U.S. Select Demographics by Census Block Groups

Overview This dataset re-shares cartographic and demographic data from the U.S. Census Bureau to provide an obvious supplement to Open Environments Block Group publications.These results do not reflect any proprietary or predictive model. Rather, they extract from Census Bureau results with some proportions and aggregation rules applied. For additional support or more detail, please see the Census Bureau citations below. Cartographics refer to shapefiles shared in the Census TIGER/Line publications. Block Group areas are updated annually, with major revisions accompanying the Decennial Census at the turn of each decade. These shapes are useful for visualizing estimates as a map and relating geographies based upon geo-operations like overlapping. This data is kept in a geodatabase file format and requires the geopandas package and its supporting fiona and DAL software. Demographics are taken from popular variables in the American Community Survey (ACS) including age, race, income, education and family structure. This data simply requires csv reader software or pythons pandas package. While the demographic data has many columns, the cartographic data has a very, very large column called "geometry" storing the many-point boundaries of each shape. So, this process saves the data separately, with demographics columns in a csv file and geometry in a gpd file needed an installation of geopandas, fiona and DAL software. More details on the ACS variables selected and derivation rules applied can be found in the commentary docstrings in the source code found here: https://github.com/OpenEnvironments/blockgroupdemographics. ## Files While the demographic data has many columns, the cartographic data has a very, very large column called "geometry" storing the many-point boundaries of each shape. So, this process saves the data separately, with demographics columns in a csv file named YYYYblcokgroupdemographics.csv. The cartographic column, 'geometry', is shared as file named YYYYblockgroupdemographics-geometry.pkl. This file needs an installation of geopandas, fiona and DAL software.

### 数据集概述
本数据集重新分享美国人口普查局（U.S. Census Bureau）的制图与人口统计数据，作为Open Environments街区组（Block Group）出版物的明确补充。本数据集的结果未涉及任何专有或预测模型，仅基于比例与聚合规则从人口普查局的公开数据中提取生成。如需额外支持或更多细节，请参阅下文引用的人口普查局相关资料。

制图数据指美国人口普查局TIGER/Line出版物中共享的形状文件（shapefile）。街区组（Block Group）区域每年更新一次，每十年一度的十年一次人口普查（Decennial Census）节点会进行重大修订。此类形状文件可用于将估算结果以地图形式可视化，也可基于重叠等地理空间操作实现地理区域的关联分析。该数据采用地理数据库文件格式存储，需使用geopandas库及其依赖的fiona与DAL软件进行读取。

人口统计数据取自美国社区调查（American Community Survey, ACS）中的常用变量，涵盖年龄、种族、收入、教育程度与家庭结构等维度。该数据仅需CSV读取软件或Python的pandas库即可处理。尽管人口统计数据包含较多字段，但制图数据存在一个体量极大的"geometry"字段，用于存储各形状的多点边界。因此本数据集将两类数据分开存储：人口统计字段保存于名为YYYYblockgroupdemographics.csv的CSV文件中，而"geometry"字段则保存于gpd格式文件中，读取该文件需安装geopandas、fiona与DAL软件。

关于所选ACS变量及衍生规则的更多细节，可参阅本项目源代码中的注释文档字符串，项目地址为：https://github.com/OpenEnvironments/blockgroupdemographics。

### 文件说明
尽管人口统计数据包含较多字段，但制图数据存在一个体量极大的"geometry"字段，用于存储各形状的多点边界。因此本数据集将两类数据分开存储：人口统计字段保存于名为YYYYblockgroupdemographics.csv的CSV文件中；而"geometry"制图字段则保存于名为YYYYblockgroupdemographics-geometry.pkl的文件中，读取该文件需安装geopandas、fiona与DAL软件。