Python

Typeerror nonetype object is not subscriptable : How to Fix ?

It is very common to encounter this python error typeerror nonetype object is not subscriptable. If you are facing the challenge to fix it, You will get the solution here.

Typeerror nonetype object is not subscriptable ( Root Cause):

There are few objects like list, dict , tuple are iterable in python. But the error “Typeerror nonetype object is not subscriptable” occurs when they have None values and Python code access them via index or subscript. Firstly, Let’s understand with some code examples.

sample_list=None
print(sample_list[0])

Let’s run and see its output.

 

Typeerror nonetype object is not subscriptable ( Solution):

The solution/Fix for this error is in the error statement itself. But we will address them using the scenarios.

Function return type None at assignment

There are so many functions in python which change the elements like list, dict, etc in place and return None. Due to some misunderstanding, we assign them to some different objects. Which becomes None. When we try to access them via an index. It gives us the same error None type object is not subscriptable.

sample_list=[1,3,2,5,8,7]
new_list=sample_list.sort()
print(new_list[0])

Here we know that the sort function returns None But the code looks like it will return the sorted list. When we try to access their element using a subscript. It throws the same error.

The correct way of doing is to call those function which returns the None prior to the assignment. Refer to the below code for understanding it.

NoneType object error Fix Code

There can be an uncountable scenario where None type iterable accessed via index. Covering all of them will not be a good idea. Hence the best way to understand the root cause behind the error and apply the solution as per the use case.

Conclusion –

Well, This is a very common error for python beginners. Anyway, I hope this article must solve your problem. In fact, we encounter this error in different scenarios but the root cause will always be the same.

Thanks

Data Science Learner Team