# swegym / pandas-dev__pandas-53681

- taskset: [swegym](https://harnessreport.com/tasks/swegym.md)
- difficulty: hard
- category: debugging
- language: 
- runnable from the site: no
- agent timeout: 3000s

## Results by harness

_none yet_

## Instruction

```
BUG: inconsistent behavior of DateOffset
### Pandas version checks

- [X] I have checked that this issue has not already been reported.

- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.

- [X] I have confirmed this bug exists on the main branch of pandas.


### Reproducible Example

```python
import pandas as pd

df = pd.DataFrame({
   'S':[pd.Timestamp('2019-04-30')],
   'A':[pd.DateOffset(months=1)]
   })

# FIRST TEST
>>> df['S'] + 26 * df['A']
0   2021-06-30
dtype: datetime64[ns]

# SECOND TEST
>>> df['S'].iloc[0] + 26 * df['A'].iloc[0]
Timestamp('2021-06-28 00:00:00')
```


### Issue Description

It seems like multiplying a DateOffset by constant leads to an inconsistent behavior: the first test gives 30/6 while the second 28/6 

### Expected Behavior

In any case it should be 2021-06-30

### Installed Versions

<details>

INSTALLED VERSIONS
------------------
commit           : 66e3805b8cabe977f40c05259cc3fcf7ead5687d
python           : 3.10.1.final.0
python-bits      : 64
OS               : Windows
OS-release       : 10
Version          : 10.0.19042
machine          : AMD64
processor        : Intel64 Family 6 Model 126 Stepping 5, GenuineIntel
byteorder        : little
LC_ALL           : None
LANG             : None
LOCALE           : Italian_Italy.1252

pandas           : 1.3.5
numpy            : 1.21.5
pytz             : 2021.3
dateutil         : 2.8.2
pip              : 21.3.1
setuptools       : 58.1.0
Cython           : None
pytest           : None
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : 4.8.0
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : None
IPython          : 8.1.1
pandas_datareader: None
bs4              : None
bottleneck       : None
fsspec           : None
fastparquet      : None
gcsfs            : None
matplotlib       : 3.5.1
numexpr          : None
odfpy            : None
openpyxl         : 3.0.9
pandas_gbq       : None
pyarrow          : None
pyxlsb           : None
s3fs             : None
scipy            : 1.7.3
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
numba            : None

</details>
```
---
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