Question

What will the following code display? numbers = [10] * 5 print(numbers)

Short answer

Answer: The output of the given code will be the list [10, 10, 10, 10, 10].

Step-by-step solution

Analyze the given code

The given Python code consists of two lines. The first line is creating a list named 'numbers', and the second line is printing the list. The list is created using the syntax [10] * 5. This syntax is operating on a list containing one element (10), and then multiplying the list by 5.

Understand the list operation

The operation [10] * 5 in Python means that the single-element list [10] is repeated 5 times. The result is a new list where this single-element list is concatenated five times.

Determine the output

Since the list [10] is repeated 5 times, the resulting list is [10, 10, 10, 10, 10]. Now that we have analyzed the code and determined the output, let's combine it in the final answer:

Output:

The output of the following code will be the list [10, 10, 10, 10, 10].

Key concepts

List Operations

In Python programming, understanding internal operations on lists is crucial for effective coding. One basic operation is replicating elements within a list. This often uses the asterisk operator (*).

For example, consider the operation `[10] * 5`. Here, `[10]` is a list with a single element, 10. The * operator repeats this entire list multiple times, based on the number that follows the asterisk. In this case, `[10]` is repeated 5 times.

• This results in the list becoming [10, 10, 10, 10, 10].
• The single-element list is concatenated with itself 5 times.
• This method is quick for creating lists with repeated elements.

Using this operation can save time, especially when you need to initialize a list with default values. It’s simple but powerful, and common in many coding scenarios like initial setups or simple data replication tasks.

Code Analysis

Breaking down lines of code systematically helps to understand what each part does and how they interact. Let's dissect the short Python code snippet from the problem statement.

First, the line `numbers = [10] * 5` assigns a value to the variable `numbers`. By analyzing it, you can see that the multiplication operator is not just replicating a number but a list. It repeats the list’s elements across a newly constructed list. This means Python's list creation handles complex data types dynamically.

• The variable `numbers` stores the result of this list operation.
• Python knows how to internally handle the replication in a way that's efficient and consistent.
• Analyzing this line shows how data can be manipulated easily in Python.

Consistently applying step-by-step code analysis like this helps you predict the behavior of your scripts and avoid common mistakes. This systematic approach is a cornerstone of understanding coding logic.

Output Prediction

Predicting output in programming involves synthesizing the knowledge of how code executes and what each part means. With our exercise, this step seems trivial, but holds great importance in developing the logic fluency.

Given the code: ``` numbers = [10] * 5 print(numbers) ``` Let's predict the output. By applying our understanding of list operations, we know that `[10] * 5` results in `[10, 10, 10, 10, 10]`. When `print(numbers)` is called, Python will display the constructed list in the console.

• This confirms that the list [10, 10, 10, 10, 10] is generated and then outputted.
• Making accurate predictions builds confidence in your coding skills.
• Output prediction tests your understanding and ensures your code does what's expected.

Mastering output prediction refines your debugging skills and is essential for seamlessly transitioning from writing code to seeing tangible results.