pass return ret lon_lst = [] lat_lst = [] for index, row in df.iterrows(): # a. 使用js api进行经纬度转换 # params['latlng'] = str(row['Y']) + ',' + str(row['X']) # lon, lat = getLonLatFromGpssgp(t_url) # b. 使用计算公式进行经纬度转换 lon, lat = gcj02towgs84(row['X'], row['Y']) lon_lst.append(lon) lat_lst.append(lon) if index % 10000 == 0: print '-' * 8 + str(index) + '-' * 8 # 4. 数据转储为Excel import shelve import xlsxwriter df['lon'] = lon_lst df['lat'] = lat_lst file_writer = pd.ExcelWriter('data/fdf.xlsx', engine='xlsxwriter') df.to_excel(file_writer) file_writer.save()
# conding:utf-8 from coordTransform_utils import gcj02towgs84, bd09togcj02 lat, lng = 39.99062,116.306206 result4 = gcj02towgs84(lng, lat) blat, blng = 12941606.14,4826039.41 result5 = bd09togcj02(blng, blat) print result5 def getConnEngine(jdbc_file_path = 'data/jdbc.properties'): import csv from sqlalchemy import create_engine prop = {} with open(jdbc_file_path, 'r') as csvfile: prop_reader = csv.reader(csvfile, delimiter="=") prop = {row[0]:row[1] for row in prop_reader} conn_str = 'postgresql+pg8000://{0}:{1}@{2}:{3}/{4}'.format( prop['jdbc.user'], prop['jdbc.password'], prop['jdbc.host'], prop['jdbc.port'], prop['jdbc.dbname'] ) engine = create_engine(conn_str) return engine