How to Count Elements and Find Duplicates in a Python List

Count occurrences of each element in a list, extract unique values, and identify duplicates using Python dictionaries and sets.

Easy Python 3.9+ Aug 9, 2026 Dictionaries & sets 12 views 0 copies

dictionary set counting counter duplicates

Python code

32 lines

Python 3.9+

def analyze_counts(data):
    """Count elements, return unique values, and find duplicates."""
    
    # Count occurrences using a dictionary
    counts = {}
    for item in data:
        counts[item] = counts.get(item, 0) + 1
    
    # Alternative compact approach with set
    unique_items = set(data)
    
    # Find duplicates: items that appear more than once
    duplicates = {item for item, count in counts.items() if count > 1}
    
    return {
        "counts": counts,
        "unique_items": unique_items,
        "duplicates": duplicates,
        "total_items": len(data),
        "unique_count": len(unique_items)
    }


if __name__ == "__main__":
    sample_data = ["apple", "banana", "apple", "orange", "banana", "apple"]
    result = analyze_counts(sample_data)
    
    print("Counts:", result["counts"])
    print("Unique items:", result["unique_items"])
    print("Duplicates:", result["duplicates"])
    print("Total items:", result["total_items"])
    print("Unique count:", result["unique_count"])

Output

stdout

Counts: {'apple': 3, 'banana': 2, 'orange': 1}
Unique items: {'orange', 'banana', 'apple'}
Duplicates: {'banana', 'apple'}
Total items: 6
Unique count: 3

How it works

The counts.get(item, 0) call safely fetches the current count or defaults to 0, avoiding a KeyError on first occurrence. The dictionary stores each unique element as a key and its frequency as the value. Converting the original list to a set (set(data)) automatically removes duplicates because sets only hold unique items. A set comprehension filters the counts dictionary to find items whose count exceeds 1, revealing duplicates in one line. This combined approach gives you counts, uniqueness, and duplicates in a single pass through the data.

Common mistakes

Using `counts[item]` without initializing missing keys — raises KeyError
Assuming sets preserve the original list order — output order is arbitrary
Counting with lists instead of dictionaries, which is O(n²) instead of O(n)

Variations

Use `collections.Counter(data)` for a built-in counting dictionary with .most_common()
Use `list(dict.fromkeys(data))` to preserve insertion order when extracting unique items

Real-world use cases

Analyzing user interaction logs to find which features are used most and duplicate click patterns.
Building an inventory system to count remaining stock per SKU and flaging duplicate part numbers.
Cleaning a CSV export by identifying duplicate customer IDs before loading into a CRM.

How to Count Elements and Find Duplicates in a Python List

Python code

Output

How it works

Common mistakes

Variations

Real-world use cases

More from Dictionaries & sets

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Python code

Output

How it works

Common mistakes

Variations

Real-world use cases

More from Dictionaries & sets

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