Python | Pandas Series.agg()

Last Updated : 19 Nov, 2018

Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric python packages. Pandas is one of those packages and makes importing and analyzing data much easier.

Pandas Series.agg() is used to pass a function or list of function to be applied on a series or even each element of series separately. In case of list of function, multiple results are returned by agg() method.

Syntax: Series.agg(func, axis=0)
Parameters:
func: Function, list of function or string of function name to be called on Series.
axis:0 or ‘index’ for row wise operation and 1 or ‘columns’ for column wise operation.
Return Type: The return type depends on return type of function passed as parameter.

Example #1:
In this example, a lambda function is passed which simply adds 2 to each value of series. Since the function will be applied to each value of series, the return type is also series. A random series of 10 elements is generated by passing array generated using Numpy random method.

# importing pandas module
import pandas as pd
   
# importing numpy module
import numpy as np
   
# creating random arr of 10 elements
arr=np.random.randn(10)
   
# creating series from array
series=pd.Series(arr)
   
# calling .agg() method
result=series.agg(lambda num : num + 2) 
   
# display
print('Array before operation: \n', series,
      '\n\nArray after operation: \n',result)

Output:

As shown in output, the function was applied to each value and 2 was added to each value of series.

Example #2: Passing List of functions

In this example, a list of some Python’s default function is passed and multiple results are returned by agg() method into multiple variables.

# importing pandas module
import pandas as pd
   
# importing numpy module
import numpy as np
   
# creating random arr of 10 elements
arr=np.random.randn(10)
   
# creating series from array
series=pd.Series(arr)
   
# creating list of function names
func_list=[min, max, sorted]
   
# calling .agg() method
# passing list of functions
result1, result2, result3= series.agg(func_list) 
   
# display
print('Series before operation: \n', series)
print('\nMin = {}\n\nMax = {},\
      \n\nSorted Series:\n{}'.format(result1,result2,result3))

Output:

As shown in output, multiple results were returned. Min, Max and Sorted array were returned into different variables result1, result2, result3 respectively.

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. And to begin with your Machine Learning Journey, join the Machine Learning – Basic Level Course

My Personal Notes

Related Articles

Python | Pandas Series.agg()