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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.

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# 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)

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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.

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# 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))

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Output:

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

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