根据特定条件在pandas中添加新行？蟒蛇

Question

如果isinstance（x，list）为True，是否可以使用pd.apply（）添加新行 那么，例如，我可以将idx 57分成同一数据帧中的三个不同的行吗？

目前：

56    the University of Notre Dame
57    [Berkeley, Columbia Business School, Haas]

所需：

56    the University of Notre Dame
57    Berkeley
58    Columbia B School
59    Haas  


AttributeError                            Traceback (most recent call last)
<ipython-input-1121-0cd6253a0f30> in <module>()
     15 s = pd.Series(["the University of Notre Dame", ["Berkeley", "Columbia Business School", "Haas"]])
     16 
---> 17 s.apply(lambda x : pd.Series(x)).stack().reset_index(drop=True)

AttributeError: 'Series' object has no attribute 'stack'

Answer 1

这样的东西？

In [106]: s = pd.Series(["the University of Notre Dame", ["Berkeley", "Columbia Business School", "Haas"]])

In [107]: s
Out[107]: 
0                  the University of Notre Dame
1    [Berkeley, Columbia Business School, Haas]
dtype: object

In [110]: s.apply(pd.Series).stack().reset_index(drop=True)
Out[110]: 
0    the University of Notre Dame
1                        Berkeley
2        Columbia Business School
3                            Haas
dtype: object