Python Program to Find Average of List

To find the average of a list in Python, use average = sum(your_list) / len(your_list) where sum() adds all numbers and len() counts them.

Examples

Input[10, 20, 30]

Output20.0

Input[5, 15, 25, 35]

Output20.0

Input[100]

Output100.0

How to Think About It

To find the average, first add all the numbers in the list to get the total sum. Then count how many numbers are in the list. Finally, divide the total sum by the count to get the average value.

Algorithm

1

Get the list of numbers.

2

Calculate the sum of all numbers in the list.

3

Count how many numbers are in the list.

4

Divide the sum by the count to get the average.

5

Return or print the average.

Code

python

numbers = [10, 20, 30]
average = sum(numbers) / len(numbers)
print(average)

Output

20.0

Dry Run

Let's trace the list [10, 20, 30] through the code

1

List input

numbers = [10, 20, 30]

2

Calculate sum

sum(numbers) = 10 + 20 + 30 = 60

3

Count elements

len(numbers) = 3

4

Calculate average

average = 60 / 3 = 20.0

5

Print result

print(average) outputs 20.0

Step	Sum	Count	Average
Initial	-	-	-
Sum calculation	60	-	-
Count calculation	-	3	-
Average calculation	-	-	20.0

Why This Works

Step 1: Sum all numbers

The sum() function adds all numbers in the list to get the total.

Step 2: Count numbers

The len() function counts how many numbers are in the list.

Step 3: Divide sum by count

Dividing the total sum by the count gives the average value.

Alternative Approaches

Using a loop to calculate sum

python

numbers = [10, 20, 30]
total = 0
for num in numbers:
    total += num
average = total / len(numbers)
print(average)

This method is more manual but helps understand how sum works internally.

Using statistics.mean() function

python

import statistics
numbers = [10, 20, 30]
average = statistics.mean(numbers)
print(average)

This uses a built-in function designed for averages, making code cleaner.

Complexity: O(n) time, O(1) space

Time Complexity

Calculating the sum requires visiting each element once, so it takes O(n) time where n is the number of elements.

Space Complexity

The calculation uses a fixed amount of extra space regardless of input size, so it is O(1).

Which Approach is Fastest?

Using built-in sum() is usually fastest and simplest; manual loops are slower but educational; statistics.mean() is clean and reliable.

Approach	Time	Space	Best For
Built-in sum()/len()	O(n)	O(1)	Simple and fast for all lists
Manual loop sum	O(n)	O(1)	Learning how summing works
statistics.mean()	O(n)	O(1)	Clean code and extra stats features