https://data.linz.govt.nz/license/attribution-4-0-international/https://data.linz.govt.nz/license/attribution-4-0-international/
The Population data table is part of NZ Suburbs and Localities Dataset. This table contains the population estimate for each suburb and locality, provided by StatsNZ.
NZ Suburbs and Localities is an easy to use layer generated from the normalised NZ Suburbs and Localities Dataset. It describes the spatial extent and name of communities in urban areas (suburbs) and rural areas (localities) for navigation and location purposes.
The suburb and locality boundaries cover New Zealand including North Island, South Island, Stewart Island/Rakiura, Chatham Islands, and nearby offshore islands.
Each suburb and locality is assigned a name, major name, Territorial Authority and, if appropriate, additional in use names. A population estimate is provided for each suburb and locality by Stats NZ.
For more information please refer to the NZ Suburbs and Localities Guidance documents:
Data Dictionary Change Request Process Change Request Principles, Requirements and Rules Changes to NZ Suburbs and Localities can be requested by emailing addresses@linz.govt.nz
In 2023, the metropolitan area of New York-Newark-Jersey City had the biggest population in the United States. Based on annual estimates from the census, the metropolitan area had around 19.5 million inhabitants, which was a slight decrease from the previous year. The Los Angeles and Chicago metro areas rounded out the top three. What is a metropolitan statistical area? In general, a metropolitan statistical area (MSA) is a core urbanized area with a population of at least 50,000 inhabitants – the smallest MSA is Carson City, with an estimated population of nearly 56,000. The urban area is made bigger by adjacent communities that are socially and economically linked to the center. MSAs are particularly helpful in tracking demographic change over time in large communities and allow officials to see where the largest pockets of inhabitants are in the country. How many MSAs are in the United States? There were 421 metropolitan statistical areas across the U.S. as of July 2021. The largest city in each MSA is designated the principal city and will be the first name in the title. An additional two cities can be added to the title, and these will be listed in population order based on the most recent census. So, in the example of New York-Newark-Jersey City, New York has the highest population, while Jersey City has the lowest. The U.S. Census Bureau conducts an official population count every ten years, and the new count is expected to be announced by the end of 2030.
Population Numbers By New York City Neighborhood Tabulation Areas The data was collected from Census Bureaus' Decennial data dissemination (SF1). Neighborhood Tabulation Areas (NTAs), are aggregations of census tracts that are subsets of New York City's 55 Public Use Microdata Areas (PUMAs). Primarily due to these constraints, NTA boundaries and their associated names may not definitively represent neighborhoods. This report shows change in population from 2000 to 2010 for each NTA. Compiled by the Population Division – New York City Department of City Planning.
Census 2010 population/demographic data approximated from block groups to LA Neighborhood Councils using Esri software.
ABS Census data extract - G01 SELECTED PERSON CHARACTERISTICS BY SEX providing a breakdown of population at Suburb level and by:age groupsaboriginal and/or Torres Strait Islander persons (a)birthplace (b) and (c)language used at home (d)age of persons attending an education institution (e)highest year of school completed (f)count of persons in occupied private dwellings (g)Count of persons in other dwellings (g) (h)This data is based on place of usual residence unless otherwise stated.(a) Applicable to persons who are of both Aboriginal and Torres Strait Islander origin.(b) Includes 'Australia', 'Australia (includes External Territories), nfd', 'Norfolk Island' and 'Australian External Territories, nec'.(c) Includes 'Inadequately described', and 'At sea'. Excludes not stated.(d) Includes 'Inadequately described' and 'Non-verbal, so described'. Excludes not stated.(e) Comprises 'Preschool', 'Primary' (including Government, Catholic, Other non-Government, Primary not further defined), 'Secondary' (including Government, Catholic, Other non-Government, Secondary not further defined) and 'Tertiary' (including vocational education (including TAFE and private training providers), university or other higher education, Tertiary not further defined). Excludes persons who did not state which type of education institution they were attending.(f) Applicable to persons aged 15 years and over.(g) Data is based on place of enumeration. Excludes overseas visitors.(h) Includes 'Visitors only' and 'Other non-classifiable' households, 'Non-private dwellings' and 'Migratory, off-shore and shipping' SA1s.Please note that there are small random adjustments made to all cell values to protect the confidentiality of data. These adjustments may cause the sum of rows or columns to differ by small amounts from table totals.
This data set is a vector polygon digital data structure taken from the Census Bureau's TIGER/Line Files, 1994, for New Mexico. The source software used was ARC/INFO 7.0.3.
ABS Census data extract - G09 COUNTRY OF BIRTH OF PERSON BY AGE providing a breakdown of population at Suburb level and by:age groupscountry of birth of person(a)Australia(b)China (excludes SARs and Taiwan)(c)Hong Kong (SAR of China)(c)Born elsewhere(d)This data is based on place of usual residence.(a) This list consists of the most common 50 Country of Birth responses reported in the 2016 Census and 2011 Census.(b) Includes 'Australia', 'Australia (includes External Territories), nfd', 'Norfolk Island' and 'Australian External Territories, nec'.(c) Special Administrative Regions (SARs) comprise 'Hong Kong (SAR of China)' and 'Macau (SAR of China)'. (d) Includes countries not identified individually, 'Inadequately described', and 'At sea'. Excludes not stated.Please note that there are small random adjustments made to all cell values to protect the confidentiality of data. These adjustments may cause the sum of rows or columns to differ by small amounts from table totals.
In 2023, the population of the Denver-Aurora-Lakewood metropolitan area in the United States was about three million people. This was a slight increase from the previous year, when the population was also about 2.99 million people.
VITAL SIGNS INDICATOR Population (LU1)
FULL MEASURE NAME Population estimates
LAST UPDATED October 2019
DESCRIPTION Population is a measurement of the number of residents that live in a given geographical area, be it a neighborhood, city, county or region.
DATA SOURCES U.S Census Bureau: Decennial Census No link available (1960-1990) http://factfinder.census.gov (2000-2010)
California Department of Finance: Population and Housing Estimates Table E-6: County Population Estimates (1961-1969) Table E-4: Population Estimates for Counties and State (1971-1989) Table E-8: Historical Population and Housing Estimates (2001-2018) Table E-5: Population and Housing Estimates (2011-2019) http://www.dof.ca.gov/Forecasting/Demographics/Estimates/
U.S. Census Bureau: Decennial Census - via Longitudinal Tract Database Spatial Structures in the Social Sciences, Brown University Population Estimates (1970 - 2010) http://www.s4.brown.edu/us2010/index.htm
U.S. Census Bureau: American Community Survey 5-Year Population Estimates (2011-2017) http://factfinder.census.gov
U.S. Census Bureau: Intercensal Estimates Estimates of the Intercensal Population of Counties (1970-1979) Intercensal Estimates of the Resident Population (1980-1989) Population Estimates (1990-1999) Annual Estimates of the Population (2000-2009) Annual Estimates of the Population (2010-2017) No link available (1970-1989) http://www.census.gov/popest/data/metro/totals/1990s/tables/MA-99-03b.txt http://www.census.gov/popest/data/historical/2000s/vintage_2009/metro.html https://www.census.gov/data/datasets/time-series/demo/popest/2010s-total-metro-and-micro-statistical-areas.html
CONTACT INFORMATION vitalsigns.info@bayareametro.gov
METHODOLOGY NOTES (across all datasets for this indicator) All legal boundaries and names for Census geography (metropolitan statistical area, county, city, and tract) are as of January 1, 2010, released beginning November 30, 2010, by the U.S. Census Bureau. A Priority Development Area (PDA) is a locally-designated area with frequent transit service, where a jurisdiction has decided to concentrate most of its housing and jobs growth for development in the foreseeable future. PDA boundaries are current as of August 2019. For more information on PDA designation see http://gis.abag.ca.gov/website/PDAShowcase/.
Population estimates for Bay Area counties and cities are from the California Department of Finance, which are as of January 1st of each year. Population estimates for non-Bay Area regions are from the U.S. Census Bureau. Decennial Census years reflect population as of April 1st of each year whereas population estimates for intercensal estimates are as of July 1st of each year. Population estimates for Bay Area tracts are from the decennial Census (1970 -2010) and the American Community Survey (2008-2012 5-year rolling average; 2010-2014 5-year rolling average; 2013-2017 5-year rolling average). Estimates of population density for tracts use gross acres as the denominator.
Population estimates for Bay Area PDAs are from the decennial Census (1970 - 2010) and the American Community Survey (2006-2010 5 year rolling average; 2010-2014 5-year rolling average; 2013-2017 5-year rolling average). Population estimates for PDAs are derived from Census population counts at the tract level for 1970-1990 and at the block group level for 2000-2017. Population from either tracts or block groups are allocated to a PDA using an area ratio. For example, if a quarter of a Census block group lies with in a PDA, a quarter of its population will be allocated to that PDA. Tract-to-PDA and block group-to-PDA area ratios are calculated using gross acres. Estimates of population density for PDAs use gross acres as the denominator.
Annual population estimates for metropolitan areas outside the Bay Area are from the Census and are benchmarked to each decennial Census. The annual estimates in the 1990s were not updated to match the 2000 benchmark.
The following is a list of cities and towns by geographical area: Big Three: San Jose, San Francisco, Oakland Bayside: Alameda, Albany, Atherton, Belmont, Belvedere, Berkeley, Brisbane, Burlingame, Campbell, Colma, Corte Madera, Cupertino, Daly City, East Palo Alto, El Cerrito, Emeryville, Fairfax, Foster City, Fremont, Hayward, Hercules, Hillsborough, Larkspur, Los Altos, Los Altos Hills, Los Gatos, Menlo Park, Mill Valley, Millbrae, Milpitas, Monte Sereno, Mountain View, Newark, Pacifica, Palo Alto, Piedmont, Pinole, Portola Valley, Redwood City, Richmond, Ross, San Anselmo, San Bruno, San Carlos, San Leandro, San Mateo, San Pablo, San Rafael, Santa Clara, Saratoga, Sausalito, South San Francisco, Sunnyvale, Tiburon, Union City, Vallejo, Woodside Inland, Delta and Coastal: American Canyon, Antioch, Benicia, Brentwood, Calistoga, Clayton, Cloverdale, Concord, Cotati, Danville, Dixon, Dublin, Fairfield, Gilroy, Half Moon Bay, Healdsburg, Lafayette, Livermore, Martinez, Moraga, Morgan Hill, Napa, Novato, Oakley, Orinda, Petaluma, Pittsburg, Pleasant Hill, Pleasanton, Rio Vista, Rohnert Park, San Ramon, Santa Rosa, Sebastopol, Sonoma, St. Helena, Suisun City, Vacaville, Walnut Creek, Windsor, Yountville Unincorporated: all unincorporated towns
This multi-scale map shows counts of the total population the US. Data is from U.S. Census Bureau's 2020 PL 94-171 data for county, tract, block group, and block.County and metro area highlights:The largest county in the United States in 2020 remains Los Angeles County with over 10 million people.The largest city (incorporated place) in the United States in 2020 remains New York with 8.8 million people.312 of the 384 U.S. metro areas gained population between 2010 and 2020.The fastest-growing U.S. metro area between the 2010 Census and 2020 Census was The Villages, FL, which grew 39% from about 93,000 people to about 130,000 people.72 U.S. metro areas lost population from the 2010 Census to the 2020 Census. The U.S. metro areas with the largest percentage declines were Pine Bluff, AR, and Danville, IL, at -12.5 percent and -9.1 percent, respectively.View more 2020 Census statistics highlights on local populations changes.
VITAL SIGNS INDICATOR Population (LU1)
FULL MEASURE NAME
Population estimates
LAST UPDATED
February 2023
DESCRIPTION
Population is a measurement of the number of residents that live in a given geographical area, be it a neighborhood, city, county or region.
DATA SOURCE
California Department of Finance: Population and Housing Estimates - http://www.dof.ca.gov/Forecasting/Demographics/Estimates/
Table E-6: County Population Estimates (1960-1970)
Table E-4: Population Estimates for Counties and State (1970-2021)
Table E-8: Historical Population and Housing Estimates (1990-2010)
Table E-5: Population and Housing Estimates (2010-2021)
Bay Area Jurisdiction Centroids (2020) - https://data.bayareametro.gov/Boundaries/Bay-Area-Jurisdiction-Centroids-2020-/56ar-t6bs
Computed using 2020 US Census TIGER boundaries
U.S. Census Bureau: Decennial Census Population Estimates - http://www.s4.brown.edu/us2010/index.htm- via Longitudinal Tract Database Spatial Structures in the Social Sciences, Brown University
1970-2020
U.S. Census Bureau: American Community Survey (5-year rolling average; tract) - https://data.census.gov/
2011-2021
Form B01003
Priority Development Areas (Plan Bay Area 2050) - https://opendata.mtc.ca.gov/datasets/MTC::priority-development-areas-plan-bay-area-2050/about
CONTACT INFORMATION
vitalsigns.info@bayareametro.gov
METHODOLOGY NOTES (across all datasets for this indicator)
All historical data reported for Census geographies (metropolitan areas, county, city and tract) use current legal boundaries and names. A Priority Development Area (PDA) is a locally-designated area with frequent transit service, where a jurisdiction has decided to concentrate most of its housing and jobs growth for development in the foreseeable future. PDA boundaries are current as of December 2022.
Population estimates for Bay Area counties and cities are from the California Department of Finance, which are as of January 1st of each year. Population estimates for non-Bay Area regions are from the U.S. Census Bureau. Decennial Census years reflect population as of April 1st of each year whereas population estimates for intercensal estimates are as of July 1st of each year. Population estimates for Bay Area tracts are from the decennial Census (1970-2020) and the American Community Survey (2011-2021 5-year rolling average). Estimates of population density for tracts use gross acres as the denominator.
Population estimates for Bay Area tracts and PDAs are from the decennial Census (1970-2020) and the American Community Survey (2011-2021 5-year rolling average). Population estimates for PDAs are allocated from tract-level Census population counts using an area ratio. For example, if a quarter of a Census tract lies with in a PDA, a quarter of its population will be allocated to that PDA. Estimates of population density for PDAs use gross acres as the denominator. Note that the population densities between PDAs reported in previous iterations of Vital Signs are mostly not comparable due to minor differences and an updated set of PDAs (previous iterations reported Plan Bay Area 2040 PDAs, whereas current iterations report Plan Bay Area 2050 PDAs).
The following is a list of cities and towns by geographical area:
Big Three: San Jose, San Francisco, Oakland
Bayside: Alameda, Albany, Atherton, Belmont, Belvedere, Berkeley, Brisbane, Burlingame, Campbell, Colma, Corte Madera, Cupertino, Daly City, East Palo Alto, El Cerrito, Emeryville, Fairfax, Foster City, Fremont, Hayward, Hercules, Hillsborough, Larkspur, Los Altos, Los Altos Hills, Los Gatos, Menlo Park, Mill Valley, Millbrae, Milpitas, Monte Sereno, Mountain View, Newark, Pacifica, Palo Alto, Piedmont, Pinole, Portola Valley, Redwood City, Richmond, Ross, San Anselmo, San Bruno, San Carlos, San Leandro, San Mateo, San Pablo, San Rafael, Santa Clara, Saratoga, Sausalito, South San Francisco, Sunnyvale, Tiburon, Union City, Vallejo, Woodside
Inland, Delta and Coastal: American Canyon, Antioch, Benicia, Brentwood, Calistoga, Clayton, Cloverdale, Concord, Cotati, Danville, Dixon, Dublin, Fairfield, Gilroy, Half Moon Bay, Healdsburg, Lafayette, Livermore, Martinez, Moraga, Morgan Hill, Napa, Novato, Oakley, Orinda, Petaluma, Pittsburg, Pleasant Hill, Pleasanton, Rio Vista, Rohnert Park, San Ramon, Santa Rosa, Sebastopol, Sonoma, St. Helena, Suisun City, Vacaville, Walnut Creek, Windsor, Yountville
Unincorporated: all unincorporated towns
ABS Census data extract - G08 ANCESTRY BY COUNTRY OF BIRTH OF PARENTS providing a breakdown of population at Suburb level and by:ancestry(a)birthplace not stated(b)total responses(c) andother(d)This data is based on place of usual residence.(a) This list of ancestries consists of the most common 30 Ancestry responses reported in the 2016 and 2011 Census. (b) Includes birthplace for either or both parents not stated.(c) This table is a multi-response table and therefore the total responses count will not equal the total persons count.(d) If two responses from one person are categorised in the 'Other' category only one response is counted. Includes ancestries not identified individually and 'Inadequately described'.Please note that there are small random adjustments made to all cell values to protect the confidentiality of data. These adjustments may cause the sum of rows or columns to differ by small amounts from table totals.
In 2021, the population of the San Diego-Chula Vista-Carlsbad metropolitan area in the United States was about 3.29 million people. This is was a slight decrease compared to the previous year, when the population was about 3.3 million.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
The projections are based upon actual values obtained in 2015, and estimates obtained for 2016. A full list of all projections, including historical projections, can be found at http://apps.treasury.act.gov.au/demography/projections/act.
These population projections are not intended to present predictions of the demographic future to any degree of reliability or precision. The population projections contained here are the projected population resulting from certain assumptions about future trends in fertility, mortality and migration trends.
Future population trends are influenced by a variety of social, economic and political factors, with significant fluctuation in short-term population growth rates as well as in the underlying social, economic and political influencers. Numerous behavioural assumptions are required to be made for each age cohort and sex. Many of these assumptions will be swamped by the random impacts on the future movements of individuals through births, deaths, and relocation. Neither the authors nor the ACT Government give warranty in relation to these projections, and no liability is accepted by the authors or the Government or any other person who assisted in the preparation of the publication, for errors and omissions, loss or damage suffered as a result of any person acting in reliance thereon.
The projections are based upon actual values obtained in 2015, and estimates obtained for 2016. A full list of all projections, including historical projections, can be found at http://apps.treasury.act.gov.au/demography/projections/act. These population projections are not intended to present predictions of the demographic future to any degree of reliability or precision. The population projections contained here are the projected population resulting from certain assumptions about future trends in fertility, mortality and migration trends. Future population trends are influenced by a variety of social, economic and political factors, with significant fluctuation in short-term population growth rates as well as in the underlying social, economic and political influencers. Numerous behavioural assumptions are required to be made for each age cohort and sex. Many of these assumptions will be swamped by the random impacts on the future movements of individuals through births, deaths, and relocation. Neither the authors nor the ACT Government give warranty in relation to these projections, and no liability is accepted by the authors or the Government or any other person who assisted in the preparation of the publication, for errors and omissions, loss or damage suffered as a result of any person acting in reliance thereon.
This layer shows the age statistics in Tucson by neighborhood, aggregated from block level data, between 2010-2019. For questions, contact GIS_IT@tucsonaz.gov. The data shown is from Esri's 2019 Updated Demographic estimates.Esri's U.S. Updated Demographic (2019/2024) Data - Population, age, income, sex, race, home value, and marital status are among the variables included in the database. Each year, Esri's Data Development team employs its proven methodologies to update more than 2,000 demographic variables for a variety of U.S. geographies.Additional Esri Resources:Esri DemographicsU.S. 2019/2024 Esri Updated DemographicsEssential demographic vocabularyPermitted use of this data is covered in the DATA section of the Esri Master Agreement (E204CW) and these supplemental terms.
This dataset utilizes 2020 US Census data and the Esri 2023 Estimate (#) of the Total Population in the geographic area. Total Population includes population living in households, on active duty in the Armed Forces, and living in group quarters such as correctional facilities, skilled nursing facilities, juvenile facilities, college dorms, and military barracks.
ODC Public Domain Dedication and Licence (PDDL) v1.0http://www.opendatacommons.org/licenses/pddl/1.0/
License information was derived automatically
Demographic Data for Boston’s Neighborhoods, 1950-2019
Boston is a city defined by the unique character of its many neighborhoods. The historical tables created by the BPDA Research Division from U.S. Census Decennial data describe demographic changes in Boston’s neighborhoods from 1950 through 2010 using consistent tract-based geographies. For more analysis of these data, please see Historical Trends in Boston's Neighborhoods. The most recent available neighborhood demographic data come from the 5-year American Community Survey (ACS). The ACS tables also present demographic data for Census-tract approximations of Boston’s neighborhoods. For pdf versions of the data presented here plus earlier versions of the analysis, please see Boston in Context.
https://www.icpsr.umich.edu/web/ICPSR/studies/6398/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/6398/terms
This data collection provides statistics gathered from a variety of federal agencies and national associations. Demographic, economic, and governmental data from both the federal government and private agencies are presented to enable multiarea comparisons as well as single-area profiles. Current estimates and benchmark census results are included. Data are available for five types of geographic coverage: (1) Metro Areas data cover 249 metropolitan statistical areas (MSAs), 17 consolidated metropolitan statistical areas (CMSAs), 54 primary metropolitan statistical areas (PSMAs), and 16 New England county metropolitan areas (NECMAs). Metro Areas data include the following general subjects: area and population, households, vital statistics, health, education, crime, housing, money income, personal income, civilian labor force, employment, construction, commercial office space, manufacturing, wholesale and retail trade, service industries, banking, federal funds and grants, and government employment. There are 14 parts for Metro Areas. (2) State Metro/Nonmetro data cover the United States, the 50 states, the District of Columbia, and the metropolitan and nonmetropolitan portions of these areas. State Metro/Nonmetro data include most of the subjects listed for Metro Areas. There are six parts for State Metro/Nonmetro. (3) Metro Counties data cover 336 metropolitan areas and their component counties and include topics identical to those presented in the State Metro/Nonmetro data. Six parts are supplied for Metro Counties. (4) Metro Central Cities data cover 336 metropolitan areas and their 522 central cities and 336 outside central cities portions. Metro Central Cities variables are limited to 13 items, which include area and population, money income, civilian labor force, and retail trade. There is one part for Metro Central Cities. (5) States data cover the United States, the 50 states, the District of Columbia, and census regions and divisions. States data include the same items as the Metro Areas data, plus information on social welfare programs, geography and environment, domestic travel and parks, gross state product, poverty, wealth holders, business, research and development, agriculture, forestry and fisheries, minerals and mining, transportation, communications, energy, state government, federal government, and elections. There are 101 parts for States.
These boundaries were developed by the Department of Planning based on 2020 Census data. Be aware that other organizations may use different neighborhood boundaries in their analyses.Demographics included are: race, ethnicity, gender, vacancy rate, homeowner status, family structure, and age.DATA DICTIONARY:
Field Name
Description
Name
Name of neighborhood statistical area
Population
Total population (P3)
White
White alone population (P3)
Blk_AfAm
Black or African American alone population (P3)
AmInd_AkNa
American Indian/Native Alaskan alone population (P3)
Asian
Asian alone population (P3)
NatHaw_Pac
Native Hawaiian and other Pacific Islander alone population (P3)
Other_Race
Some other race alone population (P3)
TwoOrMore
Two or more races population (P3)
Hisp_Lat
Hispanic or Latino population (P4)
Male
Male population (P12)
Female
Female population (P12)
Total_Units
Total housing units (H1)
Occ_Occupied
Occupied housing units (H3)
Occ_Vacant
Vacant housing units (H3)
Tenure_Owner
Owner-occupied units (H4)
Tenure_Renter
Renter-occupied units (H4)
Vacant_ForRent
Vacant units for rent (H5)
Vacant_ForSale
Vacant units for sale (H5)
Vacant_Other_All
All other vacant units (H5)
HH_Total
Total households (P16)
HH_Family
Total family households (P16)
HH_Married
Married couple family households (P16)
HH_OtherFamily
Other family households (P16)
HH_Male_NoSpouse
Male householder, no spouse present family household (P16)
HH_Female_NoSpouse
Female householder, no spouse present family household (P16)
HH_NonFamily
Total nonfamily households (P16)
HH_NonFamilyAlone
Householder living alone nonfamily households (P16)
HH_NonFamilyNotAlone
Householder not living alone nonfamily households (P16)
HH18_With18
Households with one or more people under 18 (P21)
HH18_FamilyWith18
Family households with one or more people under 18 (P21)
HH18_NonFamilyWith18
Nonfamily households with one or more people under 18 (P21)
HH18_No18
Households with no people under 18 (P21)
HH18_FamilyNo18
Family households with no people under 18 (P21)
HH18_NonFamilyNo18
Nonfamily households with no people under 18 (P21)
Age_U5
Population under 5 years (P12)
Age_5_9
Population age 5-9 (P12)
Age_10_14
Population age 10-14 (P12)
Age_15_17
Population age 15-17 (P12)
Age_18_21
Population age 18-21 (P12)
Age_22_24
Population age 22-24 (P12)
Age_25_29
Population age 25-29 (P12)
Age_30_34
Population age 30-34 (P12)
Age_35_39
Population age 35-39 (P12)
Age_40_44
Population age 40-44 (P12)
Age_45_49
Population age 45-49 (P12)
Age_50_54
Population age 50-54 (P12)
Age_55_59
Population age 55-59 (P12)
Age_60_64
Population age 60-64 (P12)
Age_65_69
Population age 65-69 (P12)
Age_70_74
Population age 70-74 (P12)
Age_75_79
Population age 75-79 (P12)
Age_80_84
Population age 80-84 (P12)
Age_85up
Population age 85 and up (P12)
Med_Age
Median age (P13)
Med_Age_Male
Median male age (P13)
Med_Age_Female
Median female age (P13)
To leave feedback or ask a question about this dataset, please fill out the following form: Neighborhood Statistical Area (NSA) Boundaries feedback form.
https://data.linz.govt.nz/license/attribution-4-0-international/https://data.linz.govt.nz/license/attribution-4-0-international/
The Population data table is part of NZ Suburbs and Localities Dataset. This table contains the population estimate for each suburb and locality, provided by StatsNZ.
NZ Suburbs and Localities is an easy to use layer generated from the normalised NZ Suburbs and Localities Dataset. It describes the spatial extent and name of communities in urban areas (suburbs) and rural areas (localities) for navigation and location purposes.
The suburb and locality boundaries cover New Zealand including North Island, South Island, Stewart Island/Rakiura, Chatham Islands, and nearby offshore islands.
Each suburb and locality is assigned a name, major name, Territorial Authority and, if appropriate, additional in use names. A population estimate is provided for each suburb and locality by Stats NZ.
For more information please refer to the NZ Suburbs and Localities Guidance documents:
Data Dictionary Change Request Process Change Request Principles, Requirements and Rules Changes to NZ Suburbs and Localities can be requested by emailing addresses@linz.govt.nz