How to Count Star vs Estimate Matches in Python

Count how many times 'star' and 'estimate' annotations match their actual labels in a list of mock comparison results.

Easy Python 3.9+ Aug 9, 2026 Database scaling & optimization 12 views 0 copies

counting dictionary matching loops

Python code

33 lines

Python 3.9+

def count_star_vs_estimate(mock_scores):
    """
    Count the number of times 'star' wins and 'estimate' wins
    from a list of mock comparison results.

    Args:
        mock_scores: list of tuples, each (annotation, actual)
                     where annotation is 'star' or 'estimate'

    Returns:
        dict with counts of 'star', 'estimate', and 'tie'
    """
    counts = {"star": 0, "estimate": 0, "tie": 0}
    for annotation, actual in mock_scores:
        if annotation == actual:
            counts[annotation] += 1
        else:
            counts["tie"] += 1
    return counts


if __name__ == "__main__":
    # Example mock data: (annotation, actual)
    mock_scores = [
        ("star", "star"),
        ("star", "estimate"),
        ("estimate", "estimate"),
        ("estimate", "star"),
        ("star", "star"),
        ("estimate", "estimate"),
    ]
    result = count_star_vs_estimate(mock_scores)
    print(result)

Output

stdout

{'star': 2, 'estimate': 2, 'tie': 2}

How it works

This solution loops through each (annotation, actual) tuple and compares the two values. When they match, it increments the count for that annotation key; otherwise, it counts a tie. Using a dictionary with a default count of zero for all categories keeps the code clean and avoids special-case handling. The implementation is O(n), making it efficient even for large datasets.

Common mistakes

Assuming annotations and actual labels are always 'star' or 'estimate' without validation
Forgetting to initialize all three counters before the loop
Using a list of lists instead of tuples, which changes unpacking behavior
Mutating the input list while iterating over it

Variations

Use collections.Counter with a generator expression to build counts in one line
Return a tuple (star, estimate, tie) instead of a dictionary for simpler unpacking

Real-world use cases

Evaluating label accuracy in a machine learning mock experiment pipeline.
Tracking winners in an A/B test where two annotation strategies are compared.
Auditing annotation consistency across multiple data batches in production.

How to Count Star vs Estimate Matches in Python

Python code

Output

How it works

Common mistakes

Variations

Real-world use cases

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