Python Map & Filter Functions -DevSkrol

Asha Ponraj

3 min readNov 27, 2021

Map

Map is a built-in function in python. It is used for transformation of the objects in a list or tuple.

Map function iterates through a list or tuple (iterable objects) implicitly and applies a function in each element.

Returns a map value.

It takes 2 arguments:

Function to be applied
Iterable Object

Lets take an example. There is a list of pet animals and birds. We need to convert all the string values in the list to uppercase.

Without using Map:

pets = ['Cat','Dog','Parrot','Ant','Bird']uppercase = []for names in pets:    name_upper = names.upper()    uppercase.append(name_upper)print(uppercase)Output:['CAT', 'DOG', 'PARROT', 'ANT', 'BIRD']

With Map:

myfriends = ['Cat','Dog','Parrot','Ant','Bird'] 
uppercase = list(map(str.upper,myfriends)) 
print(uppercase)Output:['CAT', 'DOG', 'PARROT', 'ANT', 'BIRD']

In the map function, we sent the first argument as a function str.upper. The second argument is an iterable object on which the function to be applied.

Another example: Lets say we have a list of bill price values. We need to round the values.

floatNum = [4.77,2.33,9.02,10.67,0.66,4.67] 
print(floatNum) 
intNew = list(map(round,floatNum)) 
print(intNew)Output:[4.77, 2.33, 9.02, 10.67, 0.66, 4.67] 
[5, 2, 9, 11, 1, 5]

Filter

The Filter function applies a boolean function to each item of the iterable object and return the items only if the function returns True for it.

Init signature: filter(self, /, *args, **kwargs)
Docstring: filter(function or None, iterable) -> filter object
Return an iterator yielding those items of iterable for which function(item) is true.
If function is None, return the items that are true.
It is similar to map but the only difference is that, filter will return the element of list only if the condition is true.

Without Filter:

Lets say we have a list of people’s age. We need to filter only the age that is eligible for voting (> 18).

# Prints the age which is >= 18#Filter ages without filter() functionage_list = [15,18,45,90,5]def eligibility_vote(age):    return age >= 18for age in age_list:    if(eligibility_vote(age)):        print(age)Output:18 45 90

With Filter Function:

#With Filter 
age_list = [15,18,45,90,5] 
def eligibility_vote(age): 
    return age >= 18 list(filter(eligibility_vote, age_list))Output:[18, 45, 90]

What if the function is not a Boolean function?

It process the function but returns all the elements as it is.

As Filter function is not a transformation function, it will not change the items of the iterable object. It will just filter the items if the function is a Boolean function.

#Filter
age_list = [15,18,45,90,5]
 
def eligibility_vote_all(age):
    if age >= 18:
        return age * 10
    else:
        return age * 10
 
#Without Filter
for age in age_list:
    if(eligibility_vote_all(age)):
        print(age)
         
new_list = list(filter(eligibility_vote_all,age_list))
print(new_list)Output:15 
18 
45 
90 
5 
[15, 18, 45, 90, 5]

Another Example:

words = ['Myth','Eat','Cry','Mass']
vowels = ['a','e','i','o','u']
 
def withVowel(a):
    for c in a:
        if c in vowels:
            return True        
    return False
     
list(filter(withVowel,words))Output:['Eat', 'Mass']

Filter Vs Map In terms of for loops:

Filter returns the value only if the boolean function returns True.
Map function applies a function to all the items regardless of the return value of the function and creates a new iterable object with the result.

Map:

list(map(eligibility_vote,age_list))Output:[False, True, True, True, False]

Filter:

list(filter(eligibility_vote,age_list))Output:[18, 45, 90]

If you would like to check other data structures in Python with examples, please visit the Python Tutorials from devskrol. You can also check the entire Basic Python Tutorial in devskrol.

Originally published at https://devskrol.com on November 27, 2021.