Housing Tenure and Costs - Seattle Neighborhoods

Table from the American Community Survey (ACS) 5-year series on housing tenure and cost related topics for City of Seattle Council Districts, Comprehensive Plan Growth Areas and Community Reporting Areas. Table includes B25003 Tenure of Occupied Housing Units, B25070 Gross Rent as a Percentage of Household Income in the Past 12 Months, B25063 Gross Rent, B25091 Mortgage Status by Selected Monthly Owner Costs as a Percentage of Household Income in the Past 12 Months, B25087 Mortgage Stauts and Selected Monthly Owner Costs, B25064 Median Gross Rent, B25088 Median Selected Monthly Owner Costs by Mortgage Status. Data is pulled from block group tables for the most recent ACS vintage and summarized to the neighborhoods based on block group assignment. Vintages: 2024 ACS Table(s): B25003, B25070, B25063, B25091, B25087, B25064, B25088 Data downloaded from: Census Bureau's Explore Census Data The United States Census Bureau's American Community Survey (ACS): About the Survey Geography & ACS Technical Documentation News & Updates This ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the Census and ACS when using this data. Data Note from the Census: Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables. Data Processing Notes: Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2020 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). The States layer contains 52 records - all US states, Washington D.C., and Puerto Rico Census tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99). Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey. Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page. Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations: The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate. Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution. The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate. The estimate is controlled. A statistical test for sampling variability is not appropriate. The data for this geographic area cannot be displayed because the number of sample cases is too small.本数据集表格源自美国社区调查（American Community Survey, ACS）5年系列数据，覆盖西雅图市议会选区、综合规划增长区及社区报告区域的住房保有状态与相关成本主题。本表格包含以下统计变量：B25003《已占用住房单元保有状态》、B25070《过去12个月总租金占家庭收入百分比》、B25063《总租金》、B25091《按选定月度房主成本划分的抵押状态（过去12个月家庭收入占比）》、B25087《抵押状态与选定月度房主成本》、B25064《总租金中位数》、B25088《按抵押状态划分的选定月度房主成本中位数》。 数据取自最新版ACS的街区组（block group）表格，并依据街区组分配规则汇总至各社区区域。数据年份：2024年ACS；涉及统计表格：B25003、B25070、B25063、B25091、B25087、B25064、B25088。数据下载自美国人口普查局Explore Census Data平台。 美国人口普查局美国社区调查（ACS）：相关说明包含调查概况、地理信息、ACS技术文档与新闻更新。 本即用型图层可在ArcGIS Pro、ArcGIS Online及其可配置应用、仪表盘、故事地图（Story Maps）、自定义应用与移动应用中使用，也可导出用于离线工作流程。使用本数据时请标注引用美国人口普查局与ACS相关成果。 ### 普查局数据说明 本数据基于抽样调查，存在抽样变异性。抽样变异性带来的估计值不确定性以误差边际（margin of error）体现，此处展示的为90%置信水平的误差边际。误差边际可理解为：估计值减去误差边际与估计值加上误差边际所构成的区间（即置信上下限）有90%的概率包含真实值。除抽样变异性外，ACS估计值还存在非抽样误差（关于非抽样变异性的讨论详见《数据精度》文档），本表格未体现非抽样误差的影响。 ### 数据处理说明 边界数据源自美国人口普查局TIGER地理数据库，具体为国家次州地理数据库（命名格式为`tlgdb_(年份)_a_us_substategeo.gdb`）。边界随数据更新同步更新（每年一次），且边界年份与普查局指定的数据年份完全匹配。为满足制图与地图绘制需求，本数据已移除普查边界中的水体与海岸线。对于普查街区组，水体裁剪源自TIGER提供的2020年区域水文边界子集：面积≥5000万平方米的大中型水体与河流，以及其他重要地物，均已从街区组边界中移除。对于州与县级边界，水体与海岸线源自2020年500k分辨率TIGER制图边界形状文件的海岸线信息，移除操作旨在更精准地呈现海岸线与五大湖区域。数据表格中仍保留原始的`AWATER`与`ALAND`字段，单位为平方米。本州图层包含52条记录，涵盖美国所有州、华盛顿哥伦比亚特区与波多黎各。本数据服务已移除无人口的水域区域普查街区组（即以99开头的街区组）。 百分比、衍生计数及相关误差边际均为计算所得值，字段名带有`_calc_`前缀，符合美国社区调查的规范要求。字段别名基于美国社区调查汇总文件文档页面提供的表格框架文件生成。 除`-5555…`已被置零外，其余负值（如`-4444…`）均已设为空值。这些负值在原始API数据中用于标识以下场景： 1. 误差边际列显示：无可用抽样观测值或抽样观测值过少，无法计算标准误及误差边际，不适宜进行统计检验； 2. 无可用抽样观测值或抽样观测值过少，无法计算估计值，或因中位数估计值落在开放式分布的最低区间或最高区间，无法计算中位数比值； 3. 中位数落在开放式分布的最低区间或最高区间； 4. 不适宜进行统计检验； 5. 估计值受控制； 6. 不适宜进行抽样变异性统计检验； 7. 因抽样案例数量过少，无法展示该地理区域的数据。