def load_csv_files(self): print "FlightDay Initializing: {}, {} in {} mode".format(self.folder_name, self.data_set_name, self.mode) print "\tLoading flight_history.csv...", self.flight_history = \ pd.read_csv("../Data/" + self.data_set_name + \ "/" + self.folder_name + "/" + "FlightHistory/flighthistory.csv", na_values=["MISSING", "HIDDEN", ""], keep_default_na=True, converters=dut.get_flight_history_date_converter()) print "done"
def load_csv_files(self): print "FlightDay Initializing: {}, {} in {} mode".format( self.folder_name, self.data_set_name, self.mode) print "\tLoading flight_history.csv...", self.flight_history = \ pd.read_csv("../Data/" + self.data_set_name + \ "/" + self.folder_name + "/" + "FlightHistory/flighthistory.csv", na_values=["MISSING", "HIDDEN", ""], keep_default_na=True, converters=dut.get_flight_history_date_converter()) print "done"
def __init__(self, data): data_set_name = "InitialTrainingSet_rev1" self.flight_history = pd.DataFrame(None) self.parsed_fhe = pd.DataFrame(None) if data == "flight_history": print "AllTrainingData Initializing: using data {}".format(data) for f in fn.folder_names_init_set(): print "\tLoading flight_history.csv folder {}...".format(f), temp = \ pd.read_csv("../Data/" + data_set_name + \ "/" + f + "/" + "FlightHistory/flighthistory.csv", converters = dut.get_flight_history_date_converter()) self.flight_history = pd.concat([self.flight_history, temp]) print "done" if data == "parsed_fhe": print "AllTrainingData Initializing: using data {}".format(data) for f in fn.folder_names_init_set(): print "\tLoading parsed_fhe.csv file {}...".format(f), temp = \ pd.read_csv('output_csv/parsed_fhe_' + f + '_' + "all" + '_filtered.csv', # might have to fix to work with test data? na_values=["MISSING"], keep_default_na=False, parse_dates=[9,10,11,12,13,14,15,16,17,18,27,28,29,30,31,32,33,34,35,36,37,38,43,47]) self.parsed_fhe = pd.concat([self.parsed_fhe, temp]) print "done" if data == "parsed_fhe_test": print "AllTrainingData Initializing: using data {}".format(data) for f in fn.folder_names_init_set(): print "\tLoading parsed_fhe.csv file {}...".format(f), temp = \ pd.read_csv('output_csv/parsed_fhe_' + f + '_' + "test" + '_filtered.csv', na_values=["MISSING"], keep_default_na=False, parse_dates=[9,10,11,12,13,14,15,16,17,18,27,28,29,30,31,32,33,34,35,36,37,38,43,47]) self.parsed_fhe = pd.concat([self.parsed_fhe, temp]) print "done" if data == "parsed_fhe_no_dates": print "AllTrainingData Initializing: using data {}".format(data) for f in fn.folder_names_init_set(): print "\tLoading parsed_fhe.csv file {}...".format(f), temp = \ pd.read_csv('output_csv/parsed_fhe_' + f + '_' + "all" + '_filtered.csv', # might have to fix to work with test data? na_values=["MISSING"], keep_default_na=False) self.parsed_fhe = pd.concat([self.parsed_fhe, temp]) print "done" if data == "parsed_fhe_test_no_dates": print "AllTrainingData Initializing: using data {}".format(data) for f in fn.folder_names_test_set(): print "\tLoading parsed_fhe_test.csv file {}...".format(f), temp = \ pd.read_csv('output_csv/parsed_fhe_' + f + '_' + "test" + '_filtered.csv', # might have to fix to work with test data? na_values=["MISSING"], keep_default_na=False) self.parsed_fhe = pd.concat([self.parsed_fhe, temp]) print "done" if data == "parsed_fhe_test_no_dates_with_best": print "AllTrainingData Initializing: using data {}".format(data) for f in fn.folder_names_test_set(): print "\tLoading parsed_fhe_test.csv file {}...".format(f), temp = \ pd.read_csv('output_csv/parsed_fhe_' + f + '_' + "test" + \ '_filtered_with_dates_with_best_prediction.csv', # might have to fix to work with test data? na_values=["MISSING"], keep_default_na=False) self.parsed_fhe = pd.concat([self.parsed_fhe, temp]) print "done"