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I have an array of Unix Epoch time stampts that I need to convert to datetime format in python.

I can make the conversion ok using numpy and pandas, as below:

tim = [1627599600,1627599600,1627599601,1627649998,1627649998,1627649999]
tim_np = np.array(tim)
tim_np = np.asarray(tim, dtype='datetime64[s]',)
tim_pd = pd.to_datetime(tim,unit='s', utc=True,)

print(tim_np)
print(tim_pd)

The problem I am running into is that the time zone is wrong, I am in NY so require it set to "EST".

I tried addressing by setting utc=True in the pd.to_datetime function but it still keeps defaulting to "GMT" ( 5 hours ahead).

I also tried the datetime.fromtimestamp(0) but it seemingly only works on single elements and not arrays - https://note.nkmk.me/en/python-unix-time-datetime/

Is there any efficient method to set the time zone when converting epochs?

John Conor
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1 Answers1

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Found that this can be achieved with pandas using the .tz_* methods:

.tz_localie - https://pandas.pydata.org/docs/reference/api/pandas.Series.dt.tz_localize.html

.tz_convert - https://pandas.pydata.org/docs/reference/api/pandas.Series.dt.tz_convert.html

Working code:

tim = [1627599600,1627599600,1627599601,1627649998,1627649998,1627649999]

tim_pd = (pd.to_datetime(tim,unit='s')
            .tz_localize('utc')
            .tz_convert('America/New_York'))

print(tim_pd)
John Conor
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