def search_city(state): search_engine = ZipcodeSearchEngine() state = search_engine.by_city(str(state)) cities = [] for i in state: cities.append(i.City) return cities
def filter_posts(self, service, location, company, rating): search = ZipcodeSearchEngine() if service != "None" and location != "None" and company == 'None' and rating == 'None': res = search.by_city(location) city_zips = [] for i in range(0, len(res)): city_zips.append(res[i].Zipcode) return Post.query.join(Company).filter( Company.company_zipcode.in_(city_zips), Post.service_id == service)
def search_zip(city): search_engine = ZipcodeSearchEngine() city = search_engine.by_city(str(city)) zipcodes = [] for i in city: zipcodes.append(i.Zipcode) return zipcodes
df = pd.read_csv("inputDB.csv") for i in range(len(df)): if (i % 10000 == 0): print("Cleaned", i, " rows") zip = prepare_zip(df) ssn = prepare_ssn(df) clean_ssn(df, i, ssn) if len(zip) == 5: set_by_zip(zip, df, i) else: try: L_city = search._find_city(df['City'].values[i], best_match=True) df.iloc[i, df.columns.get_loc('City')] = L_city[0] res = search.by_city(L_city[0]) if (len(res) == 0): try: L_state = search._find_city(df['State'].values[i], best_match=True) df.iloc[i, df.columns.get_loc('State')] = L_state[0] res = search.by_state(L_state[0]) if (len(res) == 0): set_unknown(df, i) else: set_by_state_and_city(res, L_state, df) except ValueError: set_unknown(df, i) else: set_by_city(df, i, res) except ValueError: