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.
Python3
# importing pandas as pdimport pandas as pd# Create the Timestamp objectts = pd.Timestamp(year = 2011, month = 11, day = 21, hour = 10, second = 49, tz = 'US/Central') # Print the Timestamp objectprint(ts) |
Output :
Now we will use the Timestamp.tz_localize() function to convert the tz-aware Timestamp to naive Timestamp.
Python3
# convert to naive Timestampts.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’.
Python3
# importing pandas as pdimport pandas as pd# Create the Timestamp objectts = pd.Timestamp(year = 2009, month = 5, day = 31, hour = 4, second = 49)# Print the Timestamp objectprint(ts) |
Output :
Now we will use the Timestamp.tz_localize() function to set the timezone of ts object to ‘US/Pacific’.
Python3
# 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’.
