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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.






# importing pandas as pd
import pandas as pd
  
# Creating the Series
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'])
  
# Creating the index
idx = ['Day 1', 'Day 2', 'Day 3', 'Day 4', 'Day 5']
  
# set the index
sr.index = idx
  
# Convert the underlying data to datetime 
sr = pd.to_datetime(sr)
  
# Print the series
print(sr)

Output :

Now we will use Series.dt.tz attribute to find the timezone of the datetime data in the given series object.




# find the timezone
result = sr.dt.tz
  
# print the result
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.




# importing pandas as pd
import pandas as pd
  
# Creating the Series
sr = pd.Series(pd.date_range('2012-12-31 00:00', periods = 5, freq = 'D',
                            tz = 'US / Central'))
  
# Creating the index
idx = ['Day 1', 'Day 2', 'Day 3', 'Day 4', 'Day 5']
  
# set the index
sr.index = idx
  
# Print the series
print(sr)

Output :



Now we will use Series.dt.tz attribute to find the timezone of the datetime data in the given series object.




# find the timezone
result = sr.dt.tz
  
# print the result
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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