How to find max value with shift and condition?

I have Dataframe like this:

Index A
0     3
1     2
2     5
3     4
4     1
5     2
6     7
7     3
8     1

And i need to go with the shift, taking 5 pieces and so that the maximum is in the center of them.

Result:

Index A   Res
0     3    0
1     2    0
2     5    5
3     4    0
4     1    0
5     2    0
6     7    7
7     3    0
8     1    0

How can i implement this using pandas methods?

>Solution :

You can use rolling with the center=True and step=5 parameters:

N = 5

df.loc[N//2::N, 'Res'] = (df['A'].rolling(N, center=True, min_periods=1, step=N)
                          .max().values
                         )

Output:

   Index  A  Res
0      0  3  NaN
1      1  2  NaN
2      2  5  5.0
3      3  4  NaN
4      4  1  NaN
5      5  2  NaN
6      6  7  NaN
7      7  3  7.0
8      8  1  NaN

If you want the 0s either pre-fill the columns with them (df['Res'] = 0) or use @Corralien’s approach from comments with a mask:

df['Res'] = (df.rolling(5, center=True, min_periods=1)['A'].max()
               .where(lambda x: x == df['A'], 0).convert_dtypes()
            )

Output:

   Index  A  Res
0      0  3    0
1      1  2    0
2      2  5    5
3      3  4    0
4      4  1    0
5      5  2    0
6      6  7    7
7      7  3    0
8      8  1    0