated neighborhoods in Brooklyn and Queens have been severely affected, and government leaders across New York State have had to find solutions to some unprecedented challenges.

Projected New York City population numbers and percentage changes from 2010 through 2040 by Borough, including school-age, 65 and Over, and total population.

This dataset contains the New York City Population By Community Districts.The community boards of the New York City government are the appointed advisory groups of the community districts of the five boroughs. There are currently 59 community districts, including twelve in Manhattan, twelve in the Bronx, eighteen in Brooklyn, fourteen in Queens, and three in Staten Island.

New York City Population FactFinder (NYC PFF) provides detailed population and housing profiles for user defined areas within New York City. Using data from decennial censuses and the American Community Survey, the profiles are comprehensive, covering the most basic population statistics, along with detailed social, economic, and housing information. Data for user-defined areas can be easily contrasted against New York City, City boroughs, City Community Districts (approximate equivalents are used), and City neighborhoods (Neighborhood Tabulation Areas). Along with count statistics (like total Spanish-speaking population), users are provided with percent values (like percent of the population with a bachelor’s degree or higher), arithmetic means (like mean travel time to work), rates (like rental housing vacancy rate), and medians (like median household income). NYC PFF profiles can also show how a selected area has changed over time. Further, each profile contains charts allowing users to visualize the distribution of selected statistics, comparing user-defined study areas with a contrast area. All NYC PFF estimates are evaluated for data reliability – unreliable data are grayed out, alerting users of unsuitability for general use.

As of 2023, all five boroughs of New York City had water service lines that were definitely or possibly made of lead. Brooklyn had the largest average share of lead/possible lead service lines (LSL), at ** percent. Manhattan and Bronx followed with ** and ** percent, respectively. Lead is a neurotoxin that poses serious adverse health risks to humans. An estimated ** percent of the New York City population may be exposed to lead-contaminated drinking water.

About this dataset

Context

The dataset tabulates the population of Brooklyn borough by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Brooklyn borough. The dataset can be utilized to understand the population distribution of Brooklyn borough by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Brooklyn borough. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Brooklyn borough.

Key observations

Largest age group (population): Male # 30-34 years (119,643) | Female # 30-34 years (123,624). Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Brooklyn borough population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Brooklyn borough is shown in the following column.
• Population (Female): The female population in the Brooklyn borough is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Brooklyn borough for each age group.

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 Brooklyn borough Population by Gender. You can refer the same here

About this dataset

Context

The dataset tabulates the population of Staten Island borough by race. It includes the population of Staten Island borough across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Staten Island borough across relevant racial categories.

Key observations

The percent distribution of Staten Island borough population by race (across all racial categories recognized by the U.S. Census Bureau): 62.85% are white, 9.94% are Black or African American, 0.53% are American Indian and Alaska Native, 12.10% are Asian, 0.03% are Native Hawaiian and other Pacific Islander, 5.33% are some other race and 9.23% are multiracial.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (excluding ethnicity) for the Staten Island borough
• Population: The population of the racial category (excluding ethnicity) in the Staten Island borough is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Staten Island borough total population. 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 Staten Island borough Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

The dataset tabulates the population of Manhattan borough by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Manhattan borough. The dataset can be utilized to understand the population distribution of Manhattan borough by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Manhattan borough. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Manhattan borough.

Key observations

Largest age group (population): Male # 30-34 years (83,603) | Female # 25-29 years (92,613). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Manhattan borough population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Manhattan borough is shown in the following column.
• Population (Female): The female population in the Manhattan borough is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Manhattan borough for each age group.

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 Manhattan borough Population by Gender. You can refer the same here

NYC Coronavirus (COVID-19) data

This repository contains data on coronavirus (COVID-19) in New York City (NYC), updated daily. Data are assembled by the NYC Department of Health and Mental Hygiene (DOHMH) Incident Command System for COVID-19 Response (Surveillance and Epidemiology Branch in collaboration with Public Information Office Branch). You can view these data on the Department of Health's website. Note that data are being collected in real-time and are preliminary and subject to change as COVID-19 response continues.

Files summary.csv This file contains summary information, including when the dataset was "cut" - the cut-off date and time for data included in this update.

Estimated hospitalization counts reflect the total number of people ever admitted to a hospital, not currently admitted.

case-hosp-death.csv This file includes daily counts of new confirmed cases, hospitalizations, and deaths.

Cases are by date of diagnosis Hospitalizations are by date of admission Deaths are by date of death Because of delays in reporting, the most recent data may be incomplete. Data shown currently will be updated in the future as new cases, hospitalizations, and deaths are reported.

boro.csv This contains rates of confirmed cases, by NYC borough of residence. Rates are:

Cumulative since the start of the outbreak Age adjusted according to the US 2000 standard population Per 100,000 people in the borough by-age.csv This contains age-specific rates of confirmed cases, hospitalizations, and deaths.

by-sex.csv This contains rates of confirmed cases, hospitalizations, and deaths.

testing.csv This file includes counts of New York City residents with specimens collected for SARS-CoV-2 testing by day, the subsets who tested positive as confirmed COVID-19 cases, were ever hospitalized, and who died, as of the date of extraction from the NYC Health Department's disease surveillance database. For each date of extraction, results for all specimen collection dates are appended to the bottom of the dataset. Lags between specimen collection date and report dates of cases, hospitalizations, and deaths can be assessed by comparing counts for the same specimen collection date across multiple data extract dates.

tests-by-zcta.csv This file includes the cumulative count of New York City residents by ZIP code of residence who:

Were ever tested for COVID-19 (SARS-CoV-2) Tested positive The cumulative counts are as of the date of extraction from the NYC Health Department's disease surveillance database. Technical Notes This section may change as data and documentation are updated.

Estimated number of COVID-19 patients ever hospitalized At this time, NYC DOHMH does not have the ability to robustly quantify the number of people currently admitted to a hospital given intense resource and time constraints on hospital reporting systems. Therefore, we have estimated the number of individuals diagnosed with COVID-19 who have ever been hospitalized by matching the list of key fields from known cases that are reported by laboratories to the NYC DOHMH Bureau of Communicable Disease surveillance database to other sources of hospital admission information. These other sources include:

The NYC DOHMH syndromic surveillance database that tracks daily hospital admissions from all 53 emergency departments across NYC The New York State Department of Health Hospital Emergency Response Data System (HERDS). Rates per 100,000 people Annual citywide, borough-specific, and demographic specific intercensal population estimates from 2018 were developed by NYC DOHMH on the basis of the US Census Bureau’s Population Estimates Program, as of November 2019.

Rates of cases at the borough-level were calculated using direct standardization for age at diagnosis and weighting by the US 2000 standard population.

https://github.com/nychealth/coronavirus-data/blob/master/README.md

About this dataset

Context

The dataset tabulates the population of Bronx borough by race. It includes the population of Bronx borough across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Bronx borough across relevant racial categories.

Key observations

The percent distribution of Bronx borough population by race (across all racial categories recognized by the U.S. Census Bureau): 15.77% are white, 34.11% are Black or African American, 1.18% are American Indian and Alaska Native, 4.07% are Asian, 0.15% are Native Hawaiian and other Pacific Islander, 31.79% are some other race and 12.93% are multiracial.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (excluding ethnicity) for the Bronx borough
• Population: The population of the racial category (excluding ethnicity) in the Bronx borough is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Bronx borough total population. 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 Bronx borough Population by Race & Ethnicity. You can refer the same here

Many residents of New York City speak more than one language; a number of them speak and understand non-English languages more fluently than English. This dataset, derived from the Census Bureau's American Community Survey (ACS), includes information on over 1.7 million limited English proficient (LEP) residents and a subset of that population called limited English proficient citizens of voting age (CVALEP) at the Community District level. There are 59 community districts throughout NYC, with each district being represented by a Community Board.

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 TIGER/Line shapefiles include both incorporated places (legal entities) and census designated places or CDPs (statistical entities). An incorporated place is established to provide governmental functions for a concentration of people as opposed to a minor civil division (MCD), which generally is created to provide services or administer an area without regard, necessarily, to population. Places always nest within a state, but may extend across county and county subdivision boundaries. An incorporated place usually is a city, town, village, or borough, but can have other legal descriptions. CDPs are delineated for the decennial census as the statistical counterparts of incorporated places. CDPs are delineated to provide data for settled concentrations of population that are identifiable by name, but are not legally incorporated under the laws of the state in which they are located. The boundaries for CDPs often are defined in partnership with state, local, and/or tribal officials and usually coincide with visible features or the boundary of an adjacent incorporated place or another legal entity. CDP boundaries often change from one decennial census to the next with changes in the settlement pattern and development; a CDP with the same name as in an earlier census does not necessarily have the same boundary. The only population/housing size requirement for CDPs is that they must contain some housing and population. The boundaries of most incorporated places in this shapefile are as of January 1, 2020, as reported through the Census Bureau's Boundary and Annexation Survey (BAS). The boundaries of all CDPs were delineated as part of the Census Bureau's Participant Statistical Areas Program (PSAP) for the 2020 Census.

Overview and Inspiration

I wanted to make some geospatial visualizations to convey the current severity of COVID19 in different parts of the U.S..

I liked the NYTimes COVID dataset, but it was lacking information on county boundary shape data, population per county, new cases / deaths per day, and per capita calculations, and county demographics.

After a lot of work tracking down the different data sources I wanted and doing all of the data wrangling and joins in python, I wanted to open-source the final enriched data set in order to give others a head start in their COVID-19 related analytic, modeling, and visualization efforts.

This dataset is enriched with county shapes, county center point coordinates, 2019 census population estimates, county population densities, cases and deaths per capita, and calculated per day cases / deaths metrics. It contains daily data per county back to January, allowing for analyizng changes over time.

UPDATE: I have also included demographic information per county, including ages, races, and gender breakdown. This could help determine which counties are most susceptible to an outbreak.

How this data can be used

Geospatial analysis and visualization - Which counties are currently getting hit the hardest (per capita and totals)? - What patterns are there in the spread of the virus across counties? (network based spread simulations using county center lat / lons) -county population densities play a role in how quickly the virus spreads? -how does a specific county/state cases and deaths compare to other counties/states? Join with other county level datasets easily (with fips code column)

Content Details

See the column descriptions for more details on the dataset

Visualizations and Analysis Examples

COVID-19 U.S. Time-lapse: Confirmed Cases per County (per capita)

https://github.com/ringhilterra/enriched-covid19-data/blob/master/example_viz/covid-cases-final-04-06.gif?raw=true" alt="">-

Other Data Notes

• Please review nytimes README for detailed notes on Covid-19 data - https://github.com/nytimes/covid-19-data/
• The only update I made in regards to 'Geographic Exceptions', is that I took 'New York City' county provided in the Covid-19 data, which has all cases for 'for the five boroughs of New York City (New York, Kings, Queens, Bronx and Richmond counties) and replaced the missing FIPS for those rows with the 'New York County' fips code 36061. That way I could join to a geometry, and then I used the sum of those five boroughs population estimates for the 'New York City' estimate, which allowed me calculate 'per capita' metrics for 'New York City' entries in the Covid-19 dataset

Acknowledgements

• Special thanks to NYTimes for all of their hard work gathering and consolidating all of the U.S. COVID19 related data on daily basis. Their git repo https://github.com/nytimes/covid-19-data/
• Also, thanks to ykzeng for the county population density estimates: https://github.com/ykzeng/covid-19/tree/master/data-

Uniquely Popular Businesses

Rankings of Business Categories in Seattle & NYC Neighborhoods

By data.world's Admin [source]

About this dataset

This dataset contains data used to analyze the uniquely popular business types in the neighborhoods of Seattle and New York City. We used publically available neighborhood-level shapefiles to identify neighborhoods, and then crossed that information against Yelp's Business Category API to find businesses operating within each neighborhood. The ratio of businesses from each category was studied in comparison to their ratios in the entire city to determine any significant differences between each borough.

Any single business with more than one category was repeated for each one, however none of them were ever recorded twice for any single category. Moreover, if a certain business type didn't make up at least 1% of a particular neighborhood's businesses overall it was removed from the analysis altogether.

The data available here is free to use under MIT license, with appropriate attribution given back to Yelp for providing this information. It is an invaluable resource for researchers across different disciplines looking into consumer behavior or clustering within urban areas!

More Datasets

For more datasets, click here.

Featured Notebooks

• 🚨 Your notebook can be here! 🚨!

How to use the dataset

How to Use This Dataset

To get started using this dataset: - Download the appropriate file for the area you’re researching - either salt5_Seattle.csv or top5_NewYorkCity.csv - from the Kaggle site which hosts this dataset (https://www.kaggle.com/puddingmagazine/uniquely-popular-businesses). - Read through each columns information available under Columns section associated with this kaggle description (above).
- Take note of columns that are relevant to your analysis such as nCount which indicates the number of businesses in a neighborhood, rank which shows how popular that business type is overall and neighborhoodTotal which specifies total number of businesses in a particular neighborhood etc.,
- ) Load your selected file into an application designed for data analysis such as Jupyter Notebook, Microsoft Excel, Power BI etc.,
- ) Begin performing various analyses related to understanding where certain types of unique business are most common by subsetting rows based on specific neighborhoods; alternatively perform regressions-based analyses related to trends similar unique type's ranks over multiple neighborhoods etc.,

If you have any questions about interpreting data from this source please reach out if needed!

Research Ideas

• Analyzing the unique business trends in Seattle and New York City to identify potential investment opportunities.
• Creating a tool that helps businesses understand what local competitions they face by neighborhood.
• Exploring the distinctions between neighborhoods by plotting out the different businesses they have in comparison with each other and other cities

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

See the dataset description for more information.

Columns

File: top5_Seattle.csv | Column name | Description | |:----------------------|:----------------------------------------------------------------------------------------------------------------------------------| | neighborhood | Name of the neighborhood. (String) | | yelpAlias | The Yelp-specified Alias for the business type. (String) | | yelpTitle | The Title given to this business type by Yelp. (String) | | nCount | Number of businesses with this type within a particular neighborhood. (Integer) | | neighborhoodTotal | Total number of businesses located within that particular region. (Integer) | | cCount | Number of businesses with this storefront within an entire city. (Integer) | | cityTotal | Total number of all types of storefronts within an entire city. (Integer) ...

The NYC KIDS Survey is a population-based telephone survey conducted by the Health Department. The survey provides robust data on the health of children aged 13 years or younger (2017: children aged 0-13 years; 2019: children aged 1-13 years) in New York City, including citywide and borough estimates, on a broad range of topics including physical and mental health, health care access, and school and childcare enrollment and learning. For more information, visit https://www1.nyc.gov/site/doh/data/data-sets/child-chs.page

New York has become one of the worst-affected COVID-19 hotspots and a pandemic epicenter due to the ongoing crisis. This paper identifies the impact of the pandemic and the effectiveness of government policies on human mobility by analyzing multiple datasets available at both macro and micro levels for New York City. Using data sources related to population density, aggregated population mobility, public rail transit use, vehicle use, hotspot and non-hotspot movement patterns, and human activity agglomeration, we analyzed the inter-borough and intra-borough movement for New York City by aggregating the data at the borough level. We also assessed the internodal population movement amongst hotspot and non-hotspot points of interest for the month of March and April 2020. Results indicate a drop of about 80% in people’s mobility in the city, beginning in mid-March. The movement to and from Manhattan showed the most disruption for both public transit and road traffic. The city saw its first case on March 1, 2020, but disruptions in mobility can be seen only after the second week of March when the shelter in place orders was put in effect. Owing to people working from home and adhering to stay-at-home orders, Manhattan saw the largest disruption to both inter- and intra-borough movement. But the risk of spread of infection in Manhattan turned out to be high because of higher hotspot-linked movements. The stay-at-home restrictions also led to an increased population density in Brooklyn and Queens as people were not commuting to Manhattan. Insights obtained from this study would help policymakers better understand human behavior and their response to the news and governmental policies.

About this dataset

Context

The dataset tabulates the population of Queens borough by race. It includes the population of Queens borough across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Queens borough across relevant racial categories.

Key observations

The percent distribution of Queens borough population by race (across all racial categories recognized by the U.S. Census Bureau): 28.35% are white, 17.39% are Black or African American, 0.71% are American Indian and Alaska Native, 26.05% are Asian, 0.07% are Native Hawaiian and other Pacific Islander, 16.21% are some other race and 11.23% are multiracial.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (excluding ethnicity) for the Queens borough
• Population: The population of the racial category (excluding ethnicity) in the Queens borough is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Queens borough total population. 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 Queens borough Population by Race & Ethnicity. You can refer the same here

Projected total New York City population for five intervals from 2010 through 2040 by Borough, broken down by 18 age cohorts. (Age groups may not add up to the total due to rounding.)

Splitgraph serves as an HTTP API that lets you run SQL queries directly on this data to power Web applications. For example:

See the Splitgraph documentation for more information.

Presents the number of individuals for each shelter facility type by borough and community district