🚀 Day 77/150 – Find Duplicate Characters in a String in Python

Strings are one of the most commonly used data types in Python, and a frequent interview or practice question is finding duplicate characters in a string. Duplicate characters are those that appear more than once in the given text.

In this blog, we'll explore multiple ways to identify duplicate characters in a string using Python.

Method 1 – Using a Dictionary

A dictionary can store the frequency of each character. Once the count is calculated, we can print characters whose frequency is greater than 1.

text = "programming" freq = {} for ch in text: freq[ch] = freq.get(ch, 0) + 1 for ch, count in freq.items(): if count > 1: print(ch)

Output

r
g
m

Why Use This Method?

• Efficient and easy to understand
• Works well for large strings
• Time Complexity: O(n)

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Method 2 – Taking User Input

This method allows users to enter their own string and find duplicate characters dynamically.

text = input("Enter a string: ") freq = {} for ch in text: freq[ch] = freq.get(ch, 0) + 1 for ch, count in freq.items(): if count > 1: print(ch)

Example Input

hello world
 
Output

l
o

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Method 3 – Using Nested Loops

This approach compares each character with the remaining characters in the string.

text = "programming" duplicates = [] for i in range(len(text)): for j in range(i + 1, len(text)): if text[i] == text[j] and text[i] not in duplicates: duplicates.append(text[i]) print(duplicates)

Output

['r', 'g', 'm']
 
Pros

• No dictionary required
• Useful for understanding string comparisons

Cons

• Less efficient for larger strings
• Time Complexity: O(n²)

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Method 4 – Using Set and count()

A concise approach is to use a set to get unique characters and count their occurrences.

text = "programming" for ch in set(text): if text.count(ch) > 1: print(ch)

Output

r
g
m

Pros

• Short and readable
• Easy to implement

Cons

• count() scans the string repeatedly
• Not ideal for very large strings

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🎯 Real-World Applications

Finding duplicate characters is useful in:

• Data validation
• Text processing
• Password analysis
• Frequency analysis
• Coding interviews and programming challenges