如何有效地使用字典式或其他方法来清理数据

问题描述

我正在处理具有大量部门代码的数据集。我还有其他文章可以对部门进行解码,那里是合并或替换的有效方法。

第一个数据集:

Location        DeptCode
Delhi           12B
Gurgoun         12D 
Hydrabad        13A 
Punjab          20A
Jhansi          31B

Below is the code: 
Department        DeptCode
Electronics       [12A,12B,12C,12D,12E ........12Z]
Electronics       [13A,13B,.......13Z]
Grocery           20A
Grocery           [31A,31B,31C,.........31Z]

预期:

Department        DeptCode     Location
Electronics       12B          Delhi
Electronics       12D          Gurgoun
Electronics       13A          Hydrabad
Grocery           20A          Punjab
Grocery           31B          Jhansi          

解决方法

让我们先尝试explode然后尝试merge

Out = df1.merge(df2.explode('DeptCode'),on='Deptcode',how='left')

相关问答

错误1:Request method ‘DELETE‘ not supported 错误还原:...
错误1:启动docker镜像时报错:Error response from daemon:...
错误1:private field ‘xxx‘ is never assigned 按Alt...
报错如下,通过源不能下载,最后警告pip需升级版本 Requirem...