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.
