Pandas: converting to datetime with timezone name

Question

I am trying to convert to datetime in pandas dataframe, where name of timezone is included. I have tried the following but it yields an error:

d = {'col1': ['Sun Dec 31 00:00:00 EAT 1899', 'Mon Mar 02 00:00:00 EAT 2020']}
x = pd.DataFrame(data=d)
pd.to_datetime(x['col1'], format='%a %b %d %H:%M:%S %Z %Y', errors='coerce')

0   NaT
1   NaT
Name: col1, dtype: datetime64[ns]

Is there any way to convert to datetime this way? If not, how to ignore the timezone name?

Ben.T · Accepted Answer · 2020-04-21 13:54:00Z

1

you can use dateutil:

import dateutil
print (x['col1'].apply(dateutil.parser.parse))
0   1899-12-31
1   2020-03-02
Name: col1, dtype: datetime64[ns]

or to ignore the part with the timezoen, something like:

pd.to_datetime(x['col1'].str[:20] + x['col1'].str[24:])

but not sure if it is interesting

edited Apr 21, 2020 at 13:54

answered Apr 21, 2020 at 13:36

Ben.T

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