按多列分组以查找重复的行 pandas [英] Grouping by multiple columns to find duplicate rows pandas

问题描述

我有一个 df

id    val1    val2
 1     1.1      2.2
 1     1.1      2.2
 2     2.1      5.5
 3     8.8      6.2
 4     1.1      2.2
 5     8.8      6.2

我想按 val1 和 val2 进行分组，并仅获取具有相同 val1 和 val2 组合多次出现的行的相似数据帧.

I want to group by val1 and val2 and get similar dataframe only with rows which has multiple occurance of same val1 and val2 combination.

最终df:

id    val1    val2
 1     1.1      2.2
 4     1.1      2.2
 3     8.8      6.2
 5     8.8      6.2

推荐答案

您需要 duplicated 与参数 subset 用于指定列以 keep=False 检查所有重复的掩码和按布尔索引过滤:

You need duplicated with parameter subset for specify columns for check with keep=False for all duplicates for mask and filter by boolean indexing:

df = df[df.duplicated(subset=['val1','val2'], keep=False)]
print (df)
   id  val1  val2
0   1   1.1   2.2
1   1   1.1   2.2
3   3   8.8   6.2
4   4   1.1   2.2
5   5   8.8   6.2

详情:

print (df.duplicated(subset=['val1','val2'], keep=False))
0     True
1     True
2    False
3     True
4     True
5     True
dtype: bool

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