Python | Pandas Series.items()

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.

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# 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)

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Output :

Now we will use Series.items() function to iterate over all the elements in the given series object.

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# iterate over all the elements
for items in sr.items():
    print(items)

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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.

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# 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)

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Output :

Now we will use Series.items() function to iterate over all the elements in the given series object.

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# iterate over all the elements
for items in sr.items():
    print(items)

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Output :



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