Perform function on pairs of rows in Pandas dataframe

Question

Say I have the following dataframe:

>>> df=pd.DataFrame(data=['A','B','C','D','E'], columns=['Name'])
>>> df
  Name
0    A
1    B
2    C
3    D
4    E
>>> 

I want to create a list of values for adjacent rows in the dataframe. If I create an index of pairs I can get that result by using groupby:

>>> df.index=[0,0,1,1,2]
>>> df.groupby(level=0).agg(lambda x: list(x))
     Name
0  [A, B]
1  [C, D]
2     [E]

What is the most efficient way of doing this?

Answer 1

You can groupby by "adjacency" in one go (without mutating the DataFrame):

In [11]: g = df.groupby(df.index // 2)

and then do whatever it is you need to do:

In [12]: g.get_group(0)
Out[12]:
  Name
0    A
1    B

In [13]: g.sum()
Out[13]:
  Name
0   AB
1   CD
2    E