What is the format for UNIX timestamp of '253402128000000'?-CodePudding

I'm trying to convert a whole column of timestamp values in UNIX format but I get some values that doesn't look like a normal timestamp format: 253402128000000

For what I know, a timestamp should look like: 1495245009655

I've tried in miliseconds, nanoseconds and other configurations for Pandas to_datetime but I haven't been able to find a solution that can convert the format.

EDIT

My data looks like below and the ValidEndDateTime seems way off.

        "ValidStartDateTime": "/Date(1495245009655)/",
        "ValidEndDateTime": "/Date(253402128000000)/",

SOLUTION

I've accepted the answer below because I can see the date is a "never-end" date as all the values in my dataset that can't be converted is set to the same value: 253402128000000

Thank you for the answers!

CodePudding user response：

From a comment of yours:

The data I get looks like this: "ValidStartDateTime": "/Date(1495245009655)/", "ValidEndDateTime": "/Date(253402128000000)/",

The numbers appear to be UNIX timestamps in milliseconds and the big "End" one seems to mean "never end", note the special date:

1495245009655 = Sat May 20 2017 01:50:09

253402128000000 = Thu Dec 30 9999 00:00:00

Converted with https://currentmillis.com/

CodePudding user response：

I think it was divided by 1,000,000 becoming 253402128 and calculated.

Which means approximately 44 years ago.

Format: Microseconds (1/1,000,000 second)

GMT: Wed Jan 11 1978 21:28:48 GMT 0000

I used this website as reference: https://www.unixtimestamp.com/

CodePudding user response：

Use pd.to_datetime:

>>> pd.to_datetime(1495245009655, unit='ms')
Timestamp('2017-05-20 01:50:09.655000')

>>> pd.to_datetime(253402128000000 / 100, unit='ms')
Timestamp('2050-04-19 22:48:00')