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()) |
chevron_right
filter_none
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() |
chevron_right
filter_none
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() |
chevron_right
filter_none
Output :
Attention geek! Strengthen your foundations with the Python Programming Foundation Course and learn the basics.
To begin with, your interview preparations Enhance your Data Structures concepts with the Python DS Course.
Article Contributed By :
Vote for difficulty
Article Tags :
