five

UNI-CEN Standardized Census Data Table - Census Division (CD) - 2011 - Wide Format (DBF) (Version 2023-03)

收藏
Mendeley Data2024-01-31 更新2024-06-27 收录
下载链接:
https://borealisdata.ca/citation?persistentId=doi:10.5683/SP3/HFFSLZ
下载链接
链接失效反馈
官方服务:
资源简介:
UNI-CEN Standardized Census Data Tables contain Census data that have been reformatted into a common table format with standardized variable names and codes. The data are provided in two tabular formats for different use cases. "Long" tables are suitable for use in statistical environments, while "wide" tables are commonly used in GIS environments. The long tables are provided in Stata Binary (dta) format, which is readable by all statistics software. The wide tables are provided in comma-separated values (csv) and dBase 3 (dbf) formats with codebooks. The wide tables are easily joined to the UNI-CEN Digital Boundary Files. For the csv files, a .csvt file is provided to ensure that column data formats are correctly formatted when importing into QGIS. A schema.ini file does the same when importing into ArcGIS environments. As the DBF file format supports a maximum of 250 columns, tables with a larger number of variables are divided into multiple DBF files. For more information about file sources, the methods used to create them, and how to use them, consult the documentation at https://borealisdata.ca/dataverse/unicen_docs. For more information about the project, visit https://observatory.uwo.ca/unicen.

UNI-CEN标准化普查数据表(UNI-CEN Standardized Census Data Tables)收录经重新格式化的普查数据,采用统一表格格式,并配备标准化变量名称与编码。该数据集针对不同应用场景提供两种表格格式:‘长表’适配统计分析环境,‘宽表’则多用于地理信息系统(Geographic Information System,GIS)环境。长表采用Stata二进制(dta)格式,可被所有统计软件读取。宽表附带编码手册,提供逗号分隔值(csv)与dBase 3(dbf)两种格式。宽表可便捷地与UNI-CEN数字边界文件进行关联拼接。针对csv文件,配套提供.csvt文件,以确保在导入QGIS时列数据格式正确无误。若导入ArcGIS环境,则可通过schema.ini文件实现相同的格式校验功能。由于dbf格式最多仅支持250列,变量数量较多的表格会被拆分为多个dbf文件。如需了解文件来源、制作方法及使用方式等更多信息,请查阅以下文档:https://borealisdata.ca/dataverse/unicen_docs。如需了解该项目的更多详情,请访问:https://observatory.uwo.ca/unicen。
创建时间:
2024-01-31
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作