Calculate the frequency counts of each unique value of a Pandas series
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()) |
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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() |
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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() |
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