应一位园子里的朋友的要求,发一下这个数据,所有数据都是本人自己在网上找的,然后整理了一下:
这套数据共包括:
- 省份34个(包括港澳台地区);
- 城市345个(每个城市包括一个可通用的邮政编码);
- 城市对应的地区2862个(这个地区只的是城市中的小的区,比如:北京的海淀区).
SQL版:
SQL脚本下载:点击下载
运行脚本时候将第一行的 USE [DBCT_Dev] 中的 DBCT_Dev 改为要插入数据的数据库名,还可以修改各个表名,默认的表名为:省份[S_Province],城市[S_City],地区[S_District].
XML版:
其实该版本是由上面的数据生成的,不过为了大家的方便也单独放出来,下面的例子数据不全,完整数据XML文件见下方的文件下载:
省份数据:
![](https://www.cnblogs.com/Images/OutliningIndicators/None.gif)
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![](https://www.cnblogs.com/Images/dot.gif)
城市数据:
![](https://www.cnblogs.com/Images/OutliningIndicators/None.gif)
![](https://www.cnblogs.com/Images/OutliningIndicators/None.gif)
![](https://www.cnblogs.com/Images/OutliningIndicators/None.gif)
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地区数据:
![](https://www.cnblogs.com/Images/OutliningIndicators/None.gif)
![](https://www.cnblogs.com/Images/OutliningIndicators/None.gif)
![](https://www.cnblogs.com/Images/OutliningIndicators/None.gif)
![](https://www.cnblogs.com/Images/OutliningIndicators/None.gif)
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![](https://www.cnblogs.com/Images/OutliningIndicators/None.gif)
![](https://www.cnblogs.com/Images/OutliningIndicators/None.gif)
![](https://www.cnblogs.com/Images/dot.gif)
完整数据下载:点击下载