BUG: to_json returns incorrect timestamps if DatetimeIndex precision is not ns · Issue #53686 · pandas-dev/pandas (original) (raw)

Pandas version checks

• I have checked that this issue has not already been reported.
• 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 import numpy as np

d = pd.DataFrame({'testcol': pd.Series([12], index=[np.datetime64('2023-01-01T11:22:33.123456')])}) d.index = d.index.astype('datetime64[us]')

d.to_json(date_format='iso')

Issue Description

With a DataFrame in which the DatetimeIndex precision has been set to us, the json representation is incorrect.

With the usual initialization, the DatetimeIndex has precision ns, and it works fine:

import pandas as pd d = pd.DataFrame({'testcol': pd.Series([12], index=[np.datetime64('2023-01-01T11:22:33.123456')])}) d.to_json(date_format='iso') '{"testcol":{"2023-01-01T11:22:33.123":12}}'

If the precision is changed (I tried it as a workaround of issue #53684 ), the date is incorrect in to_json:

d.index = d.index.astype('datetime64[us]') d testcol 2023-01-01 11:22:33.123456 12

d.to_json(date_format='iso') '{"testcol":{"1970-01-20T08:36:12.153":12}}'

The date_unit parameter doesn't help, the date is still incorrect.

Other precisions fail too:

d.index = d.index.astype('datetime64[s]') d testcol 2023-01-01 11:22:33 12

d.to_json(date_format='iso') '{"testcol":{"1970-01-01T00:00:01.672":12}}'

Expected Behavior

The output of to_json in iso format should be '{"testcol":{"2023-01-01T11:22:33.123456":12}}'

Installed Versions

INSTALLED VERSIONS

commit : 965ceca
python : 3.10.8.final.0
python-bits : 64
OS : Linux
OS-release : 4.12.14-195-default
Version : #1 SMP Tue May 7 10:55:11 UTC 2019 (8fba516)
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8

pandas : 2.0.2
numpy : 1.24.3
pytz : 2023.3
dateutil : 2.8.2
setuptools : 63.2.0
pip : 22.2.2
Cython : None
pytest : 7.3.1
hypothesis : None
sphinx : 7.0.1
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.9.2
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.1.2
IPython : 8.13.2
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 : None
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 : 2.0.1
zstandard : None
tzdata : 2023.3
qtpy : None
pyqt5 : None