API: timestamp resolution inference - default to one unit (if possible) instead of being data-dependent? about pandas HOT 10 OPEN

I think could help simplify the implementation

I don't think it will simplify things generally, because we still need the current inference logic when the default unit does not fit, but from looking a bit into it, I also don't think it should make the code much more complex.

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cc @pandas-dev/pandas-core

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This sounds reasonable and I think could help simplify the implementation

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I think this would be an improvement. Seems like a good idea that anyone working with human times (say down to second precision) with a range of the modern era would get the same basis for the timestamp.

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take

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Based on discussions, I will update to_datetime to always use nanoseconds in the given scenarios.

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@jorisvandenbossche would updating the to_datetime function to accept a default unit='ns' be a feasible solution for this? Or are there cases where it wouldn't make sense to default to nanoseconds?

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@Pranav-Wadhwa nanoseconds is what we used previously, so I don't think we want to go back to that. The OP suggests microseconds as a default resolution, although I'm not sure its as simple as changing the to_datetime signature either.

Before diving into the details I think should get some more agreement from the pandas core team. @jbrockmendel is our datetime guru so let's see if he has any thoughts first

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I’m fine with OP suggestion as long as we are internally consistent, I.e. Timestamp constructor

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@jbrockmendel what do you mean by timestamp constructor? If we set the default value of unit='us' in to_datetime, it resolves the example that the OP mentioned but would require changing many test cases in tests/tools/test_to_datetime.py.

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