What are the functions map(), filter(), reduce()?

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Kirill Smirnov

Data Science Consultant, Altran

map()

map(                                                )
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map()

map(                       Iterable1, Iterable2, ...)

Iterables: [1, 2, 3, 4, 5], [10, 20, 30, 40, 50], ...

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map()

map(function(x1, x2, ...), Iterable1, Iterable2, ...)

Iterables: [1, 2, 3, 4, 5], [10, 20, 30, 40, 50], ...

1, 10, ... $\rightarrow$ function(1, 10, ...) $\rightarrow$ new object

2, 20, ... $\rightarrow$ function(2, 20, ...) $\rightarrow$ new object

3, 30, ... $\rightarrow$ function(3, 30, ...) $\rightarrow$ new object

4, 40, ... $\rightarrow$ function(4, 40, ...) $\rightarrow$ new object

5, 50, ... $\rightarrow$ function(5, 50, ...) $\rightarrow$ new object

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map() with single Iterable

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

The task is to get [1, 4, 9, 16, 25]

def squared(x):
    return x**2

squares = map(squared, nums)

print(squares)

<map object at 0x7fdbe4ab3da0>

squares is iterable

for square in squares:
    print(square)

1
4
9
16
25
Esercitarsi con le domande di colloquio di coding in Python

map() with single Iterable

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

The task is to get [1, 4, 9, 16, 25]

def squared(x):
    return x**2

squares = map(squared, nums)

print(squares)

<map object at 0x7fdbe4ab3da0>

squares is Iterable

list(squares)

[1, 4, 9, 16, 25]
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map() with single Iterable

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

The task is to get [1, 4, 9, 16, 25]

def squared(x):
    return x**2

squares = map(squared, nums)

print(squares)

<map object at 0x7fdbe4ab3da0>

squares is Iterator

next(squares)

1

next(squares)

4
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map() with lambda expressions

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

The task is to get [1, 4, 9, 16, 25]

def squared(x):
    return x**2

squares = map(squared, nums)
list(squares)

[1, 4, 9, 16, 25]

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

The task is to get [1, 4, 9, 16, 25]

squares = map(lambda x: x**2, nums)
list(squares)

[1, 4, 9, 16, 25]
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map() with multiple Iterables

nums1 = [1, 2, 3, 4, 5]
nums2 = [10, 20, 30, 40, 50]

The task is to get: [1*10, 2*20, 3*30, 4*40, 5*50] = [10, 40, 90, 160, 250]

mult = map(lambda x, y: x*y, nums1, nums2)

list(mult)

[10, 40, 90, 160, 250]
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filter()

filter(                     )
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filter()

filter(             Iterable)

Iterable: [1, 2, 3, 4, 5]

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filter()

filter(function(x), Iterable)

Iterable: [1, 2, 3, 4, 5]

1 $\rightarrow$ function(1) $\rightarrow$ True $\rightarrow$ 1 is kept

2 $\rightarrow$ function(2) $\rightarrow$ False $\rightarrow$ 2 is rejected

3 $\rightarrow$ function(3) $\rightarrow$ True $\rightarrow$ 3 is kept

4 $\rightarrow$ function(4) $\rightarrow$ False $\rightarrow$ 4 is rejected

5 $\rightarrow$ function(5) $\rightarrow$ True $\rightarrow$ 5 is kept

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filter() example

nums = [-3, -2, -1, 0, 1, 2, 3]

The task is to get: [1, 2, 3]

def positive(x):
    return x > 0

fobj = filter(positive, nums)

print(fobj)

<filter object at 0x7f196d378d68>

fobj is Iterable

for item in fobj:
    print(item)

1
2
3
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filter() example

nums = [-3, -2, -1, 0, 1, 2, 3]

The task is to get: [1, 2, 3]

def positive(x):
    return x > 0

fobj = filter(positive, nums)

print(fobj)

<filter object at 0x7f196d378d68>

fobj is Iterable

list(fobj)

[1, 2, 3]
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filter() example

nums = [-3, -2, -1, 0, 1, 2, 3]

The task is to get: [1, 2, 3]

def positive(x):
    return x > 0

fobj = filter(positive, nums)

print(fobj)

<filter object at 0x7f196d378d68>

fobj is Iterator

next(fobj)

1

next(fobj)

4
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filter() with lambda expressions

nums = [-3, -2, -1, 0, 1, 2, 3]

The task is to get: [1, 2, 3]

def positive(x):
    return x > 0

fobj = filter(positive, nums)
list(fobj)

[1, 2, 3]

nums = [-3, -2, -1, 0, 1, 2, 3]

The task is to get: [1, 2, 3]

fobj = filter(lambda x: x > 0, nums)
list(fobj)

[1, 2, 3]
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reduce()

from functools import reduce

reduce(function(x, y), Iterable)

Iterable: [1, 2, 3, 4, 5]

[1, 2, 3, 4, 5] $\rightarrow$ new object of the same type as the content

The representation of the given list

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reduce()

from functools import reduce

reduce(function(x, y), Iterable)

Iterable: [1, 2, 3, 4, 5]

[1, 2, 3, 4, 5] $\rightarrow$ new object of the same type as the content

Combining the first two elements in the list

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reduce()

from functools import reduce

reduce(function(x, y), Iterable)

Iterable: [1, 2, 3, 4, 5]

[1, 2, 3, 4, 5] $\rightarrow$ new object of the same type as the content

Combining the output with the third element in the list

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reduce()

from functools import reduce

reduce(function(x, y), Iterable)

Iterable: [1, 2, 3, 4, 5]

[1, 2, 3, 4, 5] $\rightarrow$ new object of the same type as the content

Combining the output with the fourth element in the list

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reduce()

from functools import reduce

reduce(function(x, y), Iterable)

Iterable: [1, 2, 3, 4, 5]

[1, 2, 3, 4, 5] $\rightarrow$ new object of the same type as the content

Combining the output with the fifth element in the list

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reduce() example

nums = [8, 4, 5, 1, 9]

The task is to get: 1 - minimum 

def smallest(x, y):
    if x < y:
        return x
    else:
        return y

reduce(smallest, nums)

1

smallest(8, 4) $\rightarrow$ 4

smallest(4, 5) $\rightarrow$ 4

smallest(4, 1) $\rightarrow$ 1

smallest(1, 9) $\rightarrow$ 1 - final result

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reduce() with lambda expressions

nums = [8, 1, 4, 2, 9]

The task is to get: 1 - minimum 

def smallest(x, y):
    if x < y:
        return x
    else:
        return y

reduce(smallest, nums)

1

nums = [8, 1, 4, 2, 9]

The task is to get: 1 - minimum

reduce(lambda x, y: x if x < y else y, nums)

1
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Let's practice!

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