从仅某些列具有相同值的Pandas数据框中删除重复的行 [英] Remove duplicate rows from Pandas dataframe where only some columns have the same value

问题描述

我有一个熊猫数据框，如下所示:

I have a pandas dataframe as follows:

A   B   C
1   2   x
1   2   y
3   4   z
3   5   x

我希望在特定列中共享相同值的行中仅保留1行.在上面的示例中，我的意思是列 A 和 B .换句话说，如果列 A 和 B 的值在数据帧中出现多次，则仅应保留一行(无关紧要).

I want that only 1 row remains of rows that share the same values in specific columns. In the example above I mean columns A and B. In other words, if the values of columns A and B occur more than once in the dataframe, only one row should remain (which one does not matter).

FWIW:所谓的重复行(即列 A 和 B 相同的地方)的最大数目为2.

FWIW: the maximum number of so called duplicate rows (that is, where column A and B are the same) is 2.

结果应如下所示:

A   B   C
1   2   x
3   4   z
3   5   x

或

A   B   C
1   2   y
3   4   z
3   5   x

推荐答案

使用subset的="noreferrer"> drop_duplicates ，仅保留最后重复的行，请添加keep='last':

Use drop_duplicates with parameter subset, for keeping only last duplicated rows add keep='last':

df1 = df.drop_duplicates(subset=['A','B'])
#same as
#df1 = df.drop_duplicates(subset=['A','B'], keep='first')
print (df1)
   A  B  C
0  1  2  x
2  3  4  z
3  3  5  x

---

df2 = df.drop_duplicates(subset=['A','B'], keep='last')
print (df2)
   A  B  C
1  1  2  y
2  3  4  z
3  3  5  x

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