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
In [1]: import pandas as pd
In [2]: import numpy as np
In [3]: pd.Timedelta(np.timedelta64(200000, "D"))
Out[3]: Timedelta('-13504 days +00:25:26.290448384')Problem description
Pandas provides a useful error message if one tries to create a Timestamp using a datetime that is out of bounds for nanosecond-precision times:
In [4]: pd.Timestamp(np.datetime64("0001-01-01", "us"))
---------------------------------------------------------------------------
OutOfBoundsDatetime Traceback (most recent call last)
<ipython-input-11-1bf9f0c9d954> in <module>
----> 1 pd.Timestamp(np.datetime64("0001-01-01", "us"))
~/Software/pandas/pandas/_libs/tslibs/timestamps.pyx in pandas._libs.tslibs.timestamps.Timestamp.__new__()
~/Software/pandas/pandas/_libs/tslibs/conversion.pyx in pandas._libs.tslibs.conversion.convert_to_tsobject()
~/Software/pandas/pandas/_libs/tslibs/conversion.pyx in pandas._libs.tslibs.conversion.get_datetime64_nanos()
~/Software/pandas/pandas/_libs/tslibs/np_datetime.pyx in pandas._libs.tslibs.np_datetime.check_dts_bounds()
OutOfBoundsDatetime: Out of bounds nanosecond timestamp: 1-01-01 00:00:00
I was excited to see an exception along these lines added for out-of-bounds timedeltas, OutOfBoundsTimedelta:
#34448; however, it does not seem to be very easy to trigger. Is the idea to eventually check this in more places?
Expected Output
I might expect this to raise the newly added OutOfBoundsTimedelta error.
Output of pd.show_versions()
INSTALLED VERSIONS
commit : 2a7d332
python : 3.7.3.final.0
python-bits : 64
OS : Darwin
OS-release : 19.5.0
Version : Darwin Kernel Version 19.5.0: Tue May 26 20:41:44 PDT 2020; root:xnu-6153.121.2~2/RELEASE_X86_64
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.1.2
numpy : 1.19.1
pytz : 2020.1
dateutil : 2.8.1
pip : 19.2.2
setuptools : 49.6.0.post20200917
Cython : 0.29.19
pytest : 5.0.1
hypothesis : 5.6.0
sphinx : 3.0.4
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.4.1
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.11.2
IPython : 7.10.1
pandas_datareader: None
bs4 : 4.9.1
bottleneck : 1.2.1
fsspec : 0.8.2
fastparquet : None
gcsfs : 0.6.2+6.geca6dce
matplotlib : 3.3.0rc1.post439+g7e9530338
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pytables : None
pyxlsb : None
s3fs : None
scipy : 1.2.1
sqlalchemy : None
tables : None
tabulate : None
xarray : 0.16.1
xlrd : None
xlwt : None
numba : 0.51.2