BUG: Timestamp.isoformat works incorrect on ns precision #53020
Description
Pandas version checks
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I have checked that this issue has not already been reported.
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I have confirmed this bug exists on the latest version of pandas.
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I have confirmed this bug exists on the main branch of pandas.
Reproducible Example
import pandas as pd ts = pd.Timestamp("2023-01-01 00:00:00") ts_1ns = ts + pd.Timedelta(nanoseconds=1) print(ts.isoformat(timespec='nanoseconds')) print(ts_1ns.isoformat(timespec='nanoseconds'))Issue Description
If the requested precision is in nanoseconds and the timestamp has 0 microseconds, then the format is invalid and looks like the following:
2023-01-01T00:00:00.000000.000000000
2023-01-01T00:00:00.000000.000000001
Expected Behavior
2023-01-01T00:00:00.000000000
2023-01-01T00:00:00.000000001
Installed Versions
/opt/homebrew/Cellar/python@3.11/3.11.2_1/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/_distutils_hack/__init__.py:33: UserWarning: Setuptools is replacing distutils. warnings.warn("Setuptools is replacing distutils.") INSTALLED VERSIONS ------------------ commit : 37ea63d540fd27274cad6585082c91b1283f963d python : 3.11.2.final.0 python-bits : 64 OS : Darwin OS-release : 22.4.0 Version : Darwin Kernel Version 22.4.0: Mon Mar 6 20:59:28 PST 2023; root:xnu-8796.101.5~3/RELEASE_ARM64_T6000 machine : arm64 processor : arm byteorder : little LC_ALL : None LANG : ru_RU.UTF-8 LOCALE : ru_RU.UTF-8 pandas : 2.0.1 numpy : 1.24.2 pytz : 2023.3 dateutil : 2.8.2 setuptools : 65.6.3 pip : 23.1 Cython : None pytest : None hypothesis : None sphinx : None blosc : None feather : None xlsxwriter : None lxml.etree : None html5lib : None pymysql : None psycopg2 : None jinja2 : 3.1.2 IPython : 8.12.0 pandas_datareader: None bs4 : 4.12.2 bottleneck : None brotli : None fastparquet : None fsspec : None gcsfs : None matplotlib : 3.7.1 numba : None numexpr : None odfpy : None openpyxl : 3.1.2 pandas_gbq : None pyarrow : None pyreadstat : None pyxlsb : None s3fs : None scipy : 1.10.1 snappy : None sqlalchemy : None tables : None tabulate : None xarray : None xlrd : None zstandard : None tzdata : 2023.3 qtpy : None pyqt5 : None