Zaktualizuj 'z434743-create-dataset.py'
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@ -11,11 +11,13 @@ movies = pandas.read_csv('./ium_z434743/rotten_tomatoes_movies.csv',
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sep=',')
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sep=',')
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movies = movies.dropna()
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movies = movies.dropna()
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movies = movies.drop(movies.columns[[0, 1, 4, 5, 6, 7, 9, 10, 11, 12, 13, 14, 15]], axis=1)
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movies = movies.sample(CUTOFF)
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movies = movies.sample(CUTOFF)
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X, Y = movies, movies
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X = movies.copy()
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Y = pandas.DataFrame(movies.pop('audienceScore'))
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X_train, X_temp, Y_train, Y_temp = train_test_split(X, Y, test_size=0.3, random_state=1)
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X_train, X_temp, Y_train, Y_temp = train_test_split(X, Y, test_size=0.3, random_state=1)
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@ -24,3 +26,6 @@ X_dev, X_test, Y_dev, Y_test = train_test_split(X_temp, Y_temp, test_size=0.3, r
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X_train.to_csv('X_train.csv', index=False)
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X_train.to_csv('X_train.csv', index=False)
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X_dev.to_csv('X_dev.csv', index=False)
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X_dev.to_csv('X_dev.csv', index=False)
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X_test.to_csv('X_test.csv', index=False)
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X_test.to_csv('X_test.csv', index=False)
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Y_test.to_csv('Y_test.csv', index=False)
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Y_train.to_csv('Y_train.csv', index=False)
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Y_dev.to_csv('Y_dev.csv', index=False)
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