BUG: Inconsistent `to_datetime` behaviour

[abhijeetbodas2001]

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

>>> pd.to_datetime("1704660000", unit="s", origin="unix")
<stdin>:1: FutureWarning: The behavior of 'to_datetime' with 'unit' when parsing strings is deprecated. In a future version, strings will be parsed as datetime strings, matching the behavior without a 'unit'. To retain the old behavior, explicitly cast ints or floats to numeric type before calling to_datetime.
Timestamp('2024-01-07 20:39:28')

>>> pd.to_datetime(1704660000, unit="s", origin="unix")
Timestamp('2024-01-07 20:40:00')

Issue Description

Incorrect datetime object generated when unix timestamp is passed as string.

Expected Behavior

The timestamp string should be converted to the correct datetime regarless of the dtype of the input (string or int). Or, raise error if string inputs are illegal.

The current depracation warning seems to imply that the behaviour is working as expected now, but won't be available in future versions.

Installed Versions

[~] $ pip list | rg "pandas|numpy"
numpy                             1.26.1
pandas                            2.2.0
pandas-stubs                      2.1.4.231218

[MarcoGorelli]

The current depracation warning seems to imply that the behaviour is working as expected now, but won't be available in future versions.

indeed, it'll error in the future

not sure what you're asking, sorry - could you clarify please? what's your expected output?

[abhijeetbodas2001]

Thanks for your response.

not sure what you're asking, sorry - could you clarify please? what's your expected output?

to_datetime currently gives different outputs when the same unix timestamp is passed as a string vs as an int. Question is, should it not return the same datetime object in both the cases?

[MarcoGorelli]

thanks - sorry, I'd missed the minutes/seconds difference

I agree, but as the first one's deprecated this probably isn't worth fixing

Thanks anyway for the report! 🙏

[abhijeetbodas2001]

I had hoped a fix could have made it to the next minor release (ie, before it is removed), but I can understand if it does not make the cut. Anyways, thanks!

[QuLogic]

Do note that this was working correctly in 1.5.3; so while it is deprecated, this is a regression introduced in Pandas 2.0.0.

[QuLogic]

Since I have a good&bad commit, I can bisect the change, which points to 83c2a5f.

I believe the issue is that the string is being cast to float32 instead of float64 somewhere:

>>> pd.to_datetime(np.float32("1704660000"), unit="s", origin="unix")
Timestamp('2024-01-07 20:39:28')
>>> pd.to_datetime(np.float64("1704660000"), unit="s", origin="unix")
Timestamp('2024-01-07 20:40:00')
>>>