Flatten List

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JCSU Unit 2 Problem Set 1 (Click for link to problem statements)

Problem Highlights

• 💡 Difficulty: Easy
• ⏰ Time to complete: 10 mins
• 🛠️ Topics: Nested Loops, Iteration, List Flattening

1: U-nderstand

Understand what the interviewer is asking for by using test cases and questions about the problem.

• Established a set (2-3) of test cases to verify their own solution later.
• Established a set (1-2) of edge cases to verify their solution handles complexities.
• Have fully understood the problem and have no clarifying questions.
• Have you verified any Time/Space Constraints for this problem?

• What is the goal of the problem?
  • The goal is to flatten a list of lists into a single list containing all elements in the same order.
• Are there constraints on input?
  • The input will always be a list of lists.

HAPPY CASE Input: nested_list = [ [1, 2], [3, 4], [5, 6] ] Output: [1, 2, 3, 4, 5, 6] Explanation: The nested list is flattened to a single list containing all elements.

EDGE CASE Input: nested_list = def flatten_list(nested_list): flattened = [] # Initialize an empty list to store the flattened elements for sublist in nested_list: # Iterate through each sublist in the nested list for element in sublist: # Iterate through each element in the sublist flattened.append(element) # Append the element to the flattened list return flattened # Return the flattened list--%23%23-5%3A-R-eview----%2A%2AReview%2A%2A-the-code-by-running-specific-example%28s%29-and-recording-values-%28watchlist%29-of-your-code%27s-variables-along-the-way.--Example-1%3A---Input%3A-nested_list-%3D-%5B-%5B1%2C-2%5D%2C-%5B3%2C-4%5D%2C-%5B5%2C-6%5D-%5D---Expected-Output%3A-%5B1%2C-2%2C-3%2C-4%2C-5%2C-6%5D---Observed-Output%3A-%5B1%2C-2%2C-3%2C-4%2C-5%2C-6%5D--Example-2%3A---Input%3A-nested_list-%3D-%5B%5B##-2:-M-atch----**Match**-what-this-problem-looks-like-to-known-categories-of-problems,-e.g.-Linked-List-or-Dynamic-Programming,-and-strategies-or-patterns-in-those-categories.--For-**list-flattening-problems**,-we-want-to-consider-the-following-approaches:----**Nested-Loops:**-Use-a-nested-loop-to-iterate-through-each-sublist-and-extract-elements.---**List-Comprehension:**-Use-Python-list-comprehensions-for-concise-syntax-(alternative-solution).--##-3:-P-lan----**Plan**-the-solution-with-appropriate-visualizations-and-pseudocode.--**General-Idea:**---Iterate-through-each-sublist-in-the-nested-list,-and-then-iterate-through-each-element-in-the-sublist.-Append-all-elements-to-a-new-list-in-order.--###-Steps:--1.-Initialize-an-empty-list-`flattened`-to-store-the-flattened-elements.-2.-For-each-sublist-in-the-input-`nested_list`:-------For-each-element-in-the-sublist:-----------Append-the-element-to-`flattened`.-3.-Return-the-`flattened`-list.--##-4:-I-mplement----**Implement**-the-code-to-solve-the-algorithm.--

def flatten_list(nested_list):
    flattened = []  # Initialize an empty list to store the flattened elements
    for sublist in nested_list:  # Iterate through each sublist in the nested list
        for element in sublist:  # Iterate through each element in the sublist
            flattened.append(element)  # Append the element to the flattened list
    return flattened  # Return the flattened list

def flatten_list(nested_list):
    flattened = []  # Initialize an empty list to store the flattened elements
    for sublist in nested_list:  # Iterate through each sublist in the nested list
        for element in sublist:  # Iterate through each element in the sublist
            flattened.append(element)  # Append the element to the flattened list
    return flattened  # Return the flattened list

• Expected Output: []
• Observed Output: []

6: E-valuate

Evaluate the performance of your algorithm and state any strong/weak or future potential work.

Assume n is the total number of elements in all sublists.

• Time Complexity: O(n) because we iterate through each element exactly once.
• Space Complexity: O(n) because we create a new flattened list to store all elements.