def generate_answers():
try:
raw_data = pd.read_csv('DOHMH_New_York_City_Restaurant_Inspection_Results.csv',low_memory=False)
except IOError:
sys.exit()
print "The program has got the raw data. Now it is cleaning the data... Please wait."
raw_data_cleaning = data_clean.clean(raw_data)
cleaned_data = raw_data_cleaning.clean_data()
# question 4: compute the performance of all restaurants and print the sum for different Boroughs.
print "Computing the performance of all restaurants..."
grade_analysis_functions.print_restaurant_grades_all(cleaned_data)
print "Camputing the performance of restaurants in different boroughs..."
grade_analysis_functions.print_restaurant_grades_by_borough(cleaned_data)
# question 5: generate the graphs
print "Generating the graphs..."
df_whole_city = grade_analysis_functions.get_grade_count_values(cleaned_data)
graph_plot.generate_graph(df_whole_city,'nyc')
for boroname in cleaned_data['BORO'].unique():
graph_plot.generate_graph(grade_analysis_functions.get_grade_count_values(cleaned_data[cleaned_data['BORO'] == boroname]),boroname.lower())
print "The graphs have been generated. Please check the current directory. Thanks!"
def start_analyse_grade():
print "*******************************************************************"
print "This is a program to analyse the grade of restaurants in NY. "
print "Make sure the csv data file is placed under the current directory. "
print "Several functions may take a bit long time, thank you for your patience."
print "*******************************************************************"
print "Reading the data, please wait..."
try:
raw_data = pd.read_csv('DOHMH_New_York_City_Restaurant_Inspection_Results.csv',low_memory=False)
except IOError:
print "Can not open the data file, please put the DOHMH_New_York_City_Restaurant_Inspection_Results.csv datafile under the current directory "
sys.exit()
print "Cleaning the data, please wait..."
data_process_instance = data_processing.Clean_Raw_Data(raw_data) #create an instance to get the cleaned data
cleaned_data = data_process_instance.get_cleaned_data()
try:
#Q4:print the results of sum of the function results(all restaurants and restaurants by borough)
print "Calculating the score all restaurants, it takes a bit long(more than 40s in my laptop),please wait..."
grade_analysis_functions.print_restaurant_grades_all(cleaned_data)
print "Calculating the score of restaurants by borough,please wait..."
grade_analysis_functions.print_restaurant_grades_by_borough(cleaned_data)
except KeyError:
print "KeyError happens when use grade_analysis_functions"
command = raw_input('if you want to contiue, please enter yes, otherwise will exit the program')
if command!= 'yes':
sys.exit()
for boroname in cleaned_data['BORO'].unique():
print "Generating the grade number satistics graph over time in "+boroname+ " ..."
plotgraph.generate_line_graph(grade_analysis_functions.get_grade_count_values(cleaned_data[cleaned_data['BORO'] == boroname]),boroname.lower())
print "Generating the grade number satistics graph over time in New York City..."
df_whole_city = grade_analysis_functions.get_grade_count_values(cleaned_data)
plotgraph.generate_line_graph(df_whole_city,'nyc')
print "All the 6 graphs are generated and saved, thanks for using"
