How to perform windowed operation on dataframe?

Question

Given

import pandas as pd
import numpy as np

ssss = pd.DataFrame(np.arange(6))

ssss:

   0
0  0
1  1
2  2
3  3
4          


        

Answer 1

If windows are not overlapped you can use groupby.

I think you need GroupBy.transform with integer division:

#if default RangeIndex
ssss['res'] = ssss.groupby(ssss.index // 2)[0].transform('mean')
#any index - helper array
ssss['res'] = ssss.groupby(np.arange(len(ssss)) // 2)[0].transform('mean')
print (ssss)
   0  res
0  0  0.5
1  1  0.5
2  2  2.5
3  3  2.5
4  4  4.5
5  5  4.5

EDIT:

print (df)
   0  1  2
0  0  5  a
1  1  4  b
2  2  3  c
3  3  2  d
4  4  1  e
5  5  0  f

def row_reduce(col0, col1):
    return str(2 * col0) + str(col1)

def col_reduce(rows_data):
    return ",".join(rows_data)


df['res'] = (df.apply(lambda x: row_reduce(x[0], x[1]), axis=1)
               .groupby(df.index // 2)
               .transform(col_reduce))
print (df)
   0  1  2     res
0  0  5  a   05,24
1  1  4  b   05,24
2  2  3  c   43,62
3  3  2  d   43,62
4  4  1  e  81,100
5  5  0  f  81,100