def test_graph_generator(self):
try:
os.remove('./grade_improvement_nyc.pdf')
except OSError:
pass
cleaned_df = dc.data_loader_and_cleaner('DOHMH_New_York_City_Restaurant_Inspection_Results.csv').cleaned_df
nyc_grades_dictionary = agg._nyc_grades_by_year(cleaned_df)
gg.grades_by_year_graph_generator(nyc_grades_dictionary, "nyc")
self.assertTrue(os.path.isfile('grade_improvement_nyc'))
# This function returns the total improvement for NYC required in question 4 of Assignment 10.
# It sums the test_restaurant_grades function output of each restaurant in the city and prints it.
gc._nyc_total_restaurant_improvement(cleaned_df)
# This function returns the total improvement for each borough of NYC required in question 4 of Assignment 10.
# It sums the test_restaurant_grades function output of each restaurant in each borough and prints it.
gc._total_restaurant_improvement_by_boro(cleaned_df)
# The following two functions aggregate the total number of distinct grades/restaurants by year and saves them in
# two dictionaries, one for the whole city and one for each borough.
nyc_grades_dictionary = agg._nyc_grades_by_year(cleaned_df)
boros_grades_dictionary = agg._nyc_boros_grades_by_year(cleaned_df)
# Next, we generate the chart of the total number of restaurants in New York City for each grade over time.
gg.grades_by_year_graph_generator(nyc_grades_dictionary, "nyc")
# Finally, we generate the charts of the total number of restaurants by borough for each grade over time.
for boro in boros_grades_dictionary.keys():
if boro == 'STATEN ISLAND':
boro_name = 'staten' #This condition was added to produce correct filename for the Staten Island borough graph file required in problem 5
else:
boro_name = boro
gg.grades_by_year_graph_generator(boros_grades_dictionary[boro], boro_name)
except LookupError as e:
print str(e)
except TypeError as e:
print str(e)
except IOError as e:
print str(e)
