删除 Pandas 中的重复项，不包括一列
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Dropping duplicates in Pandas excluding one column
提问by Jstuff
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相关信息
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? The column not matching being Description.
如何消除与 5 列中的 4 列匹配的重复项？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_dupilcateswith the subsetparameter could work, but I am unsure of how I can apply it to multiple columns.
我在网上发现drop_dupilcates使用该subset参数可以工作，但我不确定如何将其应用于多列。
回答by ayhan
You've actually found the solution. For multiple columns, subset will be a list.
您实际上已经找到了解决方案。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']))
