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Calculate the frequency counts of each unique value of a Pandas series

  • Last Updated : 17 Aug, 2020
Geek Week

Let us see how to find the frequency counts of each unique value of a Pandas series. We will use the value_counts() function to perform this task.

Example 1 :




# importing the module
import pandas as pd
  
# creating the series
s = pd.Series(data = [2, 3, 4, 5, 5, 6
                      7, 8, 9, 5, 3])
  
# displaying the series
print(s)
  
# finding the unique count
print(s.value_counts())

Output :

Output:

Example 2 :






# importing the module
import pandas as pd
  
# creating the series
s = pd.Series(np.take(list('0123456789'), 
              np.random.randint(10, size = 40)))
  
# displaying the series
print(s)
  
# finding the unique count
s.value_counts()

Output :

Output:

Example 3 :




# importing pandas as pd 
import pandas as pd 
    
# creating the Series 
sr = pd.Series(['Mumbai', 'Pune', 'Agra', 'Pune'
                'Goa', 'Shimla', 'Goa', 'Pune']) 
  
# displaying the series 
print(sr) 
  
# finding the unique count
sr.value_counts()

Output :

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