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Python Program to Make a Flattened List from Nested List

In this example, you will learn to make a flattened list from a nested list in Python.

To understand this example, you should have the knowledge of the following Python programming topics:


Example 1: Using List Comprehension

my_list = [[1], [2, 3], [4, 5, 6, 7]]

flat_list = [num for sublist in my_list for num in sublist]
print(flat_list)

Output

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

This is one of the simplest pythonic ways of flattening a list.

  • Using list comprehension access the sublist from my_list, then access each element of the sublist.
  • Each element num is stored in flat_list.

Learn more about list comprehension at Python List Comprehension.


Example 2: Using Nested for Loops (non pythonic way)

my_list = [[1], [2, 3], [4, 5, 6, 7]]

flat_list = []
for sublist in my_list:
    for num in sublist:
        flat_list.append(num)

print(flat_list)

Output

[1, 2, 3, 4, 5, 6, 7]
  • Create an empty list flat_list.
  • Access each element of the sublist using a nested loop and append that element to flat_list.

Example 3: Using itertools package

import itertools

my_list = [[1], [2, 3], [4, 5, 6, 7]]

flat_list = list(itertools.chain(*my_list))
print(flat_list)

Output

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

Using itertools module, we can create a flattened list.

  • chain() method from itertools module returns each element of each iterable (i.e. sub lists ).
  • list() converts those returned values into a list.

Example 4: Using sum()

my_list = [[1], [2, 3], [4, 5, 6, 7]]

flat_list = sum(my_list, [])
print(flat_list)

Output

[1, 2, 3, 4, 5, 6, 7]
  • Provide two arguments to the sum() method: my_list and an empty list (i.e. [ ]).
  • sum() combines my_list and [ ] to produce a flattened list.

Example 5: Using lambda and reduce()

from functools import reduce

my_list = [[1], [2, 3], [4, 5, 6, 7]]
print(reduce(lambda x, y: x+y, my_list))

Output

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

In the above example, reduce() applies the lambda function to all the elements of my_list.

Learn more about lambda expressions at Python Anonymous/Lambda Function.

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