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Python – Check If All Elements in List are False

In this tutorial, we will look at how to check if all the elements in a list are False or not in Python with the help of some examples.

How to check if all the list items are False?

You can use the Python built-in all() function to check if all the elements in a list are False or not by comparing each value in the list with the boolean value False.

check if all elements in list are false

The all() function takes in an iterable as an argument and returns True if all the values in the iterable are truthy (represent True in a boolean context).

So, to check if all the values in a given list are False or not, use the all() function to check if each value in the list is equal to False. The following is the syntax –

# check if all the list values are False
all(val == False for val in ls)

It returns True if all the values in the list are equal to False.

Note that there are other methods as well that you can use to check if all list values are False or not. For example –

  • Iterate through the list and keep a count of values that are False. If this count is the same as the length of the list, you can say that all values are False.

Examples

Let’s now look at some examples of using the above methods. First, we will create a few lists that we’ll use to demonstrate the methods.

# list with all False values
ls1 = [False, False, False, False]
# list with not all values True
ls2 = [False, True, False, True]
# empty list
ls3 = []

# display the lists
print(ls1)
print(ls2)
print(ls3)

Output:

[False, False, False, False]
[False, True, False, True]
[]

Here, we created three lists – ls1, ls2, and ls3. The list ls1 contains only False values as its elements. The list ls2 has repeated values but not all values are False and the list ls3 is empty (it does not contain any elements).

Example 1 – Check if all the list elements are False using all()

The idea here is to use the all() function to check if each list element is equal to the boolean value False.

You can use a list comprehension to create a list of boolean values – whether a list element is equal to False or not and then pass this resulting list as an argument to the all() function.

Let’s apply this to the lists ls1 and ls2 created above.

# check if all values in list are False
print(all([val == False for val in ls1]))
print(all([val == False for val in ls2]))

Output:

True
False

We get True for ls1 and False for ls2.

If you apply this method to an empty list, you’ll get True as the output.

print(all([val == False for val in ls3]))

Output:

True

Note that the all() takes an iterable as an argument, you can directly use an iterator (without using a list comprehension).

# check if all list values are False
print(all(val == False for val in ls1))
print(all(val == False for val in ls2))
print(all(val == False for val in ls3))

Output:

True
False
True

We get the same results as above.

Example 2 – Check if all list elements are False using a for loop

The idea, here, is to iterate through the list and keep a count of False values in the list. If the resulting count is the same as the length of the list, we can say that all the values in the list are False.

def all_list_elements_false(ls):
    count = 0
    for val in ls:
        if val == False:
            count += 1
    return count == len(ls)

# check if all list values are False
print(all_list_elements_false(ls1))
print(all_list_elements_false(ls2))
print(all_list_elements_false(ls3))

Output:

True
False
True

We get True for ls1 and False for ls2. Note that here we get True for an empty list.

Summary

In this tutorial, we looked at some different methods to check if all the values in a list are False or not. The following are the different methods covered –

  • Use the Python built-in all() function to check if each list element is equal to False.
  • Iterate through the list elements and track the count of values that are equal to False and then compare this count with the length of the list.

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Author

  • Piyush

    Piyush is a data scientist passionate about using data to understand things better and make informed decisions. In the past, he's worked as a Data Scientist for ZS and holds an engineering degree from IIT Roorkee. His hobbies include watching cricket, reading, and working on side projects.