def main(): sns.set() file_names = os.listdir() needed_files = ['sentence_length.csv', 'socio_econ.csv', 'Chicago_shape.zip', 'population.csv'] for file_name in needed_files: if file_name not in file_names: save_useful_files() print('file_saved') crime_data = get_crime_data() print('get crime data') geo_data = get_geo_data() population_data = get_population_data() sentence_length_data = get_sentence_length_data() socio_econ_data = get_socio_econ_data() get_crime_sample(crime_data) q1 = Question1.Question1(crime_data, sentence_length_data, geo_data, socio_econ_data) q1._plot_a_single_year(2018) q1._plot_change('42 43 45') q1._safety_ranking(2018) q2 = Question2.Question2() q2.aggregate_data(crime_data) q2.machine_learning() q2._report_predict('assault', 43, 23) q2._report_predict('theft', 9, 23) q2._report_predict('theft', 9, 10) q2._report_predict('theft', 9, 13) print('The mean square error of the model is ' + str(q2.mes())) Question3.Question3(crime_data, geo_data, population_data) Question4.Question4(crime_data, geo_data, population_data, socio_econ_data)
def main(): sns.set() file_names = os.listdir() needed_files = [ 'sentence_length.csv', 'socio_econ.csv', 'Chicago_shape.zip', 'population.csv' ] for file_name in needed_files: if file_name not in file_names: save_useful_files() print('file_saved') crime_data = get_crime_data() print('get crime data') geo_data = get_geo_data() population_data = get_population_data() sentence_length_data = get_sentence_length_data() socio_econ_data = get_socio_econ_data() # get_crime_sample(crime_data) q1 = Question1.Question1(crime_data, sentence_length_data, geo_data, socio_econ_data) q1.plot_communities_single_year() q1.plot_change_through_years() q1.safety_ranking() q2 = Question2.Question2() q2.aggregate_data(crime_data) q2.machine_learning() q2.predict() print('The mean square error of the model is ' + str(q2.mes())) Question3.Question3(crime_data, geo_data, population_data) Question4.Question4(crime_data, geo_data, population_data, socio_econ_data)