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.items() function iterates over the given series object. The function iterates over the tuples containing the index labels and corresponding value in the series.
Syntax: Series.items()
Parameter : None
Returns : tuples
Example #1: Use Series.items() function to iterate over all the elements in 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.items() function to iterate over all the elements in the given series object.
# iterate over all the elements for items in sr.items(): print(items) |
Output :
As we can see in the output, the Series.items() function has successfully iterated over all the elements in the given series object.
Example #2 : Use Series.items() function to iterate over all the elements in 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.items() function to iterate over all the elements in the given series object.
# iterate over all the elements for items in sr.items(): print(items) |
Output :
