feature_extractor.py

import pandas as pd
import os

class FeatureExtractor(object):
    def __init__(self):
        pass

    def fit(self, X_df, y_array):
        pass

    def transform(self, X_df):
        X_encoded = X_df
        path = os.path.dirname(__file__)
        data_weather = pd.read_csv(os.path.join(path, "external_data.csv"))
        X_weather = data_weather[['Date', 'AirPort', 'Max TemperatureC']]
        X_weather = X_weather.rename(
            columns={'Date': 'DateOfDeparture', 'AirPort': 'Arrival'})
        X_encoded = pd.merge(X_encoded, X_weather, how='left',
                             left_on=['DateOfDeparture', 'Arrival'],
                             right_on=['DateOfDeparture', 'Arrival'],
                             sort=False)

        X_encoded = X_encoded.join(pd.get_dummies(
            X_encoded['Departure'], prefix='d'))
        X_encoded = X_encoded.join(
            pd.get_dummies(X_encoded['Arrival'], prefix='a'))
        X_encoded = X_encoded.drop('Departure', axis=1)
        X_encoded = X_encoded.drop('Arrival', axis=1)

        X_encoded = X_encoded.drop('DateOfDeparture', axis=1)
        X_array = X_encoded.values
        return X_array