🔍 Introduction Free Course -

https://www.dsawithpiyush.com/course/dsa/Arrays/ARRAYS_INTRO

Arrays are one of the most fundamental data structures in computer science. Every advanced concept in DSA—such as sliding window, two pointers, prefix sums, stacks, queues, and dynamic programming—is built on top of arrays.

If you are preparing for coding interviews or learning DSA from scratch, mastering arrays is non‑negotiable.

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📌 What is an Array?

An array is a linear data structure that stores elements of the same data type in contiguous memory locations, where each element can be accessed using an index.

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🧠 Key Characteristics of Arrays

* Fixed size (in most languages)
* Index-based access (0-based indexing)
* Fast access time – **O(1)**
* Inefficient insertion & deletion in middle – **O(n)**

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📊 Visual Representation

```

Index: 0 1 2 3 4

Value: 10 20 30 40 50

```

Access element at index 2 → `arr[2] = 30`

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🌍 Real-World Examples

Marks of students in a class

Daily temperatures of a city

Stock prices over N days

Scores in a leaderboard

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⚙️ Basic Operations on Array

1️⃣ Traversal

js

const arr = [10, 20, 30, 40];
for (let i = 0; i < arr.length; i++) {
  console.log(arr[i]);
}


⏱ Time Complexity: O(n)

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2️⃣ Accessing Elements

js

const arr = [5, 10, 15];
console.log(arr[1]); // 10


⏱ Time Complexity: O(1)

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3️⃣ Insertion

js

let arr = [10, 20, 30];
arr.push(40); // insert at end


  End insertion: O(1) (amortized)
  Middle insertion: O(n)

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4️⃣ Deletion

js

let arr = [10, 20, 30];
arr.splice(1, 1); // removes 20
⏱ Time Complexity: O(n)

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⚠️ Limitations of Arrays

Fixed size

Memory wastage or overflow

Slow insertion/deletion

👉 These limitations lead to Linked Lists.

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 🧩 Important Array Patterns (VERY IMPORTANT)

🔹 Sliding Window

Used when working with subarrays or ranges.

🔹 Two Pointer Technique

Used in sorted arrays for optimized traversal.

🔹 Prefix Sum

Used to answer range sum queries efficiently.

🔹 Kadane’s Algorithm

Used to find maximum subarray sum.

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🧪 Dry Run Example

Problem: Find sum of array

Input

```

[1, 2, 3, 4]

```

Step-by-step

* sum = 0
* sum = 1
* sum = 3
* sum = 6
* sum = 10

Output: `10`

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## ⏱ Time & Space Complexity Summary

| Operation | Time Complexity |

| --------- | --------------- |

| Access    | O(1)            |
| Traversal | O(n)            |
| Insertion | O(n)            |
| Deletion  | O(n)            |

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🧠 Common Interview Questions on Arrays

Q1. Why is array access O(1)?

Because elements are stored in contiguous memory locations.

Q2. Difference between array and linked list?

Array provides fast access, linked list provides dynamic size.

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🧑‍💻 LeetCode Practice Problems (Must Solve)

Easy

Two Sum

https://leetcode.com/problems/two-sum/description/

Best Time to Buy and Sell Stock

https://leetcode.com/problems/best-time-to-buy-and-sell-stock/description/

Medium

Maximum Subarray (Kadane)

Product of Array Except Self

https://leetcode.com/problems/product-of-array-except-self/description/

Hard

Trapping Rain Water

https://leetcode.com/problems/trapping-rain-water/

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🚫 Common Mistakes Beginners Make

Off-by-one index errors

Modifying array during iteration

Ignoring edge cases (empty array)

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 🔗 Related Topics (Internal Linking)

Sliding Window Technique

Two Pointer Technique

Prefix Sum Array

Kadane Algorithm

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🎯 When to Use Arrays?

Use arrays when

Size is known

Fast access is required

Order matters

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🚀 Final Thoughts

Arrays are the foundation of DSA. Once you master arrays, learning advanced topics becomes significantly easier. Next Topic - Array Traversal

https://www.dsawithpiyush.com/post/array-traversal-in-data-structure-or-ds

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📌 **DSA with Piyush** – Learn DSA the right way, from basics to interviews.