README.md

metadata

language:
  - en
pretty_name: Project Euler Problems
tags:
  - code
size_categories:
  - n<1k

Project Euler Problems Dataset

A comprehensive collection of mathematical and programming challenges from Project Euler (projecteuler.net), organized for machine learning and educational purposes.

Dataset Description

This dataset contains 918 problems from Project Euler, a series of challenging mathematical/computer programming problems that require creative problem-solving approaches.

Features

• id: Problem number (integer)
• title: Problem title
• problem: Plain text version of the problem statement
• question_latex: LaTeX formatted problem statement
• question_html: HTML formatted problem statement
• numerical_answer: The correct numerical answer
• pub_date: Publication date
• solved_by: Number of people who have solved the problem
• diff_rate: Difficulty rating (percentage of users who solved it)

Splits

The dataset provides several splits for different use cases:

• train/test: Standard 80/10/10 split for machine learning
  • train: 734 problems
  • test: 184 problems
• easy/medium/hard: Problems grouped by difficulty level
  • easy: 277 problems (>25% solve rate)
  • medium: 336 problems (5-25% solve rate)
  • hard: 305 problems (≤5% solve rate)
• early_problems/later_problems: First half vs. second half of problems by ID
  • early_problems: 464 problems
  • later_problems: 454 problems
• sample: A random selection of 50 problems for quick experimentation

Usage

from datasets import load_dataset

# Load the entire dataset with all splits
dataset = load_dataset("alexandonian/project-euler")

# Work with specific splits
train_problems = dataset["train"]
hard_problems = dataset["hard"]
sample_problems = dataset["sample"]

# Example: Get a problem
problem = train_problems[0]
print(f"Problem #{problem["id"]}: {problem["title"]}")
print(problem["problem"])
print(f"Answer: {problem["numerical_answer"]}")

Potential Applications

• Training math problem-solving models
• Generating solutions or solution approaches
• Testing reasoning capabilities of language models
• Educational tools for learning algorithmic thinking

Citation & License

This dataset is provided for research and educational purposes. Project Euler problems are from projecteuler.net.