Python | Pandas Timestamp.tz_localize

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 Timestamp.tz_localize() function convert naive Timestamp to local time zone, or remove timezone from tz-aware Timestamp.

Syntax :Timestamp.tz_localize()
Parameters : 
tz : Time zone for time which Timestamp will be converted to. None will remove timezone holding local time. 
ambiguous : bool, ‘NaT’, default ‘raise’ 
errors : ‘raise’, ‘coerce’, default ‘raise’
Return : localized : Timestamp 
 

Example #1: Use Timestamp.tz_localize() function to convert a tz-aware Timestamp to a naive Timestamp object. 

# importing pandas as pd
import pandas as pd

# Create the Timestamp object
ts = pd.Timestamp(year = 2011,  month = 11, day = 21, 
                  hour = 10, second = 49, tz = 'US/Central') 

# Print the Timestamp object
print(ts)

Output : 

Now we will use the Timestamp.tz_localize() function to convert the tz-aware Timestamp to naive Timestamp. 

# convert to naive Timestamp
ts.tz_localize(tz = None)

Output : 

As we can see in the output, the Timestamp.tz_localize() function has converted the given Timestamp to a naive Timestamp. 
  
Example #2: Use Timestamp.tz_localize() function to convert the given naive Timestamp to tz-aware Timestamp object. Set the timezone to 'US/Pacific'.

# importing pandas as pd
import pandas as pd

# Create the Timestamp object
ts = pd.Timestamp(year = 2009, month = 5, day = 31, 
                             hour = 4, second = 49)

# Print the Timestamp object
print(ts)

Output : 

Now we will use the Timestamp.tz_localize() function to set the timezone of ts object to 'US/Pacific'. 

# set to 'US / Pacific'
ts.tz_localize(tz = 'US/Pacific')

Output : 

As we can see in the output, the Timestamp.tz_localize() function has set the timezone of the given object to 'US/Pacific'.