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Python | Pandas Series.keys()

Last Updated : 12 Feb, 2019
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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.keys() function is an alias for index. It returns the index labels of the given series object.

Syntax: Series.keys()

Parameter : None

Returns : index

Example #1: Use Series.keys() function to return the index labels of the given series object.




# importing pandas as pd
import pandas as pd
  
# Creating the Series
sr = pd.Series([10, 25, 3, 25, 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.keys() function to return the index labels of the given series object.




# return the keys
result = sr.keys()
  
# Print the result
print(result)


Output :


As we can see in the output, the Series.keys() function has returned all the index labels of the given series object.
 
Example #2 : Use Series.keys() function to return the index labels of the given series object.




# importing pandas as pd
import pandas as pd
  
# Creating the Series
sr = pd.Series([11, 21, 8, 18, 65, 84, 32, 10, 5, 24, 32])
  
# Create the Index
index_ = pd.date_range('2010-10-09', periods = 11, freq ='M')
  
# set the index
sr.index = index_
  
# Print the series
print(sr)


Output :

Now we will use Series.keys() function to return the index labels of the given series object.




# return the keys
result = sr.keys()
  
# Print the result
print(result)


Output :

As we can see in the output, the Series.keys() function has returned all the index labels of the given series object.



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