EnergySignature = Input Data

DaRe_Energy_Main = Script for data preparation.

                Input -> Input Data from Energy Signature
                Output -> .csv file containing elaborated data
                                        'EnergyClean/Energy_%s_%s_%i.csv' % (str(split), outliers_rmv, year)
                                        split = True || False
                                        outliers_rmv = 'ZS' || 'IQR' || 'NO'
                                        year = 2017 || 2018

DaRe_Energy_Random_Forest = Script for random forest model creation.

                        Input -> .csv file containing elaborated data
                        Output -> 1. 'Random_Forest_model.sav' containing the Random Forest model
                                  2. 'test_data.csv' containing the data used to test the model

DaRe_Energy_Predictor = Autonomous script for data prediction.

                    Input -> 1. Random Forest Model File
                             2. Input Data to predict
                             3. Output file
                             
                             usage: DaRe_Energy_Predictor.py <modelFile> <inFile> <outFile>
                             for more instructions: DaRe_Energy_Predictor.py -h || --help
                             
                    Output -> <outFile> containing the input data with added column for predicted values