Python | Pandas Series.tz_localize
Last Updated :
30 May, 2022
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_localize() function is used to localize tz-naive index of a Series or DataFrame to target time zone. This operation localizes the Index. In order to localize the values in a timezone-naive Series, we can use Series.dt.tz_localize().
Syntax: Series.tz_localize(tz, axis=0, level=None, copy=True, ambiguous=’raise’, nonexistent=’raise’) Parameter : tz : string or pytz.timezone object axis : the axis to localize level : If axis is a MultiIndex, localize a specific level. Otherwise must be None copy : Also make a copy of the underlying data ambiguous : ‘infer’, bool-ndarray, ‘NaT’, default ‘raise’ nonexistent : str, default ‘raise’ Returns : Series or DataFrame
Example #1: Use Series.tz_localize() function to localize the time zone naive index of the given Series to the target time zone.
Python3
import pandas as pd
sr = pd.Series([ 'New York' , 'Chicago' , 'Toronto' , 'Lisbon' , 'Rio' , 'Moscow' ])
didx = pd.DatetimeIndex(start = '2014-08-01 10:00' , freq = 'W' ,
periods = 6 )
sr.index = didx
print (sr)
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Output : Now we will use Series.tz_localize() function to localize the given time zone naive index to time zone aware index. The target time zone is ‘US/Central’.
Python3
sr.tz_localize( 'US/Central' )
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Output : As we can see in the output, the Series.tz_localize() function has converted the given naive time zone index to a time aware index. Example #2: Use Series.tz_localize() function to localize the time zone naive index of the given Series to the target time zone.
Python3
import pandas as pd
sr = pd.Series([ 19.5 , 16.8 , 22.78 , 20.124 , 18.1002 ])
didx = pd.DatetimeIndex(start = '2014-08-01 10:00' , freq = 'W' ,
periods = 5 )
sr.index = didx
print (sr)
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Output : Now we will use Series.tz_localize() function to localize the given time zone naive index to time zone aware index. The target time zone is ‘Asia/Calcutta’.
Python3
sr.tz_localize( 'Asia/Calcutta' )
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Output :
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