Python | Панды Series.dt.tz_localize

Опубликовано: 27 Марта, 2022

Series.dt can be used to access the values of the series as datetimelike and return several properties. Pandas Series.dt.tz_localize() function localize tz-naive Datetime Array/Index to tz-aware Datetime Array/Index. This method takes a time zone (tz) naive Datetime Array/Index object and makes this time zone aware. It does not move the time to another time zone.

Syntax: Series.dt.tz_localize(*args, **kwargs)
Parameter :
tz : Time zone to convert timestamps to.
Returns : same type as self

Example #1: Use Series.dt.tz_localize() function to localize the tz-naive datetime value in the series to tz-aware.

# importing pandas as pd
import pandas as pd
  
# Creating the Series
sr = pd.Series(["2012-12-31", "2019-1-1 12:30", "2008-02-2 10:30",
               "2010-1-1 09:25", "2019-12-31 00:00"])
  
# Creating the index
idx = ["Day 1", "Day 2", "Day 3", "Day 4", "Day 5"]
  
# set the index
sr.index = idx
  
# Convert the underlying data to datetime 
sr = pd.to_datetime(sr)
  
# Print the series
print(sr)

Выход :

Now we will use Series.dt.tz_localize() function to localize the given tz-naive series to ‘US/Eastern’.

# localize to "US / Eastern"
result = sr.dt.tz_localize(tz = "US / Eastern")
  
# print the result
print(result)

Выход :

As we can see in the output, the Series.dt.tz_localize() function has successfully localized the given tz-naive datetime series to tz-aware.

Example #2 : Use Series.dt.tz_localize() function to return the given series object as an array of native python datetime object.

Выход :

Now we will use Series.dt.tz_localize() function to localize the given tz-naive series to ‘Europe/Berlin’.

# localize to "Europe / Berlin"
result = sr.dt.tz_localize(tz = "Europe / Berlin")
  
# print the result
print(result)

Выход :

As we can see in the output, the Series.dt.tz_localize() function has successfully localized the given tz-naive datetime series to tz-aware.

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Python | Панды Series.dt.tz_localize

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