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Python | Pandas Series.tz_convert

Last Updated : 30 Jan, 2019
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Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric python packages. Pandas is one of those packages and makes importing and analyzing data much easier.

Pandas series is a One-dimensional ndarray with axis labels. The labels need not be unique but must be a hashable type. The object supports both integer- and label-based indexing and provides a host of methods for performing operations involving the index.

Pandas Series.tz_convert() function works with time zone aware indexes. It convert tz-aware axis to target time zone.

Syntax: Series.tz_convert(tz, axis=0, level=None, copy=True)

Parameter :
tz : string or pytz.timezone object
axis : the axis to convert
level : int, str, default None
copy : Also make a copy of the underlying data.

Returns : Series

Example #1: Use Series.tz_convert() function to convert the time zone aware index of the given Series to the target time zone.




# importing pandas as pd
import pandas as pd
  
# Creating the Series
sr = pd.Series(['New York', 'Chicago', 'Toronto', 'Lisbon', 'Rio', 'Moscow'])
  
# Create the Datetime Index
didx = pd.DatetimeIndex(start ='2014-08-01 10:00', freq ='W'
                           periods = 6, tz = 'Asia/Calcutta'
  
# set the index
sr.index = didx
  
# Print the series
print(sr)


Output :

Now we will use Series.tz_convert() function to convert the given time zone index to time zone aware index to the target time zone which is ‘US/Central’.




# convert to 'US / Central'
sr.tz_convert('US/Central')


Output :

As we can see in the output, the Series.tz_convert() function has converted the time zone of the index of the given series object to the desired time zone.
 
Example #2: Use Series.tz_convert() function to convert the time zone aware index of the given Series to the target time zone.




# importing pandas as pd
import pandas as pd
  
# Creating the Series
sr = pd.Series([19.5, 16.8, 22.78, 20.124, 18.1002])
  
# Create the Datetime Index
didx = pd.DatetimeIndex(start ='2014-08-01 10:00', freq ='W'
                     periods = 5, tz = 'Asia/Calcutta'
  
# set the index
sr.index = didx
  
# Print the series
print(sr)


Output :

Now we will use Series.tz_convert() function to convert the given time zone index to time zone aware index to the target time zone which is ‘Europe/Berlin’




# convert to 'Europe / Berlin'
sr.tz_convert('Europe/Berlin')


Output :



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