Pandas Series dt.tz_localize() | Convert tz-Naive DateTime to tz-Aware Last Updated : 11 Jul, 2025 Comments Improve Suggest changes Like Article Like Report The dt.tz_localize() method converts the time zone (tz)-naive Datetime Series object into a tz-aware Datetime Series. It does not move the time to another time zone. Example: Python3 import pandas as pd 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']) idx = ['Day 1', 'Day 2', 'Day 3', 'Day 4', 'Day 5'] sr.index = idx sr = pd.to_datetime(sr) result = sr.dt.tz_localize(tz = 'US / Eastern') print(result) Output : SyntaxSyntax: Series.dt.tz_localize((tz, ambiguous='raise', nonexistent='raise') Parameter: tz: Time zone to convert timestamps toambiguous: determines whether the time should be interpreted as wall time (default), the version of the time that was earlier, the version of the time that was later, or raise an error if ambiguousnon-existent: determines whether the time should be shifted forward to the closest existing time, shifted backward to the closest existing time, return NaT, or raise an error if nonexistentReturns: same type as self How to Convert a tz-Naive DateTime Series to tz-Aware DateTime SeriesTo convert a naive DateTime series to an aware DateTime series we use the dt.tz_localize() method of the Pandas library in Python. Let's understand it better with an example: ExampleUse the Series.dt.tz_localize() function to return the given series object as an array of native Python DateTime objects. Python3 # 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')) # 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 Series.dt.tz_localize() function to localize the given tz-naive series to 'Europe/Berlin'. Python3 # localize to 'Europe / Berlin' result = sr.dt.tz_localize(tz = 'Europe / Berlin') # print the result print(result) Output : As we can see in the output, the dt.tz_localize() function has successfully localized the given tz-naive datetime series to tz-aware. Comment S Shubham__Ranjan Follow 0 Improve S Shubham__Ranjan Follow 0 Improve Article Tags : Pandas Python-pandas Python pandas-series-datetime AI-ML-DS With Python Explore Pandas Tutorial 4 min read IntroductionPandas Introduction 3 min read How to Install Pandas in Python? 5 min read How To Use Jupyter Notebook - An Ultimate Guide 5 min read Creating ObjectsCreating a Pandas DataFrame 2 min read Python Pandas Series 5 min read Creating a Pandas Series 3 min read Viewing DataPandas Dataframe/Series.head() method - Python 3 min read Pandas Dataframe/Series.tail() method - Python 3 min read Pandas DataFrame describe() Method 4 min read Selection & SlicingDealing with Rows and Columns in Pandas DataFrame 5 min read Pandas Extracting rows using .loc[] - Python 3 min read Extracting rows using Pandas .iloc[] in Python 7 min read Indexing and Selecting Data with Pandas 4 min read Boolean Indexing in Pandas 6 min read Python | Pandas DataFrame.ix[ ] 2 min read Python | Pandas Series.str.slice() 3 min read How to take column-slices of DataFrame in Pandas? 2 min read OperationsPython | Pandas.apply() 4 min read Apply function to every row in a Pandas DataFrame 3 min read Python | Pandas Series.apply() 3 min read Pandas dataframe.aggregate() | Python 2 min read Pandas DataFrame mean() Method 2 min read Python | Pandas Series.mean() 2 min read Python | Pandas dataframe.mad() 2 min read Python | Pandas Series.mad() to calculate Mean Absolute Deviation of a Series 2 min read Python | Pandas dataframe.sem() 3 min read Python | Pandas Series.value_counts() 2 min read Pandas Index.value_counts()-Python 3 min read Applying Lambda functions to Pandas Dataframe 6 min read Manipulating DataAdding New Column to Existing DataFrame in Pandas 6 min read Python | Delete rows/columns from DataFrame using Pandas.drop() 4 min read Python | Pandas DataFrame.truncate 3 min read Python | Pandas Series.truncate() 2 min read Iterating over rows and columns in Pandas DataFrame 4 min read Pandas Dataframe.sort_values() 2 min read Python | Pandas Dataframe.sort_values() | Set-2 3 min read How to add one row in existing Pandas DataFrame? 4 min read Grouping DataPandas GroupBy 4 min read Grouping Rows in pandas 2 min read Combining Multiple Columns in Pandas groupby with Dictionary 2 min read Merging, Joining, Concatenating and ComparingPython | Pandas Merging, Joining and Concatenating 8 min read Python | Pandas Series.str.cat() to concatenate string 3 min read Python - Pandas dataframe.append() 4 min read Python | Pandas Series.append() 4 min read Pandas Index.append() - Python 2 min read Python | Pandas Series.combine() 3 min read Add a row at top in pandas DataFrame 1 min read Python | Pandas str.join() to join string/list elements with passed delimiter 2 min read Join two text columns into a single column in Pandas 2 min read How To Compare Two Dataframes with Pandas compare? 5 min read How to compare the elements of the two Pandas Series? 3 min read Working with Date and TimePython | Working with date and time using Pandas 8 min read Python | Pandas Timestamp.timestamp 3 min read Python | Pandas Timestamp.now 3 min read Python | Pandas Timestamp.isoformat 2 min read Python | Pandas Timestamp.date 2 min read Python | Pandas Timestamp.replace 3 min read Pandas.to_datetime()-Python 3 min read Python | pandas.date_range() method 4 min read Like