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Python List, Set and Dictionary Comprehension

Video Link: https://youtu.be/TGaKzl6p4nA

In this video, we learned to use list, set, and dictionary comprehension in Python.

Programs in the Video

List Comprehension

Before we learn about list comprehension, let's first understand why it is used.

Suppose we have to create a list of the first five powers of 2. For this, we would normally use a for loop and append every item to the list.

numbers = []

for i in range(1, 6):
    numbers.append(2**i)

print(numbers)

Output

[2, 4, 8, 16, 32]

Wouldn't it be neat if we could do this same task in a single line?

List comprehension allows us to do exactly that.

# numbers = []

# for i in range(1, 6):
#     numbers.append(2**i)

numbers = [2**i for i in range(1, 6)]

print(numbers)

Output

[2, 4, 8, 16, 32]

This comprehension says, "Create a numbers list with elements in the form 2**i where i takes values from 1 to 5."

Conditionals in List Comprehension

List comprehensions can also have an optional if conditional along with a for loop.

import math
numbers = [49, 64, 81, 100, 121]

new_list = [math.sqrt(n) for n in numbers]

Output

[7.0, 8.0, 9.0, 10.0, 11.0]

To get square roots of only the even numbers in the numbers list:

import math
numbers = [49, 64, 81, 100, 121] 

new_list = [math.sqrt(n) for n in numbers if n % 2 == 0]
print(new_list)

Output

[8.0, 10.0]

Multiple Loops in List Comprehension

We can have more than one for loop in list comprehension:

team1 = ['Janet', 'Arya', 'Mary']
team2 = ['Evan', 'Jake', 'Randy']

new_list = [(x,y) for x in team1 for y in team2]
print(new_list)

Output

[('Janet', 'Evan'), ('Janet', 'Jake'), ('Janet', 'Randy'), ('Arya', 'Evan'), ('Arya', 'Jake'), ('Arya', 'Randy'), ('Mary', 'Evan'), ('Mary', 'Jake'), ('Mary', 'Randy')]

We can also write nested list comprehensions. It means that we can use a list comprehension inside another list comprehension.

Note: We generally write list comprehensions to simplify our code and make it easier to read, so you should avoid using list comprehensions inplace of complex and long nested for loops.

Set Comprehension

We can also use set comprehensions in Python to create sets quickly and concisely.

Its syntax is similar to that of list comprehension but we use {} instead of [].

word = "programming"
alphabets = {x for x in word}

print(alphabets)

Output

{'o', 'r', 'm', 'a', 'i', 'g', 'p', 'n'}

Dictionary Comprehension

Similar to list and set comprehension, dictionary comprehension is an elegant and concise way to create dictionaries in Python.

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

# square_dict = dict()
# for num in numbers:
#     square_dict[num] = num**2
# print(square_dict)

square_dict = {num:num**2 for num in numbers}
print(square_dict)

Output

{1: 1, 2: 4, 3: 9, 4: 16, 5: 25}

Lets try one more example:

Suppose we have a dictionary that looks like this:

old_price = {'milk': 1.02, 'coffee': 2.5, 'bread': 2.5}

We need to construct a new dictionary with new prices by increasing the price of items by 50% for those that are more than $2.

old_price = {'milk': 1.02, 'coffee': 2.3, 'bread': 2.5}

new_price = {key: value*1.5 if value>2 else value for (key, value) in old_price.items()}
print(new_price)

Output

{'milk': 1.02, 'coffee': 3.4499999999999997, 'bread': 3.75}

The above code is equivalent to:

old_price = {'milk': 1.02, 'coffee': 2.3, 'bread': 2.5}

new_price = dict()
for key, value in old_price.items():
    if value > 2:
        new_price[key] = value * 1.5
    else:
        new_price[key] = value

print(new_price)