Monthly data on federally administered Supplemental Security Income payments.

Annual mid-year population estimates for those aged 90 years and over by sex and single year of age (90 to 104 years), and the 105 years and over age group, UK.

CGO: Financing: ytd data was reported at -28,653.000 KRW bn in Oct 2018. This records a decrease from the previous number of -14,031.000 KRW bn for Sep 2018. CGO: Financing: ytd data is updated monthly, averaging -6,754.000 KRW bn from Jun 1999 (Median) to Oct 2018, with 233 observations. The data reached an all-time high of 28,619.000 KRW bn in Jun 2013 and a record low of -42,915.000 KRW bn in Nov 2007. CGO: Financing: ytd data remains active status in CEIC and is reported by Ministry of Strategy and Finance. The data is categorized under Global Database’s South Korea – Table KR.F001: Consolidated Central Government Statistics.

2018-2023 Statistics on the work of the Legal Department

Dataset contains counts and measures for individuals from the 2013, 2018, and 2023 Censuses. Data is available by statistical area 2.

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The variables included in this dataset are for the census usually resident population count (unless otherwise stated). All data is for level 1 of the classification (unless otherwise stated).

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The variables for part 1 of the dataset are:

• Census usually resident population count
• Census night population count
• Age (5-year groups)
• Age (life cycle groups)
• Median age
• Birthplace (NZ born/overseas born)
• Birthplace (broad geographic areas)
• Ethnicity (total responses) for level 1 and ‘Other Ethnicity’ grouped by ‘New Zealander’ and ‘Other Ethnicity nec’
• Māori descent indicator
• Languages spoken (total responses)
• Official language indicator
• Gender
• Cisgender and transgender status – census usually resident population count aged 15 years and over
• Sex at birth
• Rainbow/LGBTIQ+ indicator for the census usually resident population count aged 15 years and over
• Sexual identity for the census usually resident population count aged 15 years and over
• Legally registered relationship status for the census usually resident population count aged 15 years and over
• Partnership status in current relationship for the census usually resident population count aged 15 years and over
• Number of children born for the sex at birth female census usually resident population count aged 15 years and over
• Average number of children born for the sex at birth female census usually resident population count aged 15 years and over
• Religious affiliation (total responses)
• Cigarette smoking behaviour for the census usually resident population count aged 15 years and over
• Disability indicator for the census usually resident population count aged 5 years and over
• Difficulty communicating for the census usually resident population count aged 5 years and over
• Difficulty hearing for the census usually resident population count aged 5 years and over
• Difficulty remembering or concentrating for the census usually resident population count aged 5 years and over
• Difficulty seeing for the census usually resident population count aged 5 years and over
• Difficulty walking for the census usually resident population count aged 5 years and over
• Difficulty washing for the census usually resident population count aged 5 years and over.

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Download lookup file for part 1 from Stats NZ ArcGIS Online or embedded attachment in Stats NZ geographic data service. Download data table (excluding the geometry column for CSV files) using the instructions in the Koordinates help guide.

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Footnotes

Te Whata

Under the Mana Ōrite Relationship Agreement, Te Kāhui Raraunga (TKR) will be publishing Māori descent and iwi affiliation data from the 2023 Census in partnership with Stats NZ. This will be available on Te Whata, a TKR platform.

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Geographical boundaries

Statistical standard for geographic areas 2023 (updated December 2023) has information about geographic boundaries as of 1 January 2023. Address data from 2013 and 2018 Censuses was updated to be consistent with the 2023 areas. Due to the changes in area boundaries and coding methodologies, 2013 and 2018 counts published in 2023 may be slightly different to those published in 2013 or 2018.

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Subnational census usually resident population

The census usually resident population count of an area (subnational count) is a count of all people who usually live in that area and were present in New Zealand on census night. It excludes visitors from overseas, visitors from elsewhere in New Zealand, and residents temporarily overseas on census night. For example, a person who usually lives in Christchurch city and is visiting Wellington city on census night will be included in the census usually resident population count of Christchurch city.

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Population counts

Stats NZ publishes a number of different population counts, each using a different definition and methodology. Population statistics – user guide has more information about different counts.

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Caution using time series

Time series data should be interpreted with care due to changes in census methodology and differences in response rates between censuses. The 2023 and 2018 Censuses used a combined census methodology (using census responses and administrative data), while the 2013 Census used a full-field enumeration methodology (with no use of administrative data).

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Study participation time series

In the 2013 Census study participation was only collected for the census usually resident population count aged 15 years and over.

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About the 2023 Census dataset

For information on the 2023 dataset see Using a combined census model for the 2023 Census. We combined data from the census forms with administrative data to create the 2023 Census dataset, which meets Stats NZ's quality criteria for population structure information. We added real data about real people to the dataset where we were confident the people who hadn’t completed a census form (which is known as admin enumeration) will be counted. We also used data from the 2018 and 2013 Censuses, administrative data sources, and statistical imputation methods to fill in some missing characteristics of people and dwellings.

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Data quality

The quality of data in the 2023 Census is assessed using the quality rating scale and the quality assurance framework to determine whether data is fit for purpose and suitable for release. Data quality assurance in the 2023 Census has more information.

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Concept descriptions and quality ratings

Data quality ratings for 2023 Census variables has additional details about variables found within totals by topic, for example, definitions and data quality.

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Disability indicator

This data should not be used as an official measure of disability prevalence. Disability prevalence estimates are only available from the 2023 Household Disability Survey. Household Disability Survey 2023: Final content has more information about the survey.

Activity limitations are measured using the Washington Group Short Set (WGSS). The WGSS asks about six basic activities that a person might have difficulty with: seeing, hearing, walking or climbing stairs, remembering or concentrating, washing all over or dressing, and communicating. A person was classified as disabled in the 2023 Census if there was at least one of these activities that they had a lot of difficulty with or could not do at all.

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Using data for good

Stats NZ expects that, when working with census data, it is done so with a positive purpose, as outlined in the Māori Data Governance Model (Data Iwi Leaders Group, 2023). This model states that "data should support transformative outcomes and should uplift and strengthen our relationships with each other and with our environments. The avoidance of harm is the minimum expectation for data use. Māori data should also contribute to iwi and hapū tino rangatiratanga”.

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Confidentiality

The 2023 Census confidentiality rules have been applied to 2013, 2018, and 2023 data. These rules protect the confidentiality of individuals, families, households, dwellings, and undertakings in 2023 Census data. Counts are calculated using fixed random rounding to base 3 (FRR3) and suppression of ‘sensitive’ counts less than six, where tables report multiple geographic variables and/or small populations. Individual figures may not always sum to stated totals. Applying confidentiality rules to 2023 Census data and summary of changes since 2018 and 2013 Censuses has more information about 2023 Census confidentiality rules.

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Measures

Measures like averages, medians, and other quantiles are calculated from unrounded counts, with input noise added to or subtracted from each contributing value during measures calculations. Averages and medians based on less than six units (e.g. individuals, dwellings, households, families, or extended families) are suppressed. This suppression threshold changes for other quantiles. Where the cells have been suppressed, a placeholder value has been used.

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Percentages

To calculate percentages, divide the figure for the category of interest by the figure for 'Total stated' where this applies.

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Symbol

-997 Not available

-999 Confidential

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Inconsistencies in definitions

Please note that there may be differences in definitions between census classifications and those used for other data collections.

This data set shows crude birth rate in Malaysia. The rates are per 1,000 population. More Info : https://www.statistics.gov.my

Characteristics of usual residents by whether they have previously served in the UK armed forces, with adjusted estimates for the non-veteran population, Census 2021.

Madagascar MG: Government Expenditure per Student: Primary: % of(GDP) Gross Domestic Productper Capita data was reported at 6.567 % in 2012. This records a decrease from the previous number of 6.611 % for 2011. Madagascar MG: Government Expenditure per Student: Primary: % of(GDP) Gross Domestic Productper Capita data is updated yearly, averaging 7.829 % from Dec 1998 (Median) to 2012, with 8 observations. The data reached an all-time high of 11.240 % in 2005 and a record low of 5.903 % in 1998. Madagascar MG: Government Expenditure per Student: Primary: % of(GDP) Gross Domestic Productper Capita data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Madagascar – Table MG.World Bank: Education Statistics. Government expenditure per student is the average general government expenditure (current, capital, and transfers) per student in the given level of education, expressed as a percentage of GDP per capita.; ; United Nations Educational, Scientific, and Cultural Organization (UNESCO) Institute for Statistics.; Median;

The new version of these data is in GPM-like format (consistent with the GPM Dual-frequency Radar data format), and can be found under the name GPM_3PR. This product consists of monthly statistics of the PR measurements at both a low (5 degrees x 5 degrees) and a high (0.5 degrees x 0.5 degrees) horizontal resolution. The low resolution grids are in the Planetary Grid 1 structure and include 1) mean and standard deviation of the rain rate, reflectivity, path-integrated attenuation (PIA), storm height, Xi, bright band height and the NUBF (Non-Uniform Beam Filling) correction; 2) rain fractions; 3) histograms of the storm height, bright-band height, snow-ice layer, reflectivity, rain rate, path-attenuation and NUBF correction; 4) correlation coefficients. The high resolution grids are in the Planetary Grid 2 structure and contain mean rain rate along with standard deviation and rain fractions.

The monthly resident population statistics by gender and age for each township and city in Changhua County.

Hydrographic and Impairment Statistics (HIS) is a National Park Service (NPS) Water Resources Division (WRD) project established to track certain goals created in response to the Government Performance and Results Act of 1993 (GPRA). One water resources management goal established by the Department of the Interior under GRPA requires NPS to track the percent of its managed surface waters that are meeting Clean Water Act (CWA) water quality standards. This goal requires an accurate inventory that spatially quantifies the surface water hydrography that each bureau manages and a procedure to determine and track which waterbodies are or are not meeting water quality standards as outlined by Section 303(d) of the CWA. This project helps meet this DOI GRPA goal by inventorying and monitoring in a geographic information system for the NPS: (1) CWA 303(d) quality impaired waters and causes; and (2) hydrographic statistics based on the United States Geological Survey (USGS) National Hydrography Dataset (NHD). Hydrographic and 303(d) impairment statistics were evaluated based on a combination of 1:24,000 (NHD) and finer scale data (frequently provided by state GIS layers).

Serbia RS: Government Expenditure per Student: Primary: % of(GDP) Gross Domestic Productper Capita data was reported at 46.554 % in 2015. This records a decrease from the previous number of 50.953 % for 2011. Serbia RS: Government Expenditure per Student: Primary: % of(GDP) Gross Domestic Productper Capita data is updated yearly, averaging 53.975 % from Dec 2007 (Median) to 2015, with 6 observations. The data reached an all-time high of 58.067 % in 2009 and a record low of 46.554 % in 2015. Serbia RS: Government Expenditure per Student: Primary: % of(GDP) Gross Domestic Productper Capita data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Serbia – Table RS.World Bank.WDI: Education Statistics. Government expenditure per student is the average general government expenditure (current, capital, and transfers) per student in the given level of education, expressed as a percentage of GDP per capita.; ; United Nations Educational, Scientific, and Cultural Organization (UNESCO) Institute for Statistics.; Median;

110 years of current demographic data provided by this collection

This dataset reflects is for the Individual Shelter & Rescue Statistics that were reported in 2018 for the 2017 Calendar year. Although PACFA requires this data to be submitted and takes all care possible to ensure the validity of this data, we do not control, and therefore guarantee, the complete accuracy, completeness and availability of data. PACFA believes this information to be within ± 4% margin of error. The CDA-PACFA is not responsible for any issues that may arise from the use of this data.

Ecuador EC: Government Expenditure per Student: Primary: % of(GDP) Gross Domestic Productper Capita data was reported at 9.352 % in 2016. This records an increase from the previous number of 8.963 % for 2015. Ecuador EC: Government Expenditure per Student: Primary: % of(GDP) Gross Domestic Productper Capita data is updated yearly, averaging 10.394 % from Dec 1999 (Median) to 2016, with 10 observations. The data reached an all-time high of 11.615 % in 2013 and a record low of 2.846 % in 2000. Ecuador EC: Government Expenditure per Student: Primary: % of(GDP) Gross Domestic Productper Capita data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ecuador – Table EC.World Bank.WDI: Education Statistics. Government expenditure per student is the average general government expenditure (current, capital, and transfers) per student in the given level of education, expressed as a percentage of GDP per capita.; ; United Nations Educational, Scientific, and Cultural Organization (UNESCO) Institute for Statistics.; Median;

In 2024, the gross government debt of China amounted to an estimated ** percent of the country's gross domestic product (GDP), compared to ** percent for Russia. For China, this was an increase over 2001 levels, when the gross government debt amounted to ** percent of the country's GDP. Russia, on the other hand, has reduced this figure from 2001 levels, when gross government debt was ** percent of the country's GDP.

This dataset contains the number of New York State live births stratified by the mother's race/ethnicity, and measure. Measures include attendant at birth, birthweight, how infant is fed, infant’s sex, marital status, method of delivery, mother’s age, mother’s education, pre-pregnancy BMI, order of birth, place of birth, plurality, prenatal care began, and primary financial coverage. The data presented here may not be the same as the Vital Statistics tables on the DOH public web due to data updates. For more information, check out: http://www.health.ny.gov/statistics/vital_Statistics/. The "About" tab contains additional details concerning this dataset.