Python 熊猫：使用其他列的迭代值添加新列

我有一个数据框，有两列——一列有单词，另一列有pos_标签

       word1  tag1
0        Why  WRB
1         is  VBZ
2       this   DT
3  happening   NN
4         to   TO
5         us  PRP
6    Asterix  NNP
7        and   CC
8     Obelix  NNP

如何再添加两列，其值为“word1”和“tag1”列的第（I+1）个值，以生成结果

       word1  tag1       word2   tag2
0        Why   WRB          is    VBZ
1         is   VBZ        this     DT
2       this    DT   happening    NNP
3  happening   NNP         to      TO
4         to    TO          us    PRP
5         us   PRP     Asterix    NNP
6    Asterix   NNP         and     CC
7        and    CC      Obelix    NNP
8     Obelix   NNP         nan    nan

---

通过调用并传递

-1

作为间隔来添加新列：

In [84]:

df['word2'], df['tag2'] = df['word1'].shift(-1), df['tag1'].shift(-1)
df
Out[84]:
       word1 tag1      word2 tag2
0        Why  WRB         is  VBZ
1         is  VBZ       this   DT
2       this   DT  happening   NN
3  happening   NN         to   TO
4         to   TO         us  PRP
5         us  PRP    Asterix  NNP
6    Asterix  NNP        and   CC
7        and   CC     Obelix  NNP
8     Obelix  NNP        NaN  NaN

---

通过调用并传递

-1

作为间隔来添加新列：

In [84]:

df['word2'], df['tag2'] = df['word1'].shift(-1), df['tag1'].shift(-1)
df
Out[84]:
       word1 tag1      word2 tag2
0        Why  WRB         is  VBZ
1         is  VBZ       this   DT
2       this   DT  happening   NN
3  happening   NN         to   TO
4         to   TO         us  PRP
5         us  PRP    Asterix  NNP
6    Asterix  NNP        and   CC
7        and   CC     Obelix  NNP
8     Obelix  NNP        NaN  NaN

在数据帧上使用shift（-1）

In [109]: df[['word2', 'tag2']] = df.shift(-1)

In [110]: df
Out[110]:
       word1 tag1      word2 tag2
0        Why  WRB         is  VBZ
1         is  VBZ       this   DT
2       this   DT  happening   NN
3  happening   NN         to   TO
4         to   TO         us  PRP
5         us  PRP    Asterix  NNP
6    Asterix  NNP        and   CC
7        and   CC     Obelix  NNP
8     Obelix  NNP        NaN  NaN

在数据帧上使用shift（-1）

In [109]: df[['word2', 'tag2']] = df.shift(-1)

In [110]: df
Out[110]:
       word1 tag1      word2 tag2
0        Why  WRB         is  VBZ
1         is  VBZ       this   DT
2       this   DT  happening   NN
3  happening   NN         to   TO
4         to   TO         us  PRP
5         us  PRP    Asterix  NNP
6    Asterix  NNP        and   CC
7        and   CC     Obelix  NNP
8     Obelix  NNP        NaN  NaN