Python Map, Filter, Zip and Reduce by examples

Ndamulelo Nemakhavhani

Nov 1, 2018·2 min read

These functions can save you a lot of time when working with iterables ,e.g Sets, Lists, Strings etc.

MAP

1. Example 1

• Say you want to perform a min-max normalization all entries in your list

Syntax: map( function, iterable(s) )

arr = [ 32,11,55,21,9]normal = map( lambda x: (x - min(arr))/ (max(arr) -min(arr)), arr)normal = list(normal)// Output: [0.5, 0.043478260869565216, 1.0, 0.2608695652173913, 0.0]

• Note that in this case, we used a lambda function that applies our normalization formula to each element in the list.

Filter

Use filter to extract values that meet certain conditions in an iterable.

1. Example 1

• Say you want to return all even values in a list

list_ = [4,7,9,1]even_vals = filter( lambda x: x % 2 == 0, list_ )event_vals = list(even_vals)// Outputs: [ 4 ] 

• Note: You can also apply filter to more than one iterable if required.

ZIP

• With zip you can combine multiple iterables into one data structure

1. Example

• Map player names to their scores in the last two games

names = [ “Ja”, “Beel”, “Madison”]last_game = [1,4,9]previous_game = [3,4,5]player_performance = list( zip( names, last_game, previous_game ) )// Output: ('Ja', 1, 3), ('Beel', 4, 4), ('Madison', 9, 5)]

• The elements with the same index are grouped together

Reduce

• Reduce allows you to perform cumulative tasks on your iterables.

1. Example

• Calculate the product of all entries in a list

list_b = [ 1,3,2,5]product = reduce( lambda a, b: a* b , list_b)// product >> 30

References

1. https://docs.python.org/2/tutorial/datastructures.html
2. https://www.geeksforgeeks.org/zip-in-python/