2023 Census totals by topic for dwellings by SA1

The variables included in this dataset are for occupied private dwellings (unless otherwise stated). All data is for level 1 of the classification (unless otherwise stated): Access to basic amenities (total responses) Dwelling dampness Dwelling mould Dwelling occupancy status for all dwellings for levels 1 and 2 Dwelling type for occupied dwellings for levels 1 and 2 Fuel types used to heat dwellings (total responses) Main types of heating used (total responses) Number of bedrooms Average number of bedrooms Number of rooms Average number of rooms. Download lookup file from Stats NZ ArcGIS Online or Stats NZ geographic data service. Footnotes 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. 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). 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. 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. 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. 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”. 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. 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. Percentages To calculate percentages, divide the figure for the category of interest by the figure for 'Total stated' where this applies. Symbol -999 Confidential Inconsistencies in definitions Please note that there may be differences in definitions between census classifications and those used for other data collections.本数据集包含的变量均针对已入住的私人住宅（另有说明者除外）。所有数据均采用分类级别1（另有说明者除外）：基本设施可及性（总有效回复数）、住宅潮湿情况、住宅发霉情况、所有住宅的居住状况（分类级别1和2）、已入住住宅的类型（分类级别1和2）、住宅供暖所用燃料类型（总有效回复数）、主要供暖方式（总有效回复数）、卧室数量、平均卧室数量、房间总数、平均房间数量。 可从新西兰统计局（Stats NZ）ArcGIS在线平台（ArcGIS Online）或新西兰统计局地理数据服务下载查找表文件。 ## 脚注 ### 地理边界 2023年地理区域统计标准（2023年12月更新）包含2023年1月1日起施行的地理边界相关信息。2013年与2018年人口普查的地址数据已更新，以适配2023年的区域划分。由于区域边界与编码方法的调整，2023年发布的2013年与2018年统计计数，可能与2013年或2018年当年发布的结果存在细微差异。 ### 时序数据使用提示 由于人口普查方法的变更及各次普查间回复率的差异，使用时序数据时需谨慎解读。2023年与2018年人口普查采用混合普查方法（结合普查回复与行政数据），而2013年人口普查采用全现场枚举法（未使用行政数据）。 ### 2023年人口普查数据集说明 如需了解2023年数据集的详细信息，请参阅《2023年人口普查混合普查模型应用》。本数据集将普查表单数据与行政数据相结合，符合新西兰统计局（Stats NZ）人口结构信息的质量标准。针对未填写普查表单的群体（即采用行政枚举法），在确认其身份后，我们将其真实人口数据纳入数据集。此外，我们还结合2018年与2013年人口普查数据、行政数据源及统计插补方法，填补了部分人口与住宅特征的缺失值。 ### 数据质量 2023年人口普查的数据质量通过质量评级量表与质量保证框架进行评估，以确定数据是否符合使用要求并适合对外发布。更多信息可参阅《2023年人口普查数据质量保证》。 ### 概念说明与质量评级 《2023年人口普查变量数据质量评级》一文提供了各主题分类下变量的更多细节，例如定义与数据质量情况。 ### 数据使用规范 新西兰统计局（Stats NZ）期望使用者以积极正向的目的使用普查数据，符合《毛利数据治理模型》（Data Iwi Leaders Group, 2023）中的相关要求。该模型指出："数据应助力变革性成果的实现，强化彼此间及与环境间的关系。避免数据造成伤害是数据使用的最低要求。毛利数据还应助力部落（iwi）与次部落（hapū）实现自治（tino rangatiratanga）"。 ### 保密条款 2023年人口普查保密规则已应用于2013年、2018年及2023年的数据集。这些规则旨在保护2023年人口普查数据中个人、家庭、住户、住宅及经营主体的隐私。当表格涉及多个地理变量或小样本群体时，统计计数采用固定随机舍入至3的倍数（FRR3）方法计算，并对计数小于6的"敏感"数据进行屏蔽。单个分项的合计值可能与总计数不完全一致。更多关于2023年人口普查保密规则的信息，请参阅《2023年人口普查保密规则应用及2018、2013年人口普查以来的变更概要》。 ### 统计量计算说明 均值、中位数及其他分位数等统计量均基于未舍入的计数计算得出，且在计算过程中会为每个参与计算的数值添加或减去输入噪声。基于不足6个样本（如个人、住宅、住户、家庭或扩展家庭）计算的均值与中位数将被屏蔽。该屏蔽阈值会根据其他分位数的情况进行调整。被屏蔽的单元格将使用占位符值填充。 ### 百分比计算说明 如需计算百分比，请将目标分类的数值除以适用的"已明确回复总计"数值。 ### 符号说明 -999：机密数据 ### 定义不一致提示 请注意，人口普查分类体系中的定义可能与其他数据采集所用的定义存在差异。