Python map, filter and reduce

In Python, the map(), filter(), and reduce() functions are built-in functions that are used to perform operations on lists and other iterable objects.

Map

map() function applies a given function to all items of an input list and returns a new list with the modified items. The basic syntax of the map function is as follows:

1Syntax:
2map(function, iterable)

Here is an example of using the map() function to square all the numbers in a list:

1Syntax:
2numbers = [1, 2, 3, 4, 5]
3squared_numbers = list(map(lambda x: x**2, numbers))
4print(squared_numbers) # [1, 4, 9, 16, 25]

The map() function applies a given function to all items of an input list.

Filter

filter() function filters the items of an input list based on a given function and returns a new list with the items that pass the filter. The basic syntax of the filter function is as follows:

1Syntax:
2filter(function, iterable)

Here is an example of using the filter() function to get even numbers from a list:

1numbers = [1, 2, 3, 4, 5]
2even_numbers = list(filter(lambda x: x % 2 == 0, numbers))
3print(even_numbers) # [2, 4]

filter() function filters the items of an input list based on a given function.

Reduce

reduce() function applies a given function cumulatively on the items of an input list and returns a single value. The basic syntax of the reduce function is as follows:

1syntax:
2reduce(function, iterable)

Here is an example of using the reduce() function to find the product of all the numbers in a list:

1from functools import reduce
2numbers = [1, 2, 3, 4, 5]
3product = reduce(lambda x, y: x+y, numbers)
4print(product) # 15

reduce() function applies a given function cumulatively on the items of an input list and returns a single value.