| from datasets import load_dataset | |
| import pandas as pd | |
| divider = 1 | |
| data_size = 25000 // divider | |
| case_size = data_size // 2 | |
| dataset = load_dataset("imdb") | |
| train_df = pd.DataFrame(dataset['train']) | |
| test_df = pd.DataFrame(dataset['test']) | |
| train_df = train_df.iloc[::divider, :] | |
| test_df = test_df.iloc[::divider, :] | |
| train_df['label'] = train_df['label'].apply(lambda x: 'NEGATIVE' if x == 0 else 'POSITIVE') | |
| test_df['label'] = test_df['label'].apply(lambda x: 'NEGATIVE' if x == 0 else 'POSITIVE') | |
| train_df.to_csv(f'imdb_train_{case_size}_{case_size}.csv', index=False) | |
| test_df.to_csv(f'imdb_test_{case_size}_{case_size}.csv', index=False) | |