5 Best Ways to Find the Kth Missing Number From a List in Python

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πŸ’‘ Problem Formulation: The challenge is to write a program that identifies the kth missing number in a sequential dataset. For example, given a list of [2, 3, 7, 9] and k=1, the desired output is ‘4’, which is the first missing element from the consecutive sequence starting from the first element in the list.

Method 1: Straightforward Iteration

This method involves iterating over the range of numbers spanned by the list and counting missing numbers until reaching the kth absence. It’s simple to implement and understand, making it perfect for smaller lists or when performance is not a critical concern.

Here’s an example:

def find_kth_missing(lst, k):
    missing_numbers = []
    current = lst[0]
    while len(missing_numbers) < k:
        if current not in lst:
        current += 1
    return missing_numbers[-1]

# Example usage
print(find_kth_missing([2, 3, 7, 9], 1))

Output: 4

This code defines a function find_kth_missing() which iterates through numbers starting from the first element in the given list. If a number is not found in the list, it’s added to the missing_numbers list until the kth missing number is identified and returned.

Method 2: Using Set Difference

This approach leverages Python’s set operations to quickly find missing elements. It’s efficient and concise, especially for large lists where direct iteration would be too slow.

Here’s an example:

def find_kth_missing_set(lst, k):
    full_set = set(range(lst[0], lst[-1] + 1))
    missing = list(full_set - set(lst))
    return missing[k - 1] if k <= len(missing) else None

# Example usage
print(find_kth_missing_set([2, 3, 7, 9], 1))

Output: 4

Here, find_kth_missing_set() uses set difference to find all missing numbers between the smallest and largest element in lst. It then retrieves the kth missing number if it exists, otherwise returns None.

Method 3: Binary Search

Binary Search offers a more performance-oriented means to find the kth missing number in a sorted list. Even for large datasets, its logarithmic time complexity provides a speedy solution.

Here’s an example:

def find_kth_missing_binary(lst, k):
    left, right = 0, len(lst) - 1
    while left <= right:
        mid = left + (right - left) // 2
        if lst[mid] - mid - lst[0] < k:
            left = mid + 1
            right = mid - 1
    return left + lst[0] + k - 1

# Example usage
print(find_kth_missing_binary([2, 3, 7, 9], 1))

Output: 4

The function find_kth_missing_binary() applies binary search to determine the position where the kth missing number would be. Once the position is found, it calculates the exact value of the kth missing number using the position and starting number.

Method 4: Counting While Traversing

This method combines linear traversal of the list with direct counting, offering a good balance between simplicity and efficiency. It is particularly useful when dealing with lists that are mostly complete, with few missing elements.

Here’s an example:

def find_kth_missing_count(lst, k):
    count, idx, current = 0, 0, lst[0]
    while count < k:
        if idx < len(lst) and lst[idx] == current:
            idx += 1
            count += 1
        if count < k: current += 1
    return current

# Example usage
print(find_kth_missing_count([2, 3, 7, 9], 1))

Output: 4

The find_kth_missing_count() function counts up from the first element in the list, incrementing a counter whenever a number is not present. When the counter matches k, it returns the current number being assessed.

Bonus One-Liner Method 5: Using List Comprehension and itertools

This method uses the power of list comprehension combined with itertools to elegantly solve the problem in a single line. Ideal for Python enthusiasts who prefer concise and readable code.

Here’s an example:

from itertools import count

def find_kth_missing_one_liner(lst, k):
    return next(x for x, y in zip(count(lst[0]), lst) if y - x >= k)

# Example usage
print(find_kth_missing_one_liner([2, 3, 7, 9], 1))

Output: 4

The one-liner find_kth_missing_one_liner() uses zip() to pair each integer in the expected range with elements from the list. It then filters for the kth position where the difference indicates a missing number using a generator expression.


  • Method 1: Straightforward Iteration. Simple and easy to grasp. Can be slow for very large lists or huge ranges of numbers.
  • Method 2: Using Set Difference. Pythonic and efficient for large lists. However, less intuitive than straightforward iteration for beginners.
  • Method 3: Binary Search. Highly efficient for sorted lists. Best suited for performance-critical applications with possibly complex code.
  • Method 4: Counting While Traversing. Balance between readability and efficiency. Works well when the list is mostly complete.
  • One-Liner Method 5: Using List Comprehension and itertools. Elegant and concise. Great for Python savants but might confound beginners.