Pandas DataFrame is a two-dimensional size-mutable, potentially heterogeneous tabular data structure with labeled axes (rows and columns). Arithmetic operations align on both row and column labels. It can be thought of as a dict-like container for Series objects. This is the primary data structure of the Pandas. Pandas DataFrame.tz_localize() function localize tz-naive index of a Series or DataFrame to target time zone. This operation localizes the Index.
Syntax: DataFrame.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 : When clocks moved backward due to DST, ambiguous times may arise nonexistent : A nonexistent time does not exist in a particular timezone where clocks moved forward due to DST Returns : Same type as the input.
Example #1: Use DataFrame.tz_localize() function to localize the given tz-naive index of the dataframe to the target timezone.
Python3
# importing pandas as pdimport pandas as pd# Creating the DataFramedf = pd.DataFrame({'Weight':[45, 88, 56, 15, 71], 'Name':['Sam', 'Andrea', 'Alex', 'Robin', 'Kia'], 'Age':[14, 25, 55, 8, 21]})# Create the indexindex_ = pd.date_range('2010-10-09 08:45', periods = 5, freq ='H', tz = 'US / Central')# Set the indexdf.index = index_# Print the DataFrameprint(df) |
Output : 
Now we will use DataFrame.tz_localize() function to localize the given tz-naive index of the dataframe to the ‘Europe/Berlin’ timezone.
Python3
# Let's find out the current timezone# of the given dataframeprint(df.index)# Let's localize the timezone of the# dataframe index to 'Europe / Berlin'df = df = df.tz_localize(tz = 'Europe / Berlin')# Let's find out the current timezone# of the given dataframeprint(df.index) |
Output : 
As we can see in the output, the DataFrame.tz_localize() function has successfully localized the tz-naive index of the given dataframe to the target timezone. Example #2 : Use DataFrame.tz_localize() function to localize the tz-naive Index of the given dataframe. The Index of the given dataframe is a MultiIndex.
Python3
# importing pandas as pdimport pandas as pd# Creating the DataFramedf = pd.DataFrame({'Weight':[45, 88, 56, 15, 71], 'Name':['Sam', 'Andrea', 'Alex', 'Robin', 'Kia'], 'Age':[14, 25, 55, 8, 21]})# Create the MultiIndexindex_ = pd.MultiIndex.from_product([['Date'], pd.date_range('2010-10-09 08:45', periods = 5, freq ='H')], names =['Level 1', 'Level 2'])# Set the indexdf.index = index_# Print the DataFrameprint(df) |
Output : 
Now we will use DataFrame.tz_localize() function to localize the tz-naive index of the given dataframe to ‘US/Central’.
Python3
# Let's find out the current timezone# of the Level 1 of the given dataframeprint(df.index[1])# Let's localize the timezone of the# level 1 of the dataframe to 'US / Central'df = df.tz_localize(tz = 'US / Central', level = 1)# Let's find out the current timezone# of the level 1 of the given dataframeprint(df.index[1]) |
Output : 
As we can see in the output, the DataFrame.tz_localize() function has successfully localized the tz-naive index of the given dataframe to ‘US/Central’.
