[英]How to drop duplicates based on two or more subsets criteria in Pandas data-frame
Lets say this is my data-frame可以说这是我的数据框
df = pd.DataFrame({ 'bio' : ['1', '1', '1', '4'],
'center' : ['one', 'one', 'two', 'three'],
'outcome' : ['f','t','f','f'] })
It looks like this...看起来像这样...
bio center outcome
0 1 one f
1 1 one t
2 1 two f
3 4 three f
I want to drop row 1 because it has the same bio & center as row 0. I want to keep row 2 because it has the same bio but different center then row 0.我想删除第 1 行,因为它与第 0 行具有相同的生物和中心。我想保留第 2 行,因为它与第 0 行具有相同的生物但不同的中心。
Something like this won't work based on drop_duplicates input structure but it's what I am trying to do像这样的东西不会基于 drop_duplicates 输入结构工作,但这是我想要做的
df.drop_duplicates(subset = 'bio' & subset = 'center' )
Any suggestions?有什么建议么?
edit: changed df a bit to fit example by correct answer编辑:改变 df 以适应正确答案的例子
Your syntax is wrong.你的语法是错误的。 Here's the correct way:这是正确的方法:
df.drop_duplicates(subset=['bio', 'center', 'outcome'])
Or in this specific case, just simply:或者在这种特定情况下,只需简单地:
df.drop_duplicates()
Both return the following:两者都返回以下内容:
bio center outcome
0 1 one f
2 1 two f
3 4 three f
Take a look at the df.drop_duplicates
documentation for syntax details.查看df.drop_duplicates
文档了解语法细节。 subset
should be a sequence of column labels. subset
应该是一系列列标签。
The previous Answer was very helpful.上一个答案非常有帮助。 It helped me.它帮助了我。 I also needed to add something in code to get what I wanted.我还需要在代码中添加一些东西来获得我想要的东西。 So, I wanted to add here that.所以,我想在这里补充一下。
The data-frame:数据框:
bio center outcome
0 1 one f
1 1 one t
2 1 two f
3 4 three f
After implementing drop_duplicates
:实施drop_duplicates
后:
bio center outcome
0 1 one f
2 1 two f
3 4 three f
Notice at the index.注意索引。 They got messed up.他们搞砸了。 If anyone wants to back the normal indexes ie 0, 1, 2
from 0, 2, 3
:如果有人想从0, 2, 3
支持正常索引,即0, 1, 2
:
df.drop_duplicates(subset=['bio', 'center', 'outcome'], ignore_index=True)
Output: Output:
bio center outcome
0 1 one f
1 1 two f
2 4 three f
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