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删除 Pandas 中的重复项,不包括一列

[英]Dropping duplicates in Pandas excluding one column

This seems simple, but I can not find any information on it on the internet.这看起来很简单,但我在互联网上找不到任何有关它的信息。

I have a dataframe like below:我有一个如下所示的数据框:

City    State Zip           Date        Description       
Earlham IA    50072-1036    2014-10-10  Postmarket Assurance: Devices
Earlham IA    50072-1036    2014-10-10  Compliance: Devices
Madrid  IA    50156-1748    2014-09-10  Drug Quality Assurance

How can I eliminate duplicates that match 4 of 5 columns?如何消除与 5 列中的 4 列匹配的重复项? The column not matching being Description .不匹配的列是Description

The result would be结果是

City    State Zip           Date        Description       
Earlham IA    50072-1036    2014-10-10  Postmarket Assurance: Devices
Madrid  IA    50156-1748    2014-09-10  Drug Quality Assurance

I found online that drop_duplicates with the subset parameter could work, but I am unsure of how I can apply it to multiple columns.我在网上发现带有subset参数的drop_duplicates可以工作,但我不确定如何将其应用于多列。

You've actually found the solution.您实际上已经找到了解决方案。 For multiple columns, subset will be a list.对于多列,子集将是一个列表。

df.drop_duplicates(subset=['City', 'State', 'Zip', 'Date']) 

Or, just by stating the column to be ignored:或者,只需说明要忽略的列:

df.drop_duplicates(subset=df.columns.difference(['Description']))

如何添加不同的多列,如 id 和 description?

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