How do you solve Shift 2D Grid on LeetCode?

Shift 2D Grid (LeetCode #1260) can be solved using Brute Force or Optimal Solution. The optimal approach is Optimal Solution with O(n) time complexity and O(n) space complexity. Key insight: Shifting elements in a 2D grid can be visualized as a circular queue operation.

What is the brute force solution for Shift 2D Grid?

The brute force approach for Shift 2D Grid is Brute Force, with O(n²) time complexity and O(1) space complexity. The brute force approach simulates each shift operation one by one. This means we will move each element in the grid to its new position for k times, which is straightforward but inefficient. The optimal Optimal Solution approach improves this to O(n).

What algorithm or data structure is used to solve Shift 2D Grid?

Shift 2D Grid uses the following concepts: Array, Matrix, Simulation. The recommended patterns to study are: Array, Circular Queue.

What are the interview tips for Shift 2D Grid?

Always think about edge cases, such as k being larger than the total number of elements. Explain your thought process clearly; it shows your understanding and can help the interviewer guide you. Practice simulating the problem with small examples to build intuition before jumping to code.

What are common mistakes when solving Shift 2D Grid?

Not considering the effective shifts (k % total_elements) which can lead to unnecessary iterations. Overcomplicating the problem by trying to shift elements one by one instead of calculating their final positions.

#1260

Shift 2D Grid

Easy

ArrayMatrixSimulationArrayCircular Queue

LeetCode ↗

Approaches

Brute ForceOptimal

Complexity Comparison

	Brute Force	Optimal Solution★
Time	O(n²)	O(n)
Space	O(1)	O(n)

💡

Intuition

Time O(n)Space O(n)

Instead of simulating each shift, we can calculate the final position of each element directly. This reduces the number of operations significantly and allows us to achieve the result in a single pass.

⚙️

Algorithm

4 steps

1Step 1: Flatten the 2D grid into a 1D array.
2Step 2: Calculate the effective shifts needed (k % total number of elements).
3Step 3: Rearrange the elements in the 1D array based on the effective shifts.
4Step 4: Convert the 1D array back into a 2D grid.

solution.py9 lines

1# Full working Python code
2
3def shiftGrid(grid, k):
4    m, n = len(grid), len(grid[0])
5    total_elements = m * n
6    k = k % total_elements
7    flat_grid = [grid[i][j] for i in range(m) for j in range(n)]
8    flat_grid = flat_grid[-k:] + flat_grid[:-k]
9    return [flat_grid[i * n:(i + 1) * n] for i in range(m)]

ℹ

Complexity note: The time complexity is O(n) because we only traverse the grid a few times (flattening and rearranging), and the space complexity is O(n) due to the additional array used for flattening.

1Shifting elements in a 2D grid can be visualized as a circular queue operation.
2Understanding the effective number of shifts (k % total elements) can significantly reduce unnecessary computations.

Solutions and explanations are original Tejav content. Problem titles © LeetCode — use the LeetCode button above for the full problem statement.