datetimeoffset

pandas out of bounds nanosecond timestamp after offset rollforward plus adding a month offset

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Since pandas represents timestamps in nanosecond resolution, the timespan that can be represented using a 64-bit integer is limited to approximately 584 years In [54]: pd.Timestamp.min Out[54]: Timestamp(‘1677-09-22 00:12:43.145225’) In [55]: pd.Timestamp.max Out[55]: Timestamp(‘2262-04-11 23:47:16.854775807’) And your value is out of this range 2262-05-01 00:00:00 and hence the outofbounds error Straight out of: https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#timestamp-limitations Workaround: … Read more

Storing DateTime (UTC) vs. storing DateTimeOffset

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There is one huge difference, where you cannot use UTC alone. If you have a scenario like this One server and several clients (all geographically in different timezones) Clients create some data with datetime information Clients store it all on central server Then: datetimeoffset stores Local time of the client and ALSO offset to the … Read more

DateTime vs DateTimeOffset

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DateTimeOffset is a representation of instantaneous time (also known as absolute time). By that, I mean a moment in time that is universal for everyone (not accounting for leap seconds, or the relativistic effects of time dilation). Another way to represent instantaneous time is with a DateTime where .Kind is DateTimeKind.Utc. This is distinct from … Read more

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