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 moduleimport pandas as pd # creating the seriess = pd.Series(data = [2, 3, 4, 5, 5, 6, 7, 8, 9, 5, 3]) # displaying the seriesprint(s) # finding the unique countprint(s.value_counts()) |
Output :
Output:
Example 2 :
# importing the moduleimport pandas as pd # creating the seriess = pd.Series(np.take(list('0123456789'), np.random.randint(10, size = 40))) # displaying the seriesprint(s) # finding the unique counts.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 countsr.value_counts() |
Output :
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