''' 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 = [