python:分离出 Pandas 数据框中重复的行

Question

假设一个数据框 df 有三列 c1, c2, c3。

df=pd.DataFrame()
df['c1']=[1,2,3,3,4]
df['c2']=["a1","a2","a2","a2","a1"]
df['c3']=[1,2,3,3,5]
print df
df1=df[df.duplicated()]
print df1

df1只有一行，也就是

    c1  c2  c3
3   3  a2   3

但我想拥有

    c1  c2  c3
2   3  a2   3
3   3  a2   3

如何获得？还有一件事，如果我尝试将参数“keep”用作df1 = df[df.duplicated(keep=False)]，它会给我错误

 Traceback (most recent call last):

 File "<ipython-input-572-188a22102b3e>", line 1, in <module>
 df1 = df[df.duplicated(keep=False)]

 File "C:\Users\Kanika\Anaconda\lib\site-packages\pandas\util\decorators.py", line 88, in wrapper
  return func(*args, **kwargs)

TypeError: duplicated() got an unexpected keyword argument 'keep'

Answer 1

您为 keep 指定的值是多少。我认为，在您的情况下，传递 False 作为保留值可能会解决问题。 Pandas Duplicated Doc's .希望对您有所帮助。

df1 = df[df.duplicated(keep=False)]