从 Pandas 数据框中删除重复的行,其中只有某些列具有相同的值 [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
我希望只剩下 1 行在特定列中共享相同值的行.在上面的例子中,我指的是 A 和 B 列.换句话说,如果 A 和 B 列的值在数据框中出现多次,则只应保留一行(哪一行无关紧要).
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:所谓重复行的最大数量(即 A 和 B 列相同)是 2.
FWIW: the maximum number of so called duplicate rows (that is, where column A and B are the same) is 2.
结果应该是这样的:
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 drop_duplicates
带有参数 subset
,用于仅保留最后重复的行添加 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
<小时>
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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