Nested List Comprehensions in Python

List Comprehensions are one of the most amazing features of Python. It is a smart and concise way of creating lists by iterating over an iterable object. Nested List Comprehensions are nothing but a list comprehension within another list comprehension which is quite similar to nested for loops.

Let’s take a look at some examples to understand what nested list comprehensions can do:

Example 1:

I want to create a matrix which looks like below:

matrix = [[0, 1, 2, 3, 4],
          [0, 1, 2, 3, 4],
          [0, 1, 2, 3, 4],
          [0, 1, 2, 3, 4],
          [0, 1, 2, 3, 4]]

The below code uses nested for loops for the given task:

[[0, 1, 2, 3, 4], [0, 1, 2, 3, 4], [0, 1, 2, 3, 4], [0, 1, 2, 3, 4], [0, 1, 2, 3, 4]]

The same output can be achieved using nested list comprehension in just one line:

[[0, 1, 2, 3, 4], [0, 1, 2, 3, 4], [0, 1, 2, 3, 4], [0, 1, 2, 3, 4], [0, 1, 2, 3, 4]]

Explanation:

The syntax of the above program is shown below:

[expression for i in range(5)] –> which means that execute this expression and append its output to the list until variable i iterates from 0 to 4.

For example:- [i for i in range(5)] –> In this case, the output of the expression
is simply the variable i itself and hence we append its output to the list while i
iterates from 0 to 4.

Thus the output would be –> [0, 1, 2, 3, 4]

But in our case, the expression itself is a list comprehension. Hence we need to first
solve the expression and then append its output to the list.

expression = [j for j in range(5)] –> The output of this expression is same as the
example discussed above.

Hence expression = [0, 1, 2, 3, 4].

Now we just simply append this output until variable i iterates from 0 to 4 which would
be total 5 iterations. Hence the final output would just be a list of the output of the
above expression repeated 5 times.

Output: [[0, 1, 2, 3, 4], [0, 1, 2, 3, 4], [0, 1, 2, 3, 4], [0, 1, 2, 3, 4], [0, 1, 2, 3, 4]]

Example 2:

Suppose I want to flatten a given 2-D list:

matrix = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]

Expected Output: flatten_matrix = [1, 2, 3, 4, 5, 6, 7, 8, 9]

This can be done using nested for loops as follows:

[1, 2, 3, 4, 5, 6, 7, 8, 9]

Again this can be done using nested list comprehension which has been shown below:

[1, 2, 3, 4, 5, 6, 7, 8, 9]

Explanation:

In this case, we need to loop over each element in the given 2-D list and append it
to another list. For better understanding, we can divide the list comprehension into
three parts:

flatten_matrix = [val
                  for sublist in matrix
                  for val in sublist]

The first line suggests what we want to append to the list. The second line is the
outer loop and the third line is the inner loop.

‘for sublist in matrix’ returns the sublists inside the matrix one by one which would be:

[1, 2, 3], [4, 5], [6, 7, 8, 9]

‘for val in sublist’ returns all the values inside the sublist.

Hence if sublist = [1, 2, 3], ‘for val in sublist’ –> gives 1, 2, 3 as output one by one.

For every such val, we get the output as val and we append it to the list.

Example 3:

Suppose I want to flatten a given 2-D list and only include those strings whose lengths are less than 6:

planets = [[‘Mercury’, ‘Venus’, ‘Earth’], [‘Mars’, ‘Jupiter’, ‘Saturn’], [‘Uranus’, ‘Neptune’, ‘Pluto’]]

Expected Output: flatten_planets = [‘Venus’, ‘Earth’, ‘Mars’, ‘Pluto’]

This can be done using an if condition inside a nested for loop which is shown below:

['Venus', 'Earth', 'Mars', 'Pluto']

This can also be done using nested list comprehensions which has been shown below:

['Venus', 'Earth', 'Mars', 'Pluto']

Explanation:

This example is quite similar to the previous example but in this example, we just
need an extra if condition to check if the length of a particular planet is less than
6 or not.

This can be divided into 4 parts as follows:

flatten_planets = [planet 
                   for sublist in planets 
                   for planet in sublist 
                   if len(planet) < 6]