The dt.tz_convert() method converts tz-aware DateTime Series object from one time zone to another.
Example
import pandas as pd
sr = pd.Series(pd.date_range('2012-12-31 00:00', periods = 5, freq = 'D',
tz = 'US / Central'))
idx = ['Day 1', 'Day 2', 'Day 3', 'Day 4', 'Day 5']
sr.index = idx
result = sr.dt.tz_convert(tz = 'Europe / Berlin')
print(result)
Output:

Syntax
Syntax: Series.dt.tz_convert(tz)
Parameter
- tz: Time zone to convert timestamps to.
Returns: series of same type as input
How to Convert Timezones For tz-aware DateTime Series
To convert timezones from one timezone to another in a tz-aware DateTime Series we use the dt.tz_convert method of the Pandas library in Python.
Let us understand it better with an example:
Example:
Use the Series.dt.tz_convert() function to convert the timezone of the timestamps 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 the dt.tz_convert() function to convert the timestamps in the given series object to 'Asia/Calcutta'.
# convert to 'Asia / Calcutta'
result = sr.dt.tz_convert(tz = 'Asia / Calcutta')
# print the result
print(result)
Output :

As we can see in the output, the dt.tz_convert() function has successfully converted the timezone of the timestamps in the given series object to the target timezone.