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• I have confirmed this bug exists on the latest version of pandas.

• I have confirmed this bug exists on the main branch of pandas.

Reproducible Example

import numpy as np
import pandas as pd

# Create sample data
dates = pd.date_range(start='2024-01-01', periods=5, freq='D')
ids = range(1, 3)

np.random.seed(42)
# Create all combinations of dates and ids
data = []
for date in dates:
    for id in ids:
        data.append({
            'date': date,
            'Id': id,
            'value': np.random.rand() * 100
        })

df_sample = pd.DataFrame(data)
print(df_sample)

def rolling_func(x):
    print(x)

    return x.iloc[-1]

df_sample.set_index('date').groupby('Id')['value'].rolling(5, min_periods=1).apply(rolling_func, raw=False)

Issue Description

    date          Id   value

2024-01-01 1 37.454012
2024-01-01 2 95.071431
2024-01-02 1 73.199394
2024-01-02 2 59.865848
2024-01-03 1 15.601864
2024-01-03 2 15.599452
2024-01-04 1 5.808361
2024-01-04 2 86.617615
2024-01-05 1 60.111501
2024-01-05 2 70.807258

For a sample dataframe like the above, the code returns the following results. I believe that the rolling results based on the group (by Id) and time-based index (by date) are wrong.

date
2024-01-01 37.454012
dtype: float64
date
2024-01-01 37.454012
2024-01-01 73.199394
dtype: float64
date
2024-01-01 37.454012
2024-01-01 73.199394
2024-01-02 15.601864
dtype: float64
date
2024-01-01 37.454012
2024-01-01 73.199394
2024-01-02 15.601864
2024-01-02 5.808361
dtype: float64
date
2024-01-01 37.454012
2024-01-01 73.199394
2024-01-02 15.601864
2024-01-02 5.808361
2024-01-03 60.111501
dtype: float64
date
2024-01-03 95.071431
dtype: float64
date
2024-01-03 95.071431
2024-01-04 59.865848
dtype: float64
date
2024-01-03 95.071431
2024-01-04 59.865848
2024-01-04 15.599452
dtype: float64
date
2024-01-03 95.071431
2024-01-04 59.865848
2024-01-04 15.599452
2024-01-05 86.617615
dtype: float64
date
2024-01-03 95.071431
2024-01-04 59.865848
2024-01-04 15.599452
2024-01-05 86.617615
2024-01-05 70.807258
dtype: float64

Expected Behavior

I expect the results shall be like the following:
date
2024-01-01 37.454012
dtype: float64
date
2024-01-01 37.454012
2024-01-02 73.199394 # Instead of "2024-01-01 73.199394"
dtype: float64
date
2024-01-01 37.454012
2024-01-02 73.199394 # Instead of "2024-01-01 73.199394"
2024-01-03 15.601864 # Instead of "2024-01-02 15.601864"
dtype: float64
date
2024-01-01 37.454012
2024-01-02 73.199394 # Instead of "2024-01-01 73.199394"
2024-01-03 15.601864 # Instead of "2024-01-02 15.601864"
2024-01-04 5.808361 # Instead of "2024-01-02 5.808361"

Installed Versions