A list of lists
Let’s start with a simple example of converting [[0,1], [2,3]] into [0,1,2,3]. This type of flattening is called shallow flattening as it will only flatten lists of one level depth.
Using list comprehension
List comprehension is a way to create lists in one line of code. Let’s see how we can use list comprehension for flattening the lists.
flatten_list = [item for subl in l for item in subl]
Let’s break this line of code.
The first loop is “for subl in l” and the second nested loop is “ for item in subl ”.
Deep flattening
When we will try to flatten a list of varying depth like this [ [ 0, 1 ], [ [ 2 ] ][ 3, 4 ] ] list with shallow flattening, the output will be as follows:
But our goal is to convert [ [ 0, 1 ], [ [ 2 ] ], [ 3, 4 ] ] this list to this [ 0, 1, 2, 3, 4 ] list. This problem can be solved with deep flattening. In deep flattening, the process undergoes multiple levels of depths to create a flattened list.
There is a built-in function named deepflatten in the iteration_utilities library. You need to install this library using.
We have successfully achieved our target. Let’s take another example by changing the depth of the list.
Using recursion
To flatten a list recursively, we will call the function inside itself to run until the end:
Check whether the list length is equal to 1. If true, then check whether the type of the first index of the list is a “list”.if true, then call the function that flattens the list else, store the number in the result.
The function will be like this:
When we run this code against this [[0,1], [2], [3,4]] list, the results will be:
Flatten without recursion
To flatten a list without recursion, we will use a while loop until we pop all the elements from it. Take a look at the code, you will have a better understanding:
Flatten nested lists
To flatten a nested list, you can use deep flattening. For deep flattening lists within lists, use the given below code:
Also, you can use the recursive function as we did above.
A list of tuples
Flattening a list of tuples of a single depth is the same as flattening lists within lists. For shallow flattening of tuples, use the following code:
For deep flattening, a list of tuples with varying depth (nested), you can use the code given below:
Flatten 2d array
Let’s take a 2d array of 5×5 dimensions and convert it to a flattened list. Check the following code:
A list of NumPy arrays
There are three built-in functions defined in NumPy library that can convert the NumPy array into flattened lists.
numpy.ravel()
numpy.flatten()
numpy.reshape(-1)
numpy.ravel()
numpy.flatten()
numpy.reshape(-1)
The difference between these three functions is speed. The flatten function returns a copy every time it flattens the array. So, if you have a large data set, don’t use the flatten function; it’s the slower one.
Flatten JSON objects
For flattening JSON objects, there is a built-in function in the flatten_json library named flatten().
You first need to install it using pip:
pip install flatten_json
Then you can use this function in our code:
Flatten a list of objects
You can flatten a list of objects using a built-in function available in the itertools library with function name itertools.chain.from_iterable() Let’s see how to use this function:
The same operation can be achieved using list comprehension too:
Flatten a list of DataFrames
For flattening a list of DataFrames, the pandas library has a built-in function for flattening called df.concat() Let’s take a look at code:
Flatten & remove duplicates
First, we will flatten our list, then we will remove the duplicates.
For flattening the list, we will use our own flatten_without_rec() function, and then we will remove the duplicates.
Let us have a look at the code:
Flatten a dictionary into a list
You can flatten a dictionary to a list using a simple for loop:
Let us have a look at the code:
Using reduce
The reduce() function is defined in the functools library. You first need to import reduce from the functools.
Let’s take a look at the code:
We flattened lists with different shapes & types in different ways. I hope you find the tutorial useful. Keep coming back.
Thank you.
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20+ examples for flattening lists in 
