Python | Pandas Series.index

Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric python packages. Pandas is one of those packages and makes importing and analyzing data much easier.

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.index attribute is used to get or set the index labels of the given Series object.

Syntax:Series.index

Parameter : None

Returns : index

Example #1: Use Series.index attribute to set the index label for the given Series object.

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# importing pandas as pd
import pandas as pd
  
# Creating the Series
sr = pd.Series(['New York', 'Chicago', 'Toronto', 'Lisbon'])
  
# Print the series
print(sr)

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Output :

Now we will use Series.index attribute to set the index label for the given object.

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# Creating the row axis labels
sr.index = ['City 1', 'City 2', 'City 3', 'City 4'

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Output :

As we can see in the output, the Series.index attribute has successfully set the index labels for the given Series object.

Example #2 : Use Series.index attribute to get the index labels of the given Series object.

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# importing pandas as pd
import pandas as pd
  
# Creating the Series
sr = pd.Series(['1/1/2018', '2/1/2018', '3/1/2018', '4/1/2018'])
  
# Creating the row axis labels
sr.index = ['Day 1', 'Day 2', 'Day 3', 'Day 4']
  
# Print the series
print(sr)

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Output :

Now we will use Series.index attribute to get the index label for the given object.

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# print the index labels
print(sr.index)

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Output :

As we can see in the output, the Series.index attribute has successfully returned the index labels for the given Series object.



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