Python Filtering Fundamentals

Filtering is a fundamental operation in programming, allowing you to select specific elements from a collection based on certain criteria. This challenge will test your ability to implement filtering logic in Python, a skill crucial for data processing, list manipulation, and creating more dynamic applications.

Problem Description

Your task is to implement a function called filter_list that takes two arguments:

data: A list of numbers.
condition: A function that accepts a single number as input and returns True if the number meets a specific condition, and False otherwise.

The filter_list function should return a new list containing only the numbers from the original data list for which the condition function returns True. The order of elements in the output list should be the same as their order in the input data list.

Key Requirements:

The function must accept a list of numbers and a function as arguments.
The function must return a new list. It should not modify the original data list.
The filtering logic should be applied using the provided condition function.

Expected Behavior: The function should iterate through each element in the data list. For each element, it should call the condition function. If the condition function returns True, the element should be added to the new result list.

Edge Cases:

An empty input data list.
A condition function that always returns True or always returns False.
A data list containing various types of numbers (integers, floats).

Examples

Example 1:

Input:
data = [1, 2, 3, 4, 5, 6]
condition = lambda x: x % 2 == 0  # Filter for even numbers

Output:
[2, 4, 6]

Explanation:
The condition checks if a number is even. The numbers 2, 4, and 6 are even, so they are included in the output list.

Example 2:

Input:
data = [10, -5, 0, 25, -15, 30]
condition = lambda x: x > 0  # Filter for positive numbers

Output:
[10, 25, 30]

Explanation:
The condition checks if a number is greater than 0. The numbers 10, 25, and 30 satisfy this condition.

Example 3:

Input:
data = [1.5, 2.7, 0.9, 3.14, 4.0]
condition = lambda x: x < 3.0  # Filter for numbers less than 3.0

Output:
[1.5, 2.7, 0.9]

Explanation:
The condition checks for numbers less than 3.0. The numbers 1.5, 2.7, and 0.9 meet this criterion.

Example 4: (Edge Case: Empty List)

Input:
data = []
condition = lambda x: x > 10

Output:
[]

Explanation:
When the input list is empty, the function should return an empty list, regardless of the condition.

Constraints

The data list will contain only numeric types (integers and/or floats).
The condition function will always be a valid Python function that accepts one numeric argument and returns a boolean.
The length of the data list can range from 0 to 1000.
The values within the data list will be within the range of -1000 to 1000.
Your solution should aim for reasonable efficiency, ideally performing the filtering in a single pass through the data.

Notes

Consider using a loop to iterate through the data list.
Remember to create and return a new list.
Python's built-in filter() function is an alternative way to achieve this, but for this challenge, you should implement the logic manually to deepen your understanding.