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.
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:
Frequently Asked:
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,
Latest Python - Video Tutorial
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.
Latest Video Tutorials