BUG: pd.to_datetime() fails to parse nanoseconds

[gtopper]

Pandas version checks

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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 pandas as pd

timestamp = '15/02/2020 02:03:04.123456789'
timestamp_format = '%d/%m/%Y %H:%M:%S.%f'
pd.to_datetime(timestamp, format=timestamp_format)

Issue Description

New in 1.5.0 – the following error is raised

ValueError: unconverted data remains: 789

If dropping nanosecond support was intentional, the documentation was not updated accordingly.

Expected Behavior

No error raised.

Installed Versions

INSTALLED VERSIONS

commit : 87cfe4e
python : 3.8.9.final.0
python-bits : 64
OS : Darwin
OS-release : 21.6.0
Version : Darwin Kernel Version 21.6.0: Mon Aug 22 20:17:10 PDT 2022; root:xnu-8020.140.49~2/RELEASE_X86_64
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : None
LOCALE : None.UTF-8

pandas : 1.5.0
numpy : 1.22.4
pytz : 2022.2.1
dateutil : 2.8.2
setuptools : 65.3.0
pip : 22.2.2
Cython : None
pytest : 5.4.3
hypothesis : None
sphinx : 3.5.4
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.0.3
IPython : 7.31.0
pandas_datareader: None
bs4 : 4.10.0
bottleneck : None
brotli : None
fastparquet : None
fsspec : 2022.8.2
gcsfs : None
matplotlib : None
numba : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 6.0.1
pyreadstat : None
pyxlsb : None
s3fs : 0.6.0
scipy : None
snappy : None
sqlalchemy : 1.4.29
tables : None
tabulate : 0.8.9
xarray : None
xlrd : None
xlwt : None
zstandard : None
tzdata : None

[MarcoGorelli]

Thanks for the report @gtopper - from git bisect, this was due to #46736
cc @jbrockmendel

[AlexKirko]

We should also add test coverage for this. Weird that we missed it.

[anthonyaag]

Incidentally just rearranging the date seems to work

timestamp = '2020/02/15 02:03:04.123456789'
timestamp_format = '%Y/%m/%d %H:%M:%S.%f'
pd.to_datetime(timestamp, format=timestamp_format)

Timestamp('2020-02-15 02:03:04.123456789')

but fails again if one adds a time zone

timestamp = '2020/02/15 02:03:04.123456789 America/New_York'
timestamp_format = '%Y/%m/%d %H:%M:%S.%f %Z'
pd.to_datetime(timestamp, format=timestamp_format)

ValueError: time data '2020/02/15 02:03:04.123456789 America/New_York' does not match format '%Y/%m/%d %H:%M:%S.%f %Z' (match)

which again succeeds if we drop nanos

timestamp = '2020/02/15 02:03:04.123456 America/New_York'
timestamp_format = '%Y/%m/%d %H:%M:%S.%f %Z'
pd.to_datetime(timestamp, format=timestamp_format)

Timestamp('2020-02-15 02:03:04.123456-0500', tz='America/New_York')