BUG: DataFrame.to_json does not take into account of time zone naive Timestamps

[alanhowells]

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
>>> d = {'date': [pd.to_datetime('2021-02-18')], 'instant': [pd.to_datetime('2021-02-18T11:12:13')]}
>>> df = pd.DataFrame(data=d)
>>> df.to_csv()
',date,instant\r\n0,2021-02-18,2021-02-18 11:12:13\r\n'
>>> df.to_json(orient='table',index=False)
'{"schema":{"fields":[{"name":"date","type":"datetime"},{"name":"instant","type":"datetime"}],"pandas_version":"1.4.0"},"data":[{"date":"2021-02-18T00:00:00.000Z","instant":"2021-02-18T11:12:13.000Z"}]}'

Issue Description

When I give a date without a time or an datetime that is time zone naïve into a dataframe, the to_json result gives UTC time zone aware instants instead of time zone naïve instants.
to_csv does the right thing by only giving the date, and a time zone naïve instant.

2021-02-18,2021-02-18 11:12:13

to_json returns a UTC time zone aware instants for both the date and the instant.

{"date":"2021-02-18T00:00:00.000Z","instant":"2021-02-18T11:12:13.000Z"}

Expected Behavior

I would expect the to_json to return the following

>>> df.to_json(orient='table',index=False)
'{"schema":{"fields":[{"name":"date","type":"datetime"},{"name":"instant","type":"datetime"}],"pandas_version":"1.4.0"},"data":[{"date":"2021-02-18","instant":"2021-02-18T11:12:13.000"}]}'

Note the lack of time for the date and the lack of time zone designator for the instant.

{"date":"2021-02-18","instant":"2021-02-18T11:12:13.000"}

Installed Versions

INSTALLED VERSIONS
------------------
commit           : 06d230151e6f18fdb8139d09abf539867a8cd481
python           : 3.9.5.final.0
python-bits      : 64
OS               : Windows
OS-release       : 10
Version          : 10.0.19042
machine          : AMD64
processor        : Intel64 Family 6 Model 165 Stepping 2, GenuineIntel
byteorder        : little
LC_ALL           : None
LANG             : None
LOCALE           : English_United Kingdom.1252
pandas           : 1.4.1

numpy            : 1.22.2

pytz             : 2021.1

dateutil         : 2.8.1

pip              : 22.0.3

setuptools       : 56.0.0

Cython           : None

pytest           : None

hypothesis       : None

sphinx           : None

blosc            : None

feather          : None

xlsxwriter       : None

lxml.etree       : None

html5lib         : None

pymysql          : None

psycopg2         : None

jinja2           : None

IPython          : None

pandas_datareader: None

bs4              : None

bottleneck       : None

fastparquet      : None

fsspec           : None

gcsfs            : None

matplotlib       : None

numba            : None

numexpr          : None

odfpy            : None

openpyxl         : None

pandas_gbq       : None

pyarrow          : None

pyreadstat       : None

pyxlsb           : None

s3fs             : None

scipy            : None

sqlalchemy       : None

tables           : None

tabulate         : None

xarray           : None

xlrd             : None

xlwt             : None

zstandard        : None

[lithomas1]

Is this a duplicate of #12997/#38760

[alanhowells]

@lithomas1 If DataFrame.to_json forwards to Series.to_json, then yes, this is a duplicate of #38760.

Sorry, I searched for "DataFrame" and "to_json", I should have searched for just "to_json".

Shall I close the issue?

[lithomas1]

Yeah. I'll close it. Thanks for reporting anyways. I'll try to take a look sometime soonish as the tz-naive case doesn't seem terribly hard to fix.