Pandas Series.is_unique

This article explains the usage details of Pandas.Series.is_unique in Python with few examples.

In Pandas, the Series class provides a member variable is_unique, whose value will return True if all Series elements are unique.

pandas.Series.is_unique

It is True if all elements in the Series are unique and False if the Series contains any duplicate value.

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Examples of Series.is_unique

First, we will create a Series object from a list,

import pandas as pd

# Create Series object from List
seres_obj = pd.Series([11, 23, 4, 56, 34, 55, 11, 4, 56, 34])

print(seres_obj)

Output:

0    11
1    23
2     4
3    56
4    34
5    55
6    11
7     4
8    56
9    34
dtype: int64

Our Series object contains many duplicate elements. Now let’s use Series.is_unique to check if Series has any duplicates or all unique values.

# Check if all values in Series are unique
if seres_obj.is_unique:
    print('Yes, All values in Series are unique')
else:
    print('No, There are duplicates in the Series')

Output:

No, There are duplicates in the Series

As values in our Series are not unique, therefore it printed that the Series contains duplicates.

The complete example is as follows,

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import pandas as pd

# Create Series object from List
seres_obj = pd.Series([11, 23, 4, 56, 34, 55, 11, 4, 56, 34])

print(seres_obj)


# Check if all values in Series are unique
if seres_obj.is_unique:
    print('Yes, All values in Series are unique')
else:
    print('No, There are duplicates in the Series')

Output

0    11
1    23
2     4
3    56
4    34
5    55
6    11
7     4
8    56
9    34
dtype: int64

No, There are duplicates in the Series

Another example of Pandas.Series.is_unique

Let’s see another example, where we will create a Pandas Series of strings and then check if the Series contains all unique elements or not. For example,

import pandas as pd

# Create Series object from List
names = pd.Series([ 'Ritika',
                    'John',
                    'Mark',
                    'Shaun',
                    'Joseph',
                    'Pulkit',
                    'Lisa',
                    'Peter',
                    ])


print(names)


# Check if all values in Series are unique
if names.is_unique:
    print('Yes, All values in Series are unique')
else:
    print('No, There are duplicates in the Series')

Output:

0    Ritika
1      John
2      Mark
3     Shaun
4    Joseph
5    Pulkit
6      Lisa
7     Peter
dtype: object

Yes, All values in Series are unique

As there are no duplicates in our Series, it printed that all elements in the Series are unique.

Summary:

Today we learned how to use the is_unique function of the Pandas series.

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