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
