DateTime conversion of exported CSV file type 1549663223992.0

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04-10-2019 03:05 PM
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New Contributor III

I've got an automated process started that downloads a Feature Layer Collection from an AGOL account for clean-up and rewrite.  Comes down just fine as a CSV but the dates come down as a large number that I can convert using float.  I'm unable to come across any way to convert this in Python (3.7) to make it a usable DateTime feature.  Can you point me towards a way to accomplish this.  Neither of the lines of code below do anything with the number.

ndt_value = (datetime.datetime(float(date_value), dateFormat=u'%m/%d/%Y', timeFormat=u'%I:%M:%S %p')
ndt_value = time.strptime(float(date_value), "%d %b %y") 

They all come across looking like this.

            dte1                          dte2

value 1549492620000.0 1549663223992.0

value 1549493100000.0 1549661829963.0

value 1549493220000.0 1554867569006.0

value 1549394280000.0 1554867776915.0

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MVP Regular Contributor

Hi Jackie Fisher‌,

The date values in your output are epoch timestamps in milliseconds.

The time.ctime() function takes seconds passed since epoch as an argument and returns a string representing local time. So, you have to divide your values by thousand, like this:

import time

print(time.ctime(1549492620000.0/1000))

# Output will be:
# Wed Feb 06 23:37:00 2019

For a quick, manual conversion of an epoch timestamp you can have a look at this website: https://www.epochconverter.com/

HTH,

Egge-Jan

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New Contributor III

Thank You.  It was just driving me crazy.

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MVP Regular Contributor

Please feel free to mark the answer as correct if your issue is being solved 🙂

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