获取多列的唯一值作为 Pandas 中的新数据框
声明：本页面是StackOverFlow热门问题的中英对照翻译，遵循CC BY-SA 4.0协议，如果您需要使用它，必须同样遵循CC BY-SA许可，注明原文地址和作者信息，同时你必须将它归于原作者（不是我）：StackOverFlow
原文地址: http://stackoverflow.com/questions/48131812/
Warning: these are provided under cc-by-sa 4.0 license. You are free to use/share it, But you must attribute it to the original authors (not me):
StackOverFlow
Get unique values of multiple columns as a new dataframe in pandas
提问by Ofek Ron
Having pandas data frame dfwith at least columns C1,C2,C3 how would you get all the unique C1,C2,C3 values as a new DataFrame?
拥有df至少包含 C1、C2、C3 列的 Pandas数据框，您如何将所有唯一的 C1、C2、C3 值作为新的 DataFrame 获取？
in other words, similiar to :
换句话说，类似于：
SELECT C1,C2,C3
FROM T
GROUP BY C1,C2,C3
Tried that
试过了
print df.groupby(by=['C1','C2','C3'])
but im getting
但我得到
<pandas.core.groupby.DataFrameGroupBy object at 0x000000000769A9E8>
回答by jezrael
I believe you need drop_duplicatesif want all unique triples:
我相信你需要drop_duplicates如果想要所有独特的三元组：
df = df.drop_duplicates(subset=['C1','C2','C3'])
If want use groupbyadd first:
如果要使用groupby添加first：
df = df.groupby(by=['C1','C2','C3'], as_index=False).first()
