Data Structures - lesson 2 | HackIndia Skills

Key point

One idea

Use the simplest structure that gives the operation cost you need. Arrays and strings are good for ordered scans. Maps and sets are good when fast lookup or frequency matters.

When to pick what

Pick an array when you need index access, sorting, prefix sums, two pointers, or a sliding window. In Python, use list. In JavaScript, use Array.

Pick a string when the input is text, but remember many strings are immutable. If you build many characters step by step, collect pieces in an array or list, then join.

Maps and sets

Pick a map when each key has a value: count, last seen index, parent, score, or group. Python uses dict. JavaScript uses Map or a plain object for simple string keys.

Pick a set when you only care whether something exists. Use it for duplicate checks, visited items, and membership tests.

Your to-do

Interview pattern check

Do each one yourself, then tap it to tick it off. The ticks are only a checklist for you: they are not marked or scored.

Ask what operation is repeated most: lookup, insert, delete, scan, sort, or index access.
Estimate the cost if you use only arrays. A repeated linear search often becomes O(n²).
Switch to a map or set if fast membership or counting removes repeated scans.
Keep the explanation short: data structure, main operation, time cost, space cost.

0 of 4 done

Example

Example file

Add one clean problem to your kit today: first non-repeating character. It shows why a map is better than scanning the string again and again.

# arrays_strings_maps_sets/first_non_repeating.py

def first_non_repeating(s: str) -> str:
    freq = {}

    for ch in s:
        freq[ch] = freq.get(ch, 0) + 1

    for ch in s:
        if freq[ch] == 1:
            return ch

    return ""


def test_first_non_repeating():
    assert first_non_repeating("aabbcdd") == "c"
    assert first_non_repeating("leetcode") == "l"
    assert first_non_repeating("aabb") == ""
    assert first_non_repeating("") == ""

Common mistake

Do not say “hash map is always faster.” It is faster for lookup and counting on average, but it uses extra memory and loses natural order unless you manage order separately.

Also avoid sorting when the original order matters. Sorting may reduce one cost, but it changes positions and can break the answer.

Tip

Use AI well

Ask AI for three approaches, not just code. Example prompt: “Solve this using array scan, sorting, and hash map. Compare time and space. Then give Python tests.”

Check the output yourself. Look for wrong edge cases, hidden sorting, missing empty input, and claims like O(1) space when a map grows with n.