Working with Python – Map, Filter and Reduce Function

Introduction

In this blog post, we are trying to discuss about Map, Filter and Reduce function of Python. These functions are very important and please try to understand that. We are using Lambda function with that. It is important in this seance that the Map-reducing architecture of Hadoop is built on that.

Hope it will be interesting.

 

Map Function

 


 

The syntax is:

Map(function, iteration)

In the above picture a pictorial diagram is added. We have a Lit. What MAP function does, it take each element from the list and pass it to the FUNCTION. The function returns a value and replaces the item of the list with that value.

In our syntax, the Function may be a normal function or a Lambda Function and the Iteration is the List object.

 

Example with Lambda Function:

 

lst=[1,2,3,4,5]

x=list(map(lambda a: a*5, lst))

print(x)

 

[5, 10, 15, 20, 25]

 

 

Let’s analyze it.

 

x=list(map(lambda a: a*5, lst))

 

Example with Function:

 

def myfunc(a):

    return(a*5)

 

lst=[1,2,3,4,5]

x=list(map(myfunc, lst))

print(x)

 

[5, 10, 15, 20, 25]

 

Filter Function

As the name define it just filter elements from the Iteration

 


 

The syntax is:

Filter(function, iteration)

 

Example with Lambda Function:

 

lst=[1,2,3,4,5]

x=list(filter(lambda a: a>2, lst))

print(x)

 

[3, 4, 5]

 

Example with Function:

 

def myfunc(a):

    if a>2:

        return(a)

   

 

lst=[1,2,3,4,5]

x=list(filter(myfunc, lst))

print(x)

 

[3, 4, 5]

 

Reduce Function

It just returns a Single value.

 


 

The syntax is:

Reduce(function, iteration)

 

Example with Lambda Function:

 

from functools import reduce

lst=[1,2,3]

x=list(reduce(lambda a:a*a, lst))

print(x)

 

à6

 

Example with Function:

 

def myfunc(a):

    return(a*a)

   

   

from functools import reduce

lst=[1,2,3]

x=list(reduce(myfunc, lst))

print(x)

 

à6

 

 

 

 

Hope you like it.


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