Python | Pandas Series.rename()

Last Updated : 14 Oct, 2019

Pandas series is a One-dimensional ndarray with axis labels. The labels need not be unique but must be a hashable type. The object supports both integer- and label-based indexing and provides a host of methods for performing operations involving the index. Pandas Series.rename() function is used to alter Series index labels or name for the given Series object.

Syntax: Series.rename(index=None, **kwargs) Parameter : index : dict-like or functions are transformations to apply to the index copy : Also copy underlying data inplace : Whether to return a new Series. If True then value of copy is ignored. level : In case of a MultiIndex, only rename labels in the specified level. Returns : Series, DataFrame, or None

Example #1: Use Series.rename() function to rename the name of the given Series object.

Python3

# importing pandas as pd import pandas as pd  # Creating the Series sr = pd.Series([10, 25, 3, 11, 24, 6])  # Create the Index index_ = ['Coca Cola', 'Sprite', 'Coke', 'Fanta', 'Dew', 'ThumbsUp']  # set the index sr.index = index_  # Print the series print(sr)

Output :

Now we will use Series.rename() function to rename the name of the given series object.

Python3 1==

# rename the series result = sr.rename('Beverages') # Print the result print(result)

Output :

As we can see in the output, the Series.rename() function has successfully renamed the given series object. Example #2: Use Series.rename() function to rename the MultiIndex axis of the given Series object.

Python3

# importing pandas as pd import pandas as pd  # Creating the Series sr = pd.Series(['New York', 'Chicago', 'Toronto', 'Lisbon', 'Rio'])  # Create the MultiIndex index_ = pd.MultiIndex.from_product([['Names'], ['City 1', 'City 2', 'City 3', 'City 4', 'City 5']],                                                                       names =['Level 1', 'Level 2'])  # set the index sr.index = index_  # Print the series print(sr)