Description
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Note: Please read this guide detailing how to provide the necessary information for us to reproduce your bug.
Code Sample, a copy-pastable example
>>> x = pd.Series([pd.Timedelta(100000, "days"), pd.Timedelta(100000, "days")])
# Results in ValueError
>>> x.sum()
# Results in OverflowError
>>> pd.Timedelta(100000, "days")*2
# Results in OverflowError
>>> x + x
# Permits overflow
>>> x*2
0 -13504 days +00:25:26.290448384
1 -13504 days +00:25:26.290448384
dtype: timedelta64[ns]Problem description
It would seem that pandas.Series calcs with Timedeltas are inconsistent in raising overflow errors, or not.
The exact error is also inconsistent (OverflowError vs ValueError).
Expected Output
Ideally x*2 in above example raises an error, and all overflow related errors are of type OverflowError.
Output of pd.show_versions()
INSTALLED VERSIONS
commit : 5f648bf
python : 3.7.5.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.19041
machine : AMD64
processor : Intel64 Family 6 Model 158 Stepping 10, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : None.None
pandas : 1.3.2
numpy : 1.21.2
pytz : 2021.1
dateutil : 2.8.2
pip : 19.2.3
setuptools : 41.2.0
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : None
IPython : None
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : None