Select the maximum/minimum from n previous rows in a DataFrame

Question

I'm using pandas in Python and I have an issue to select some data. I have DataFrame with float values, and I would like to create a column which contains the maximum (or minimum) of the n previous rows of a column, and set to 0 for the n first rows, here's an example of the result I would like to have:

df_test = pd.DataFrame({'a':[2,7,2,0,-1, 19, -52, 2]})
df_test['result_i_want_with_n=3'] = [0, 0, 0, 7, 7, 2, 19, 19]
print(df_test)
    a   result_i_want_with_n=3
0   2   0
1   7   0
2   2   0
3   0   7
4   -1  7
5   19  2
6   -52 19
7   2   19

I managed to get this result using a while, but I would like to program it in a more "pandas" way to gain computation speed.

Thanks

Answer 1

Rolling is your friend here. You need to shift by one row in order to get your exact result, otherwise your first value will be in the third row.

df_test.rolling(window=3).max().shift(1).fillna(0)

0     0.0
1     0.0
2     0.0
3     7.0
4     7.0
5     2.0
6    19.0
7    19.0