Python 利用高德地图api实现经纬度与地址的批量转换（python培训）

def transform(location):
 parameters = {'coordsys':'gps','locations': location, 'key': '7ec25a9c6716bb26f0d25e9fdfa012b8'}
    base = 'http://restapi.amap.com/v3/assistant/coordinate/convert'
    response = requests.get(base, parameters)
    answer = response.json()
    return answer['locations']

def geocode(location):
    parameters = {'location': location, 'key': '7ec25a9c6716bb26f0d25e9fdfa012b8'}
    base = 'http://restapi.amap.com/v3/geocode/regeo'
    response = requests.get(base, parameters)
    answer = response.json()
    return answer['regeocode']['addressComponent']['district'].encode('gbk','replace'),answer['regeocode']['formatted_address'].encode('gbk','replace')

def parse():
 datas = []
 totalListData = pd.read_csv('locs.csv')
 totalListDict = totalListData.to_dict('index')
 for i in range(0, len(totalListDict)):
 datas.append(str(totalListDict[i]['centroidx']) + ',' + str(totalListDict[i]['centroidy']))
 return datas

#!/usr/bin/env
#-*- coding:utf-8 -*-
'''
利用高德地图api实现经纬度与地址的批量转换
'''
import requests
import pandas as pd
import time
import sys
reload(sys)
sys.setdefaultencoding("utf-8")
 
def parse():
 datas = []
 totalListData = pd.read_csv('locs.csv')
 totalListDict = totalListData.to_dict('index')
 for i in range(0, len(totalListDict)):
 datas.append(str(totalListDict[i]['centroidx']) + ',' + str(totalListDict[i]['centroidy']))
 return datas
 
def transform(location):
 parameters = {'coordsys':'gps','locations': location, 'key': '7ec25a9c6716bb26f0d25e9fdfa012b8'}
    base = 'http://restapi.amap.com/v3/assistant/coordinate/convert'
    response = requests.get(base, parameters)
    answer = response.json()
    return answer['locations']
 
def geocode(location):
    parameters = {'location': location, 'key': '7ec25a9c6716bb26f0d25e9fdfa012b8'}
    base = 'http://restapi.amap.com/v3/geocode/regeo'
    response = requests.get(base, parameters)
    answer = response.json()
    return answer['regeocode']['addressComponent']['district'].encode('gbk','replace'),answer['regeocode']['formatted_address'].encode('gbk','replace')
 
if __name__=='__main__':
 i = 0
 count = 0
 df = pd.DataFrame(columns=['location','detail'])
 #locations = parse(item)
 locations = parse()
 for location in locations:
 dist, detail = geocode(transform(location))
 df.loc[i] = [dist, detail]
 i = i + 1
 df.to_csv('locdetail.csv', index =False)