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Python | Pandas Series.is_unique

  • Last Updated : 28 Jan, 2019

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.

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Pandas Series.is_unique attribute return a boolean value. It returns True if the data in the given Series object is unique else it return False.



Syntax:Series.is_unique

Parameter : None

Returns : boolean

Example #1: Use Series.is_unique attribute to check if the underlying data in the given Series object is unique or not.




# importing pandas as pd
import pandas as pd
  
# Creating the Series
sr = pd.Series(['New York', 'Chicago', 'Toronto', 'Lisbon', 'Chicago'])
  
# Creating the row axis labels
sr.index = ['City 1', 'City 2', 'City 3', 'City 4', 'City 5'
  
# Print the series
print(sr)

Output :

Now we will use Series.is_unique attribute to check if the underlying data in the given Series object is unique or it contains some duplicated value.




# check if underlying data is
# is unique or not
sr.is_unique

Output :


As we can see in the output, the Series.is_unique attribute has returned False indicating the underlying in the given series object is not unique.
 
Example #2 : Use Series.is_unique attribute to check if the underlying data in the given Series object is unique or not.




# 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)

Output :

Now we will use Series.is_unique attribute to check if the underlying data in the given Series object is unique or it contains some duplicated value.




# check if underlying data is
# is unique or not
sr.is_unique

Output :

As we can see in the output, the Series.is_unique attribute has returned True indicating the underlying in the given series object is unique.




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