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)