'''
LE = LabelEncoder()
food_inspections['ViolLevel'] = food_inspections['ViolLevel'].fillna(0)
food_inspections['ViolLevel'] = LE.fit_transform(
food_inspections['ViolLevel'])
return food_inspections
'''''' '''''' '''''' '''''' '''''' ''''''
' O B T A I N Y E L P D A T A '
'''''' '''''' '''''' '''''' '''''' ''''''
#First check if we can scrape data from Yelp!
try:
results = Yelp.search('food', 'Boston MA')
except:
print "ERROR: Could not extract data from Yelp. Looks like Yelp was unable to authenticate you. Do you have the necessary authentication tokens and keys? Check Yelp.py for more information."
sys.exit()
#Load data
food_inspections = pd.read_csv('fixed_locations.csv',
sep=',',
low_memory=False)
food_inspections = food_inspections.iloc[::-1]
#Convert the set {NaN,*,**,***} in ViolLevel to the set {0,1,2,3}
food_inspections = fixViolLevel(food_inspections)
#Drop the unnecessary columns
columns = [
