How to get pandas to roll through entire series?

Question

Pandas Rolling function

Last elements when window_size == step_size

I can't seem to get the last three element of an example 9 element series to be rolled on, when my window size and step size are both 3.

Is the below an intended behaviour of pandas?

My desired outcome

If so how can I roll over the Series so that:

pd.Series([1., 1., 1., 2., 2., 2., 3., 3., 3.]).rolling(window=3, step=3).mean()

evaluate to pd.Series([1., 2., 3.,])?

Example

    import pandas as pd

    def print_mean(x):
        print(x)
        return x.mean()

    df = pd.DataFrame({"A": [0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0]})

    df["left"] = (
        df["A"].rolling(window=3, step=3, closed="left").apply(print_mean, raw=False)
    )
    df["right"] = (
        df["A"].rolling(window=3, step=3, closed="right").apply(print_mean, raw=False)
    )
    df["both"] = (
        df["A"].rolling(window=3, step=3, closed="both").apply(print_mean, raw=False)
    )
    df["neither"] = (
        df["A"].rolling(window=3, step=3, closed="neither").apply(print_mean, raw=False)
    )

This evaluates to:

     A  left  right  both  neither
0  0.0   NaN    NaN   NaN      NaN
1  1.0   NaN    NaN   NaN      NaN
2  2.0   NaN    NaN   NaN      NaN
3  3.0   1.0    2.0   1.5      NaN
4  4.0   NaN    NaN   NaN      NaN
5  5.0   NaN    NaN   NaN      NaN
6  6.0   4.0    5.0   4.5      NaN
7  7.0   NaN    NaN   NaN      NaN
8  8.0   NaN    NaN   NaN      NaN

and prints:

0    0.0
1    1.0
2    2.0
dtype: float64
3    3.0
4    4.0
5    5.0
dtype: float64

1    1.0
2    2.0
3    3.0
dtype: float64
4    4.0
5    5.0
6    6.0
dtype: float64

0    0.0
1    1.0
2    2.0
3    3.0
dtype: float64
3    3.0
4    4.0
5    5.0
6    6.0
dtype: float64

Answer 1

You could try subsetting every 3 rows by using the % operator:

df[df.index % 3 == 0]

This will output: