Python | Pandas Series.rename_axis()

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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_axis() function is used to set the name of the axis for the index or columns.

Syntax: Series.rename_axis(mapper=None, index=None, columns=None, axis=None, copy=True, inplace=False)

Parameter :
mapper : Value to set the axis name attribute.
index, columns : A scalar, list-like, dict-like or functions transformations to apply to that axis’ values.
axis : The axis to rename.
copy : Also copy underlying data.
inplace : Modifies the object directly, instead of creating a new Series or DataFrame.

Returns : Series, DataFrame, or None

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

# 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_axis() function to rename the axis of the given series object.

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

Output :

As we can see in the output, the Series.rename_axis() function has successfully renamed the axis of the given series object.

Example #2 : Use Series.rename_axis() function to rename the MultiIndex axis of the given Series object.

# 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) 

Output :

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

# rename both the levels of the axis of  
# the given series object 
result = sr.rename_axis(['First_level', 'Second_level']) 
  
# Print the result 
print(result) 

Output :

As we can see in the output, the Series.rename_axis() function has successfully renamed both the levels of the axis of the given series object.