sigmoidneuron123/ChessSet

Chess Positions with Stockfish Evaluations

This dataset contains a collection of chess positions in Forsyth-Edwards Notation (FEN), each paired with a corresponding evaluation from the Stockfish chess engine. It is designed for use in training machine learning models for chess, analyzing chess positions, or for any application requiring a large set of evaluated positions.

Data Format

The data is stored in a simple CSV (Comma-Separated Values) format without a header row. Each line in the file represents a single chess position and its evaluation.

The format is as follows: "FEN_string",evaluation

Fields

Field	Description
FEN_string	A standard FEN string representing a specific board state. This includes piece placement, active color, castling availability, en passant target square, halfmove clock, and fullmove number. Learn more about FEN.
evaluation	The Stockfish engine's evaluation of the position in centipawns. - A positive value (+110) indicates an advantage for White. - A negative value (-95) indicates an advantage for Black. - A value near zero suggests a balanced position. - Mate-in-N is represented as #N (e.g., #3 for mate in 3 for the side to move) or #-N (e.g., #-2 if the side to move is being mated in 2).

Example Data

"rnbqkbnr/pppppppp/8/8/8/8/PPPPPPPP/RNBQKBNR w KQkq - 0 1",+25
"r1bqkbnr/pp1ppppp/2n5/2p5/4P3/5N2/PPPP1PPP/RNBQKB1R w KQkq - 2 3",+15
"r4rk1/pp1n1ppp/2pbp3/q2n2B1/3PN3/3Q1N2/PPP2PPP/1K1R3R b - - 5 13",-80
"4r1k1/pp1r1p1p/1qp1n1p1/4P3/3p1P2/2Q4P/PP1R2P1/3R2K1 w - - 0 29",#4

How to Use

Here is a basic Python script to read and parse the data from a file named chess_data.csv.

import csv

def load_chess_data(file_path='chess_data.csv'):
    """
    Loads and prints chess positions and their evaluations from the dataset.
    """
    positions = []
    try:
        with open(file_path, 'r', encoding='utf-8') as f:
            reader = csv.reader(f)
            for row in reader:
                if not row:
                    continue
                fen_string = row[0]
                evaluation = row[1]
                positions.append({'fen': fen_string, 'eval': evaluation})
                print(f"FEN: {fen_string}, Evaluation: {evaluation}")
    except FileNotFoundError:
        print(f"Error: The file {file_path} was not found.")
    except IndexError:
        print(f"Error: Malformed row found in {file_path}.")
    
    return positions

if __name__ == '__main__':
    # Assuming your data is in 'chess_data.csv'
    chess_dataset = load_chess_data()
    if chess_dataset:
        print(f"
Successfully loaded {len(chess_dataset)} positions.")

Data Generation (Example)

This dataset was generated using:

• Engine: Stockfish 16
• Search: 15 seconds per position
• Source: A curated list of positions from grandmaster games.

License

This dataset is released under the MIT License. You are free to use, modify, and distribute it for any purpose.