How can you create a new list from an existing list by multiplying each element by 2?

How can you create a new list from an existing list by multiplying each element by 2?

• A. Using a for loop only
• B. Using the map() function
• C. Using list comprehension, e.g., `[x * 2 for x in old_list]`
• D. Using the append() method in a loop

Answer: (C)

Creating a new list by multiplying each element of an existing list by 2 can effectively be accomplished using list comprehension. This approach is concise and directly expresses the intention to transform each element of the list. When you use list comprehension like `[x * 2 for x in old_list]`, you are iterating over each element `x` in `old_list` and applying the operation `x * 2` to it. This construct neatly encapsulates the logic of mapping each item to a new value and collecting the results into a new list. Therefore, it is both efficient and easy to read, aligning well with Python’s design philosophy favoring readability and simplicity. Other methods, such as using a for loop only, the `map()` function, or the `append()` method in a loop, could achieve similar results. However, they tend to be less straightforward. For instance, a for loop would require initializing an empty list and explicitly appending each calculated value, making it more verbose. The `map()` function would apply a function to each element but would require further conversion to a list if a list output is desired, making it slightly less intuitive. Using the `append()` method in a loop can also yield the desired list but is

Creating a new list by multiplying each element of an existing list by 2 can effectively be accomplished using list comprehension. This approach is concise and directly expresses the intention to transform each element of the list.

When you use list comprehension like [x * 2 for x in old_list], you are iterating over each element x in old_list and applying the operation x * 2 to it. This construct neatly encapsulates the logic of mapping each item to a new value and collecting the results into a new list. Therefore, it is both efficient and easy to read, aligning well with Python’s design philosophy favoring readability and simplicity.

Other methods, such as using a for loop only, the map() function, or the append() method in a loop, could achieve similar results. However, they tend to be less straightforward. For instance, a for loop would require initializing an empty list and explicitly appending each calculated value, making it more verbose. The map() function would apply a function to each element but would require further conversion to a list if a list output is desired, making it slightly less intuitive. Using the append() method in a loop can also yield the desired list but is