<gh_stars>0
import pandas as pd 
import numpy as np

import config
from preprocessors import Pipeline

pipeline = Pipeline(target=config.TARGET,
                    categorical_to_impute=config.CATEGORICAL_TO_IMPUTE,
                    year_variable=config.YEAR_VARIABLE,
                    numerical_to_impute=config.NUMERICAL_TO_IMPUTE,
                    numerical_log=config.NUMERICAL_LOG,
                    categorical_encode=config.CATEGORICAL_ENCODE,
                    features=config.FEATURES
                    )

if __name__ == '__main__':

    data = pd.read_csv(config.PATH_TO_DATASET)

    pipeline.fit(data)
    print('model performance')
    pipeline.evaluate_model()
    print("\nSome predictions:")
    predictions = pipeline.predict(data)
    print(predictions)




import pandas as pd 
import numpy as np

import config
from preprocessors import Pipeline

pipeline = Pipeline(target=config.TARGET,
                    categorical_to_impute=config.CATEGORICAL_TO_IMPUTE,
                    year_variable=config.YEAR_VARIABLE,
                    numerical_to_impute=config.NUMERICAL_TO_IMPUTE,
                    numerical_log=config.NUMERICAL_LOG,
                    categorical_encode=config.CATEGORICAL_ENCODE,
                    features=config.FEATURES
                    )

if __name__ == '__main__':

    data = pd.read_csv(config.PATH_TO_DATASET)

    pipeline.fit(data)
    print('model performance')
    pipeline.evaluate_model()
    print("\nSome predictions:")
    predictions = pipeline.predict(data)
    print(predictions)