BUG: pd.to_timedelta() fails when arg is a Series with Int64 dtype

[egoddard]

• I have checked that this issue has not already been reported.

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

• (optional) I have confirmed this bug exists on the master branch of pandas.

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Code Sample, a copy-pastable example

import pandas as pd


series = pd.Series([pd.NA], dtype="Int64")

pd.to_timedelta(series, errors="coerce")

Problem description

When converting a Series with an Int64 dtype to a timedelta, to_timedelta fails with

ValueError: cannot convert to 'int64'-dtype NumPy array with missing values. Specify an appropriate 'na_value' for this dtype.

Passing a Python list containing a NA value works, as does passing an Int64 Series that does not contain NA values. The functionality between these cases should be equivalent.

Expected Output

pd.to_timedelta() output returns a timedelta64 Series containing NA values when the input is an Int64 Series containg NA values:

0   <NA>
dtype: timedelta64[ns]

Output of pd.show_versions()

INSTALLED VERSIONS

commit : 3b6915e
python : 3.7.7.final.0
python-bits : 64
OS : Linux
OS-release : 5.4.0-7634-generic
Version : #38159534531720.04~a8480ad-Ubuntu SMP Wed Jul 22 15:13:45 UTC
machine : x86_64
processor :
byteorder : little
LC_ALL : C.UTF-8
LANG : C.UTF-8
LOCALE : en_US.UTF-8

pandas : 1.2.0.dev0+28.g3b6915ef9
numpy : 1.18.5
pytz : 2020.1
dateutil : 2.8.1
pip : 20.2.1
setuptools : 45.2.0.post20200210
Cython : 0.29.21
pytest : 6.0.1
hypothesis : 5.23.11
sphinx : 3.1.1
blosc : None
feather : None
xlsxwriter : 1.3.1
lxml.etree : 4.4.1
html5lib : 1.1
pymysql : None
psycopg2 : None
jinja2 : 2.11.2
IPython : 7.17.0
pandas_datareader: None
bs4 : 4.9.1
bottleneck : 1.3.2
fsspec : 0.8.0
fastparquet : 0.4.1
gcsfs : 0.6.2
matplotlib : 3.2.1
numexpr : 2.7.1
odfpy : None
openpyxl : 3.0.4
pandas_gbq : None
pyarrow : 0.16.0
pytables : None
pyxlsb : None
s3fs : 0.4.2
scipy : 1.5.2
sqlalchemy : 1.3.18
tables : 3.6.1
tabulate : 0.8.7
xarray : 0.16.0
xlrd : 1.2.0
xlwt : 1.3.0
numba : 0.50.1

[TomAugspurger]

Thanks for the report. sequence_to_td64ns should probably handle masked arrays like IntegerArray specially. It could be done with a to_numpy("int64", na_value=tslibs.iNaT).

Are you interested in working on this?

[egoddard]

@TomAugspurger I am interested in working on it. I attempted a quick fix by trying to force ints_to_td64ns to work with the Int64Dtype(), but that lead to other issues :). I'll try a specific case in sequence_to_td64ns and report back. Thanks!

[egoddard]

take