Pandas Index is an immutable ndarray implementing an ordered, sliceable set. It is the basic object which stores the axis labels for all pandas objects.
Pandas Index.is_unique attribute return True if the underlying data in the given Index object is unique else it return False.
Syntax: Index.is_unique
Parameter : None
Returns : boolean
Example #1: Use Index.is_unique attribute to find out if the underlying data in the given Index object is unique or not.
# importing pandas as pd import pandas as pd # Creating the index idx = pd.Index(['Melbourne', 'Sanghai', 'Lisbon', 'Doha', 'Moscow']) # Print the index print(idx) |
Output :
Now we will use Index.is_unique attribute to find out if the underlying data in the given Index object is unique or not.
# check if the values in the Index # is unique or not. result = idx.is_unique # Print the result print(result) |
Output :
As we can see in the output, the Index.is_unique attribute has returned True indicating that the underlying data of the given Index object is unique.
Example #2 : Use Index.is_unique attribute to find out if the underlying data in the given Index object is unique or not.
# importing pandas as pd import pandas as pd # Creating the index idx = pd.Index([900, 700, 620, 388, 900]) # Print the index print(idx) |
Output :
Now we will use Index.is_unique attribute to find out if the underlying data in the given Index object is unique or not.
# check if the values in the Index # is unique or not. result = idx.is_unique # Print the result print(result) |
Output :
As we can see in the output, the Index.is_unique attribute has returned False indicating that the underlying data of the given Index object is not unique.
