选择所有重复行的解决方案:

Solutions for select all duplicated rows:

您可以使用 duplicated 带有子集和参数keep=False的元素，用于选择所有重复项:

You can use duplicated with subset and parameter keep=False for select all duplicates:

df = df[df.duplicated(subset=['A','B'], keep=False)]
print (df)
     A  B  C
1  foo  1  A
2  foo  1  B

使用 transform :

df = df[df.groupby(['A', 'B'])['A'].transform('size') > 1]
print (df)
     A  B  C
1  foo  1  A
2  foo  1  B

对所有唯一行进行了一些修改的解决方案:

A bit modified solutions for select all unique rows:

#invert boolean mask by ~
df = df[~df.duplicated(subset=['A','B'], keep=False)]
print (df)
     A  B  C
0  foo  0  A
3  bar  1  A

df = df[df.groupby(['A', 'B'])['A'].transform('size') == 1]
print (df)
     A  B  C
0  foo  0  A
3  bar  1  A