Binary TreesBinary Trees36
❯
  1. 1Preorder Traversal of a Binary Tree using Recursion
  2. 2Preorder Traversal of a Binary Tree using Iteration
  3. 3Inorder Traversal of a Binary Tree using Recursion
  4. 4Inorder Traversal of a Binary Tree using Iteration
  5. 5Postorder Traversal of a Binary Tree Using Recursion
  6. 6Postorder Traversal of a Binary Tree using Iteration
  7. 7Level Order Traversal of a Binary Tree using Recursion
  8. 8Level Order Traversal of a Binary Tree using Iteration
  9. 9Reverse Level Order Traversal of a Binary Tree using Iteration
  10. 10Reverse Level Order Traversal of a Binary Tree using Recursion
  11. 11Find Height of a Binary Tree
  12. 12Find Diameter of a Binary Tree
  13. 13Find Mirror of a Binary Tree
  14. 14Left View of a Binary Tree
  15. 15Right View of a Binary Tree
  16. 16Top View of a Binary Tree
  17. 17Bottom View of a Binary Tree
  18. 18Zigzag Traversal of a Binary Tree
  19. 19Check if a Binary Tree is Balanced
  20. 20Diagonal Traversal of a Binary Tree
  21. 21Boundary Traversal of a Binary Tree
  22. 22Construct a Binary Tree from a String with Bracket Representation
  23. 23Convert a Binary Tree into a Doubly Linked List
  24. 24Convert a Binary Tree into a Sum Tree
  25. 25Find Minimum Swaps Required to Convert a Binary Tree into a BST
  26. 26Check if a Binary Tree is a Sum Tree
  27. 27Check if All Leaf Nodes are at the Same Level in a Binary Tree
  28. 28Lowest Common Ancestor (LCA) in a Binary Tree
  29. 29Solve the Tree Isomorphism Problem
  30. 30Check if a Binary Tree Contains Duplicate Subtrees of Size 2 or More
  31. 31Check if Two Binary Trees are Mirror Images
  32. 32Calculate the Sum of Nodes on the Longest Path from Root to Leaf in a Binary Tree
  33. 33Print All Paths in a Binary Tree with a Given Sum
  34. 34Find the Distance Between Two Nodes in a Binary Tree
  35. 35Find the kth Ancestor of a Node in a Binary Tree
  36. 36Find All Duplicate Subtrees in a Binary Tree
GraphsGraphs46
❯
  1. 1Breadth-First Search in Graphs
  2. 2Depth-First Search in Graphs
  3. 3Number of Provinces in an Undirected Graph
  4. 4Connected Components in a Matrix
  5. 5Rotten Oranges Problem - BFS in Matrix
  6. 6Flood Fill Algorithm - Graph Based
  7. 7Detect Cycle in an Undirected Graph using DFS
  8. 8Detect Cycle in an Undirected Graph using BFS
  9. 9Distance of Nearest Cell Having 1 - Grid BFS
  10. 10Surrounded Regions in Matrix using Graph Traversal
  11. 11Number of Enclaves in Grid
  12. 12Word Ladder - Shortest Transformation using Graph
  13. 13Word Ladder II - All Shortest Transformation Sequences
  14. 14Number of Distinct Islands using DFS
  15. 15Check if a Graph is Bipartite using DFS
  16. 16Topological Sort Using DFS
  17. 17Topological Sort using Kahn's Algorithm
  18. 18Cycle Detection in Directed Graph using BFS
  19. 19Course Schedule - Task Ordering with Prerequisites
  20. 20Course Schedule 2 - Task Ordering Using Topological Sort
  21. 21Find Eventual Safe States in a Directed Graph
  22. 22Alien Dictionary Character Order
  23. 23Shortest Path in Undirected Graph with Unit Distance
  24. 24Shortest Path in DAG using Topological Sort
  25. 25Dijkstra's Algorithm Using Set - Shortest Path in Graph
  26. 26Dijkstra’s Algorithm Using Priority Queue
  27. 27Shortest Distance in a Binary Maze using BFS
  28. 28Path With Minimum Effort in Grid using Graphs
  29. 29Cheapest Flights Within K Stops - Graph Problem
  30. 30Number of Ways to Reach Destination in Shortest Time - Graph Problem
  31. 31Minimum Multiplications to Reach End - Graph BFS
  32. 32Bellman-Ford Algorithm for Shortest Paths
  33. 33Floyd Warshall Algorithm for All-Pairs Shortest Path
  34. 34Find the City With the Fewest Reachable Neighbours
  35. 35Minimum Spanning Tree in Graphs
  36. 36Prim's Algorithm for Minimum Spanning Tree
  37. 37Disjoint Set (Union-Find) with Union by Rank and Path Compression
  38. 38Kruskal's Algorithm - Minimum Spanning Tree
  39. 39Minimum Operations to Make Network Connected
  40. 40Most Stones Removed with Same Row or Column
  41. 41Accounts Merge Problem using Disjoint Set Union
  42. 42Number of Islands II - Online Queries using DSU
  43. 43Making a Large Island Using DSU
  44. 44Bridges in Graph using Tarjan's Algorithm
  45. 45Articulation Points in Graphs
  46. 46Strongly Connected Components using Kosaraju's Algorithm

Find Maximum and Minimum in Array using Loop - Algorithm and Examples

Arrays

Contents

ProblemExamplesVisualizationSolutionAlgorithmCodeTimeSpace Detailed Exmpl

Problem Statement❯

Given an array of integers, your task is to find the maximum and minimum values present in the array using a simple loop (without any built-in functions).

  • The maximum value is the largest number in the array.
  • The minimum value is the smallest number in the array.

If the array is empty, there is no maximum or minimum, and the result should indicate that appropriately (e.g., null or a message).

Examples❯

Input Array Maximum Minimum Description
[10, 20, 5, 8, 30] 30 5 Normal case with unordered elements Visualization
[5, 5, 5, 5] 5 5 All elements are equalVisualization
[-10, -5, -3, -20] -3 -20 All elements are negativeVisualization
[100] 100 100 Only one element in the arrayVisualization
[] null null Empty array — no max or min can be determinedVisualization

Visualization Player

Solution❯

To find the maximum and minimum values in an array, we can simply scan through the array one element at a time and keep track of the largest and smallest values we encounter.

Case 1: When the Array Has Elements

We start by assuming the first element is both the maximum and the minimum. Then, we go through the rest of the array and compare each value:

  • If the current value is larger than our current maximum, we update the maximum.
  • If the current value is smaller than our current minimum, we update the minimum.

This way, by the time we reach the end of the array, we will have found the true maximum and minimum values.

Case 2: When the Array Has One Element

If the array has just a single element, then that element is both the maximum and the minimum, since there's nothing else to compare it to.

Case 3: When All Elements Are Equal

If every number in the array is the same, then that number is both the maximum and minimum. For example, in [7, 7, 7], the answer is max = 7, min = 7.

Case 4: When the Array is Empty

If the array is empty, we can't find either maximum or minimum values. There's simply no data to evaluate. In such cases, we should either return null, an empty result, or show a message like "No elements to compare"—depending on how we want to handle such edge cases.

Algorithm Steps❯

  1. Given an array of numbers arr.
  2. If array is empty, return null or -1.
  3. Initialize max_val and min_val with the first element of the array.
  4. Iterate through each element in the array starting from the second element.
  5. If the current element is greater than max_val, update max_val.
  6. If the current element is less than min_val, update min_val.
  7. After the loop, return max_val and min_val.

Code

Python
Java
JavaScript
C
C++
C#
Go
def find_max_min_loop(arr):
    if not arr:
        return None
    max_val = arr[0]
    min_val = arr[0]
    for num in arr[1:]:
        if num > max_val:
            max_val = num
        if num < min_val:
            min_val = num
    return max_val, min_val

# Sample Input
arr2 = [-5, -1, -9, 0, 3, 7]
result = find_max_min_loop(arr2)
if result:
    print("Maximum:", result[0])
    print("Minimum:", result[1])

Time Complexity❯

CaseTime ComplexityExplanation
Best CaseO(n)Even in the best case, every element must be checked to ensure no smaller or larger values exist.
Average CaseO(n)Each element is visited once to compare and possibly update the maximum or minimum.
Worst CaseO(n)In the worst case, the loop still traverses the entire array to determine the max and min values.

Space Complexity❯

O(1)

Explanation: Only a fixed number of variables (e.g., max_val, min_val) are used, regardless of input size.

Detailed Step by Step Example❯

Let us take the following array and apply the logic to find the maximum and minimum elements.

{ "array": [6,3,8,2,7,4], "showIndices": true, "highlightIndices": [0] }
{ "array": [0,6,6], "showIndices": false, "highlightIndicesGreen": [1, 2], "emptyCompIndices": [0], "labels": { "1": "max", "2": "min" } }

Initialize max = 6 and min = 6 with the first element of the array.

Check index 1

Compare 3 at index=1 with current max = 6 and min = 6.

3 is smaller than current min. Update min = 3.

{ "array": [6,3,8,2,7,4], "showIndices": true, "highlightIndices": [1], "specialIndices": [], "labels": {"1":"i"} }
{ "array": [0,6,3], "showIndices": false, "highlightIndicesGreen": [1, 2], "emptyCompIndices": [0], "labels": { "1": "max", "2": "min" } }

Check index 2

Compare 8 at index=2 with current max = 6 and min = 3.

8 is greater than current max. Update max = 8.

{ "array": [6,3,8,2,7,4], "showIndices": true, "highlightIndices": [2], "specialIndices": [], "labels": {"2":"i"} }
{ "array": [0,8,3], "showIndices": false, "highlightIndicesGreen": [1, 2], "emptyCompIndices": [0], "labels": { "1": "max", "2": "min" } }

Check index 3

Compare 2 at index=3 with current max = 8 and min = 3.

2 is smaller than current min. Update min = 2.

{ "array": [6,3,8,2,7,4], "showIndices": true, "highlightIndices": [3], "specialIndices": [], "labels": {"3":"i"} }
{ "array": [0,8,2], "showIndices": false, "highlightIndicesGreen": [1, 2], "emptyCompIndices": [0], "labels": { "1": "max", "2": "min" } }

Check index 4

Compare 7 at index=4 with current max = 8 and min = 2.

No update required.

{ "array": [6,3,8,2,7,4], "showIndices": true, "highlightIndices": [4], "specialIndices": [], "labels": {"4":"i"} }
{ "array": [0,8,2], "showIndices": false, "highlightIndicesGreen": [1, 2], "emptyCompIndices": [0], "labels": { "1": "max", "2": "min" } }

Check index 5

Compare 4 at index=5 with current max = 8 and min = 2.

No update required.

{ "array": [6,3,8,2,7,4], "showIndices": true, "highlightIndices": [5], "specialIndices": [], "labels": {"5":"i"} }
{ "array": [0,8,2], "showIndices": false, "highlightIndicesGreen": [1, 2], "emptyCompIndices": [0], "labels": { "1": "max", "2": "min" } }

Final Result:

Maximum = 8, Minimum = 2

{ "array": [6,3,8,2,7,4], "showIndices": true, "labels": { "2": "max", "3": "min" }, "specialIndices": [] }
{ "array": [0,8,2], "showIndices": false, "highlightIndicesGreen": [1, 2], "emptyCompIndices": [0], "labels": { "1": "max", "2": "min" } }