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| # scripts/generate_data.py | |
| import numpy as np | |
| import pandas as pd | |
| import os | |
| def generate_dataset(n_samples=1000): | |
| np.random.seed(42) | |
| study_hours = np.random.normal(10, 2, n_samples) | |
| tuition_hours = np.random.normal(5, 1, n_samples) | |
| parental_education = np.random.choice(['High', 'Medium', 'Low'], n_samples) | |
| school_type = np.random.choice(['Public', 'Private'], n_samples) | |
| exam_score = 50 + 2 * study_hours + 1.5 * tuition_hours + np.random.normal(0, 5, n_samples) | |
| df = pd.DataFrame({ | |
| 'StudyHours': study_hours, | |
| 'TuitionHours': tuition_hours, | |
| 'ParentalEducation': parental_education, | |
| 'SchoolType': school_type, | |
| 'FinalExamScore': exam_score | |
| }) | |
| # Ensure data directory exists | |
| os.makedirs('../data', exist_ok=True) | |
| df.to_csv('../data/sample_dataset.csv', index=False) | |
| return df | |
| if __name__ == "__main__": | |
| generate_dataset() | |
| print("Dataset generated and saved to ../data/sample_dataset.csv") | |