Is First Unique Character in a String easy or hard?

The problem is classified as Easy. The main concept is frequency counting using a hash table, which makes it a common early interview question for practicing string processing and basic data structures.

First Unique Character in a String Python/Java solution

In Python, use a dictionary or collections.Counter to count characters, then iterate through the string to find the first index with count 1. In Java, use a HashMap or an int array of size 26 to store frequencies and perform the same two-pass scan.

How to solve First Unique Character in a String in O(n)?

Count the frequency of each character using a hash map or fixed-size array. After building the counts, iterate through the string and return the first index where the frequency equals 1. Because each pass processes the string once, the total complexity remains O(n).

What is the best approach for First Unique Character in a String?

The most efficient approach uses a frequency map (hash table). First count how many times each character appears, then scan the string again to find the first character with frequency 1. This runs in O(n) time with O(n) space and is the standard interview solution.

Is First Unique Character in a String asked at Google/Amazon/Meta?

This problem or close variations appear in interviews at companies like Amazon, Microsoft, and Meta. It tests basic hash table usage, frequency counting, and string traversal, which are common patterns in coding interviews.

What data structure is used in First Unique Character in a String?

A hash table (dictionary or map) is typically used to store character frequencies. Some optimized variants also combine the map with a queue to track candidate indices for the first unique character during iteration.

What is the time complexity of First Unique Character in a String?

The optimal solution runs in O(n) time because the string is scanned twice: once to count character frequencies and once to locate the first unique character. Space complexity is O(n) for the frequency map, though it can be reduced to O(1) if the alphabet size is fixed (like lowercase English letters).