python – 将两个DataFrames合并为一些相等的列

1.csv

id,noteId,text
id2,idNote19,This is my old text 2
id5,idNote13,This is my old text 5
id1,idNote12,This is my old text 1
id3,idNote10,This is my old text 3
id4,idNote11,This is my old text 4

2.csv

id,noteId,text,other
id3,idNote10,new text 3,On1
id2,idNote19,My new text 2,Pre8

装载他们像：

>>> df1 = pd.read_csv('1.csv', encoding='utf-8').set_index('id')
>>> df2 = pd.read_csv('2.csv', encoding='utf-8').set_index('id')
>>>
>>> print df1
       noteId                   text
id
id2  idNote19  This is my old text 2
id5  idNote13  This is my old text 5
id1  idNote12  This is my old text 1
id3  idNote10  This is my old text 3
id4  idNote11  This is my old text 4
>>> print df2
        noteId            text other
id
id3   idNote10      new text 3   On1
id2   idNote19   My new text 2  Pre8
id5        NaN   My new text 2   Hl0
id22  idNote22  My new text 22    M1

我需要在这样的东西中合并两个DataFrames(df1上的ovewriting值在df2上为空,添加额外的列和df1上不存在的行)：

        noteId                   text other
id
id2   idNote19          My new text 2  Pre8
id5        NaN          My new text 2   Hl0
id1   idNote12  This is my old text 1   NaN
id3   idNote10             new text 3   On1
id4   idNote11  This is my old text 4   NaN
id22  idNote22         My new text 22    M1

我真正的DataFrames还有其他列也应该合并,而不仅仅是文本

我尝试使用合并得到类似的东西：

>>> df1 = pd.read_csv('1.csv', encoding='utf-8')
>>> df2 = pd.read_csv('2.csv', encoding='utf-8')
>>>
>>> print df1
    id    noteId                   text
0  id2  idNote19  This is my old text 2
1  id5  idNote13  This is my old text 5
2  id1  idNote12  This is my old text 1
3  id3  idNote10  This is my old text 3
4  id4  idNote11  This is my old text 4
>>> print df2
    id    noteId           text
0  id3  idNote10     new text 3
1  id2  idNote19  My new text 2
>>>
>>> print merge(df1, df2, how='left', on=['id'])
    id  noteId_x                 text_x  noteId_y         text_y
0  id2  idNote19  This is my old text 2  idNote19  My new text 2
1  id5  idNote13  This is my old text 5       NaN            NaN
2  id1  idNote12  This is my old text 1       NaN            NaN
3  id3  idNote10  This is my old text 3  idNote10     new text 3
4  id4  idNote11  This is my old text 4       NaN            NaN
>>>

但这不是我需要的.我不知道我是否在正确的道路上并且应该合并后缀列,或者是否有更好的方法来执行此操作.

谢谢！

更新：
在df1上添加了对df2为空的ovewriting值,在df2上添加了额外的列,这些列应该在“merge”之后存在于df1上,而应该在df1上添加的行

–

解

根据@ U2EF1(谢谢！)评论,我找到了解决方案：

df1.fillna(value='None', inplace=True)
df2.fillna(value='None', inplace=True)

concat([df1, df2]).groupby('id').last().fillna(value='None')

在我的情况下,定义默认的“空”值非常重要,这就是fillna的原因.

解决方法:

通常你可以用适当的索引解决这个问题：

df1.set_index(['id', 'noteId'], inplace=True)
df1.update(df2)

(如果你之后不想要那个索引,只需要df1.reset_index(inplace = True))

python – 将两个DataFrames合并为一些相等的列

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