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Context
The dataset tabulates the Darwin 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 Darwin 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 Darwin was 336, a 1.47% decrease year-by-year from 2022. Previously, in 2022, Darwin population was 341, a decline of 0% compared to a population of 341 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Darwin decreased by 27. In this period, the peak population was 391 in the year 2008. 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).
When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).
Data Coverage:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Darwin Population by Year. You can refer the same here
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TwitterComprehensive demographic dataset for Darwin Downs, Huntsville, AL, US including population statistics, household income, housing units, education levels, employment data, and transportation with year-over-year changes.
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Australia Population: Resident: Estimated: Annual: Northern Territory: Greater Darwin data was reported at 148,884.000 Person in 2017. This records an increase from the previous number of 147,102.000 Person for 2016. Australia Population: Resident: Estimated: Annual: Northern Territory: Greater Darwin data is updated yearly, averaging 131,105.500 Person from Jun 2006 (Median) to 2017, with 12 observations. The data reached an all-time high of 148,884.000 Person in 2017 and a record low of 113,461.000 Person in 2006. Australia Population: Resident: Estimated: Annual: Northern Territory: Greater Darwin data remains active status in CEIC and is reported by Australian Bureau of Statistics. The data is categorized under Global Database’s Australia – Table AU.G002: Estimated Resident Population.
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Context
The dataset tabulates the population of Darwin by race. It includes the population of Darwin across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Darwin across relevant racial categories.
Key observations
The percent distribution of Darwin population by race (across all racial categories recognized by the U.S. Census Bureau): 92.73% are white, 5.97% are some other race and 1.30% are multiracial.
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:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Darwin Population by Race & Ethnicity. You can refer the same here
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Context
The dataset tabulates the Darwin population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Darwin. The dataset can be utilized to understand the population distribution of Darwin by age. For example, using this dataset, we can identify the largest age group in Darwin.
Key observations
The largest age group in Darwin, MN was for the group of age 10 to 14 years years with a population of 40 (10.39%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in Darwin, MN was the 85 years and over years with a population of 1 (0.26%). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates
Age groups:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Darwin Population by Age. You can refer the same here
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The dataset tabulates the population of Darwin by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Darwin. The dataset can be utilized to understand the population distribution of Darwin by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Darwin. 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 Darwin.
Key observations
Largest age group (population): Male # 10-14 years (26) | Female # 65-69 years (20). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Age groups:
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
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.
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/.
This dataset is a part of the main dataset for Darwin Population by Gender. You can refer the same here
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The workforce dataset contains monthly workforce sizes from July 2005 to June 2018 in the eight Australian capital cities with estimated stratification by indoor and outdoor workers. It is included in both csv and rda format. It includes variables for:
Year Month GCCSA (Greater Capital City Statistical Area, which is used to define capital cities) Date (using the first day of the month) fulltime: Fulltime workers parttime: Parttime workers n. Overall workers outorin. Estimated indoor or outdoor status
This data are derived from the Australian Bureau of Statistics (ABS) Labour Force, Australia, Detailed, LM1 dataset: LM1 - Labour force status by age, greater capital city and rest of state (ASGS), marital status and sex, February 1978 onwards (pivot table). Occupational data from the 2006, 2011 and 2016 Census of Population and Housing (ABS Census TableBuilder Basic data) were used to stratify this dataset into indoor and outdoor classifications as per the "Indooroutdoor classification.xlsx" file. For the Census data, GCCSA for the place of work was used, not the place of usual residence.
Occupations were defined by the Australian and New Zealand Standard Classification of Occupations (ANZSCO). Each 6-digit ANZSCO occupation (the lowest level classification) was manually cross-matched with their corresponding occupation(s) from the Canadian National Occupation System (NOC). ANZSCO and NOC share a similar structure, because they are both derived from the International Standard Classification of Occupations. NOC occupations listed with an “L3 location” (include main duties with outdoor work for at least part of the working day) were classified as outdoors, including occupations with multiple locations. Occupations without a listing of "L3 location" were classified as indoors (no outdoor work). 6-digit ANZSCO occupations were then aggregated to 4-digit unit groups to match the ABS Census TableBuilder Basic data. These data were further aggregated into indoor and outdoor workers. The 4-digit ANZSCO unit groups’ indoor and outdoor classifications are listed in "Indooroutdoor classification.xlsx."
ANZSCO occupations associated with both indoor and outdoor listings were classified based on the more common listing, with indoors being selected in the event of a tie. The cross-matching of ANZSCO and NOC occupation was checked against two previous cross-matches used in published Australian studies utilising older ANZSCO and NOC versions. One of these cross-matches, the original cross-match, was validated with a strong correlation between ANZSCO and NOC for outdoor work (Smith, Peter M. Comparing Imputed Occupational Exposure Classifications With Self-reported Occupational Hazards Among Australian Workers. 2013).
To stratify the ABS Labour Force detailed data by indoors or outdoors, workers from the ABS Census 2006, 2011 and 2016 data were first classified as indoors or outdoors. To extend the indoor and outdoor classification proportions from 2005 to 2018, the population counts were (1) stratified by workplace GCCSA (standardised to the 2016 metrics), (2) logit-transformed and then interpolated using cubic splines and extrapolated linearly for each month, and (3) back-transformed to the normal population scale. For the 2006 Census, workplace location was reported by Statistical Local Area and then converted to GCCSA. This interpolation method was also used to estimate the 1-monthly worker count for Darwin relative to the rest of Northern Territory (ABS worker 1-monthly counts are reported only for Northern Territory collectively).
ABS data are owned by the Commonwealth Government under a CC BY 4.0 license. The attached datasets are derived and aggregated from ABS data.
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Context
The dataset tabulates the data for the Darwin, MN population pyramid, which represents the Darwin population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey 5-Year estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
Age groups:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Darwin Population by Age. You can refer the same here
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Twitterhttps://data.gov.in/sites/default/files/Gazette_Notification_OGDL.pdfhttps://data.gov.in/sites/default/files/Gazette_Notification_OGDL.pdf
Comprehensive population and demographic data for Darwin (70) Village
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TwitterABS 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.
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Enetwild consortium developed a data standard on wildlife monitoring data to aggregate raw data such as occurrences, drive hunt hunting bags, distance sampling data, or aggregated or estimated data such as density estimates, summarized hunting bags, probability of presence. This standard is based on the Darwin Core standard, using the Event core, the Occurrence extension, the extended measurement or fact extension. We proposed to extend the measurement or fact extension to allow them to be nested among themselves for recording confidence intervals and precision information. We offer the possibility to nest occurrences within each other as well. We propose controlled vocabularies in relation to statistical information, in both data and metadata. In addition to a single metadata sheet, this Excel file proposes two ways to enter a dataset. The first option is to record events, occurrences, and measurements in different sheets, which is similar to the option proposed by GBIF in its Integrated Publishing Toolkit. The second option is to record events, occurrences and measurements in a single sheet (data_AllInOne) with the help of conditional formatting, working on the most recent version of Excel.
This is in line with the EFSA data model harmonisation under the SIGMA project.
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人口:居民:估计:年度:北部地区:大达尔文 在06-01-2017达148,884.000人,相较于06-01-2016的147,102.000人有所增长。人口:居民:估计:年度:北部地区:大达尔文 数据按年更新,06-01-2006至06-01-2017期间平均值为131,105.500人,共12份观测结果。该数据的历史最高值出现于06-01-2017,达148,884.000人,而历史最低值则出现于06-01-2006,为113,461.000人。CEIC提供的人口:居民:估计:年度:北部地区:大达尔文 数据处于定期更新的状态,数据来源于Australian Bureau of Statistics,数据归类于全球数据库的澳大利亚 – 表 AU.G002:估计常住人口。
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Context
The dataset tabulates the Darwin population by age cohorts (Children: Under 18 years; Working population: 18-64 years; Senior population: 65 years or more). It lists the population in each age cohort group along with its percentage relative to the total population of Darwin. The dataset can be utilized to understand the population distribution across children, working population and senior population for dependency ratio, housing requirements, ageing, migration patterns etc.
Key observations
The largest age group was 18 - 64 years with a poulation of 209 (53.73% of the total population). Source: U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
Age cohorts:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Darwin Population by Age. You can refer the same here
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TwitterThe Darwin urban centre consists of Darwin City and the associated suburbs from Buffalo Creek, Berrimah and East Arm westwards, and represents approximately 35% of the Northern Territory’s population. The Darwin region falls within the NT Police Darwin Metropolitan Command. The offence data were extracted from the NT Police PROMIS system. Offence rates have been calculated using the latest available estimated resident population data from the Australian Bureau of Statistics (Australian Demographic Statistics, cat. 3101.0, with regional splits based on Regional Population Growth, Australia, 2012, cat. 3218.0). Data requests can be submitted for data not available on the website.
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Darwin’s frogs (Rhinoderma darwinii and R. rufum) are two species of mouth-brooding frogs from Chile and Argentina. Here, we present evidence on the extent of declines, current distribution and conservation status of Rhinoderma spp.; including information on abundance, habitat and threats to extant Darwin’s frog populations. All known archived Rhinoderma specimens were examined in museums in North America, Europe and South America. Extensive surveys were carried out throughout the historical ranges of R. rufum and R. darwinii from 2008 to 2012. Literature review and location data of 2,244 archived specimens were used to develop historical distribution maps for Rhinoderma spp. Based on records of sightings, optimal linear estimation was used to estimate whether R. rufum can be considered extinct. No extant R. rufum was found and our modelling inferred that this species became extinct in 1982 (95% CI, 1980–2000). Rhinoderma darwinii was found in 36 sites. All populations were within native forest and abundance was highest in Chiloé Island, when compared with Coast, Andes and South populations. Estimated population size and density (five populations) averaged 33.2 frogs/population (range, 10.2–56.3) and 14.9 frogs/100 m2 (range, 5.3–74.1), respectively. Our results provide further evidence that R. rufum is extinct and indicate that R. darwinii has declined to a much greater degree than previously recognised. Although this species can still be found across a large part of its historical range, remaining populations are small and severely fragmented. Conservation efforts for R. darwinii should be stepped up and the species re-classified as Endangered.
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These data and code are intentended to serve as complementary information to allow the full reproducibility of the results presented in the study "Natal dispersal is facilitated by routine movements integrated along a straight path in the Darwin’s frog" submitted to Ecography.
The first file titled "data and code used to run the sCJS.rar" contains capture-recapture data from three populations of the Darwin's frog (Rhinoderma darwinii) collected between March 2014 and December 2016. The age of the individuals, population of origin, and x- and y-coordinates of each capture are provided. The x- and y-coordinates are in meters. The sampling design follows the Pollock's robust design. The capture-history matrices (one for the x-coordinates and another for the y-coordinates) contain 48 columns representing twelve evenly distributed primary capture periods, each one composed of four consecutive days of capture (secondary capture ocassions). The time-period between primary capture periods is 3 months. However, note that we did not visited the populations during all these periods, therefore, some of collumns contain only NA's. The rows of the capture-history matrices represent the different individuals that were captured across the study. There are 370 rows, but for seven of these individuals we don't have spatial data (these individuals are removed in the code). Then we provide the R code used to run the sCJS of Schaub and Royle (2014). This code is almost identical to the provided by these authors, but a few modifications were made in order to fit our study design. Results of the model are also provided.
The second file "Data required to run the simulation model.rar" contains the data required to run the movement path simulation model presented in the Supplementary material, Appendix 2 of the paper. Further details about these files and model can be found in the article.
Any question can be adressed to andresvalenzuela.zoo@gmail.com
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TwitterThis data package is formatted as a Darwin Core Archive (DwC-A, event core). For more information on Darwin Core see https://www.tdwg.org/standards/dwc/. This Level 2 data package was derived from the Level 1 data package found here: https://pasta.lternet.edu/package/metadata/eml/edi/340/2, which was derived from the Level 0 data package found here: https://pasta.lternet.edu/package/metadata/eml/knb-lter-knz/87/8. The abstract below was extracted from the Level 0 data package and is included for context: Fishes were collected by habitat (pool or riffle) at 6 sites in the Kings Creek watershed with a single-pass electrofishing survey with one person operating the electrofisher and two people dipnetting. Collections were made seasonally.
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Genomic diversity is a fundamental component of Earth's total biodiversity and requires explicit consideration in efforts to conserve biodiversity. To conserve genomic diversity, it is necessary to measure its spatial distribution and quantify the contribution that any intraspecific evolutionary lineages make to overall genomic diversity. Here, we describe the range-wide population genomic structure of a threatened Australian rodent, the black-footed tree-rat (Mesembriomys gouldii), aiming to provide insight into the timing and extent of population declines across a large region with a dearth of long-term monitoring data. By estimating recent trajectories in effective population sizes at four localities, we confirm widespread population decline across the species' range, but find that the population in the peri-urban area of the Darwin region has been more stable. Based on current sampling, the Melville Island population made the greatest contribution to overall allelic richness of the species, and the prioritisation analysis suggested that conservation of the Darwin and Cobourg Peninsula populations would be the most cost-effective scenario to retain more than 90% of all alleles. Our results broadly confirm current sub-specific taxonomy and provide crucial data on the spatial distribution of genomic diversity to help prioritise limited conservation resources. Along with additional sampling and genomic analysis from the far eastern and western edges of the black-footed tree-rat distribution, we suggest a range of conservation and research priorities that could help improve black-footed tree-rat population trajectories at large and fine spatial scales, including the retention and expansion of structurally complex habitat patches.
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TwitterABS Census data extract - G01 SELECTED PERSON CHARACTERISTICS BY SEX providing a breakdown of population at LGA 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.
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TwitterABS Census data extract - G08 ANCESTRY BY COUNTRY OF BIRTH OF PARENTS providing a breakdown of population at LGA 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.
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Context
The dataset tabulates the Darwin 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 Darwin 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 Darwin was 336, a 1.47% decrease year-by-year from 2022. Previously, in 2022, Darwin population was 341, a decline of 0% compared to a population of 341 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Darwin decreased by 27. In this period, the peak population was 391 in the year 2008. 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).
When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).
Data Coverage:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Darwin Population by Year. You can refer the same here