Start by identifying the number of digits that precede the nth digit using cumulative counts. Apply binary search over digit-length groups to locate the exact number containing the nth digit. Finally, extract the correct digit by converting to string or computing offsets mathematically, ensuring a direct mapping from sequence position to digit.
Problem Statement
You are given a positive integer n and must return the nth digit in the infinite integer sequence formed by concatenating all positive integers: 123456789101112... The challenge is to locate the digit without generating the entire sequence, using math and digit counting.
For example, if n = 3, the output is 3. If n = 11, the output is 0 because the 11th digit corresponds to the second digit of 10 in the sequence. Constraints ensure n is within 1 and 2^31 - 1, requiring an efficient solution.
Examples
Example 1
Input: n = 3
Output: 3
Example details omitted.
Example 2
Input: n = 11
Output: 0
The 11th digit of the sequence 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, ... is a 0, which is part of the number 10.
Constraints
- 1 <= n <= 231 - 1
Solution Approach
Count digit ranges to locate the target group
Compute how many digits exist in 1-digit numbers, 2-digit numbers, etc., cumulatively until the range containing the nth digit is found. This sets the boundaries for binary search over the valid answer space.
Binary search within the digit-length group
Once the correct digit-length group is determined, use binary search over the numbers in that range to pinpoint the exact number that contains the nth digit. Calculate offsets carefully to avoid off-by-one errors.
Extract the exact digit
After identifying the target number, determine the position of the nth digit within it. Convert the number to a string or use mathematical division and modulus to return the correct single digit efficiently.
Complexity Analysis
| Metric | Value |
|---|---|
| Time | Depends on the final approach |
| Space | Depends on the final approach |
Time complexity is O(log n) due to binary search over digit-length ranges and numbers within the range. Space complexity is O(1) if using math, or O(log n) if string conversion is employed.
What Interviewers Usually Probe
- Candidate tries to generate the sequence directly instead of using counting or binary search.
- Candidate struggles to compute cumulative digit counts for each digit length.
- Candidate miscalculates offsets when mapping n to the correct digit within the target number.
Common Pitfalls or Variants
Common pitfalls
- Attempting to build the full sequence, which is infeasible for large n.
- Off-by-one errors when computing cumulative counts or digit offsets.
- Forgetting that multi-digit numbers contribute multiple digits, leading to wrong indexing.
Follow-up variants
- Find the nth digit for sequences of even numbers only.
- Return the nth digit in the concatenation of squares of integers.
- Compute the nth digit for a custom base sequence rather than decimal.
How GhostInterview Helps
- Automatically identifies the correct digit-length group and calculates offsets, removing manual error.
- Guides through binary search over numbers in the range without generating full sequences.
- Ensures accurate extraction of the digit using optimized math or string operations for large n.
Topic Pages
Related GhostInterview Pages
- LeetCode Interview Copilot - Use GhostInterview as a live solver when you want direct help with LeetCode-style coding questions.
- Coding Interview Assistant - See how GhostInterview supports array, string, linked list, graph, and tree interview workflows.
- How GhostInterview Works - Review the screenshot, reasoning, and answer flow before using the solver in a live interview.
FAQ
What is the main pattern used in the Nth Digit problem?
The main pattern is binary search over the valid answer space combined with cumulative digit counting.
How do I avoid off-by-one errors when locating the nth digit?
Carefully track the cumulative digit count and use zero-based indexing consistently when mapping n to the exact number and digit.
Can I generate the sequence up to n to solve this problem?
No, generating the full sequence is infeasible for large n due to memory and time constraints; counting and binary search are required.
What is the time complexity of the optimal solution?
Time complexity is O(log n), mainly from the binary search over digit-length groups and numbers within the target range.
Does this approach work for sequences other than natural numbers?
Yes, with adjustments, the same pattern of cumulative counting and binary search can locate digits in sequences of squares, evens, or other arithmetic sequences.
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