Python | Pandas Series.dt.tz
Last Updated :
20 Mar, 2019
Series.dt
can be used to access the values of the series as datetimelike and return several properties. Pandas Series.dt.tz
attribute return the timezone if any, else it return None.
Syntax: Series.dt.tz
Parameter : None
Returns : timezone
Example #1: Use Series.dt.tz
attribute to find the timezone of the underlying datetime based data in the given series object.
import pandas as pd
sr = pd.Series([ '2012-12-31' , '2019-1-1 12:30' , '2008-02-2 10:30' ,
'2010-1-1 09:25' , '2019-12-31 00:00' ])
idx = [ 'Day 1' , 'Day 2' , 'Day 3' , 'Day 4' , 'Day 5' ]
sr.index = idx
sr = pd.to_datetime(sr)
print (sr)
|
Output :
Now we will use Series.dt.tz
attribute to find the timezone of the datetime data in the given series object.
result = sr.dt.tz
print (result)
|
Output :
As we can see in the output, the Series.dt.tz
attribute has returned None
indicating the timezone for the given datetime data is not known.
Example #2 : Use Series.dt.tz
attribute to find the timezone of the underlying datetime based data in the given series object.
import pandas as pd
sr = pd.Series(pd.date_range( '2012-12-31 00:00' , periods = 5 , freq = 'D' ,
tz = 'US / Central' ))
idx = [ 'Day 1' , 'Day 2' , 'Day 3' , 'Day 4' , 'Day 5' ]
sr.index = idx
print (sr)
|
Output :
Now we will use Series.dt.tz
attribute to find the timezone of the datetime data in the given series object.
result = sr.dt.tz
print (result)
|
Output :
As we can see in the output, the Series.dt.tz
attribute has successfully returned the timezone of the underlying datetime based data in the given Series object.
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