通过经纬度算距离_办公自动化90批量查询两点驾驶距离和时长

1、目的：统计物流运距

2、方法：通过两地点的经纬度查询驾驶距离和时长

(问物流IT直接要了各线路点的经纬度，无耻的我为了口径统一只能这么干啦。如果自己做的话可以试试百度地图API或者有两个网站可批量查询【https://maplocation.sjfkai.com/】or【待补充】)

3、工具：python、百度API

4、素材：

①像这样格式的excel

②在百度地图申请key：

网址：http://lbsyun.baidu.com/

a：选择web服务API

b：选择获取秘钥

c：创建应用

d：填写信息后提交(主要是名称和IP)

e：key即红线框出来的

代码如下：跑起来还是很爽的

注意一个参数：tactics

# -*- coding: utf-8 -*-import pandasimport csvimport reimport timeimport jsonfrom urllib.request import urlopenimport urllib# 原数据文件格式：序号 + 起点纬度 + 起点经度 + 终点纬度 + 终点经度origin_path = r"D:\1工作\01-按时间顺序开始\2020\20200727供应链经营管理审计报告\测试路线距离+时长\测试1.xlsx"   # 原始坐标文件路径result_path = r"D:\1工作\01-按时间顺序开始\2020\20200727供应链经营管理审计报告\测试路线距离+时长\测试1结果.xlsx"   # 爬取数据文件保存路径"""# 百度地图提供的api服务网址"http://api.map.baidu.com/routematrix/v2/driving?output=json"  # 驾车(routematrix 批量算路)'http://api.map.baidu.com/routematrix/v2/riding?output=json'  # 骑行'http://api.map.baidu.com/routematrix/v2/walking?output=json'  # 步行'http://api.map.baidu.com/direction/v2/transit?output=json'  # bus(direction路线规划)"""# 声明坐标格式,bd09ll(百度经纬度坐标);bd09mc(百度摩卡托坐标);gcj02(国测局加密坐标),wgs84(gps设备获取的坐标)cod = r"&coord_type=bd09ll"# AK为从百度地图网站申请的秘钥AK = ['这里填你在百度地图api申请到的key',]dfBase = pandas.read_excel(origin_path, names=['序号','起点纬度','起点经度','终点纬度','终点经度'])dfBase.head()# print(dfBase)dataList = []  # 储存获取的路线数据akn = 0  # 使用第几个akfor i in range(len(dfBase)):    print(i)    ak = AK[akn]    out_lat = dfBase.at[i,'起点纬度']    out_lng = dfBase.at[i,'起点经度']    des_lat = dfBase.at[i,'终点纬度']    des_lng = dfBase.at[i,'终点经度']    """    # 获取驾车路径:常规路线规划(不考虑路况)     以下是可选参数    #  tactics =10不走高速;=11常规路线;=12距离较短;=13距离较短    """    url_drive = r"http://api.map.baidu.com/routematrix/v2/driving?output=json&origins={0},{1}&destinations={2},{3}&{4}&tactics=11&ak={4}".format(out_lat,out_lng,des_lat,des_lng,ak)    result_drive = json.loads(urlopen(url_drive).read())  # json转dict    status_drive = result_drive['status']    print('ak秘钥：{0}  获取驾车路线状态码status：{1}'.format(ak, status_drive))    if status_drive == 0:  # 状态码为0：无异常        distance_drive = result_drive['result'][0]['distance']['value']  # 里程(米)        timesec_drive = result_drive['result'][0]['duration']['value']  # 耗时(秒)    elif status_drive == 302 or status_drive == 210 or status_drive == 201:  # 302:额度不足;210:IP验证未通过        distance_drive = timesec_drive = 'AK错误'        akn += 1        ak = AK[akn]    else:        distance_drive = timesec_drive = '请求错误'    dataList.append([ak,status_drive,distance_drive,timesec_drive])dfAll = pandas.DataFrame(dataList, columns=['ak','status_drive','distance_drive','timesec_drive'])dfAlldfAll.to_excel(result_path )

跑完之后输出

分享一个tips：

把秒转换为*天*小时*分钟*秒

=TEXT(M2/86400,"d天h小时m分钟s秒")

参考文献：https://blog.csdn.net/mg_aping/article/details/81711708?biz_id=102&utm_term=pyton%E7%99%BE%E5%BA%A6api%E9%A9%BE%E9%A9%B6%E8%B7%9D%E7%A6%BB&utm_medium=distribute.pc_search_result.none-task-blog-2~all~sobaiduweb~default-0-81711708&spm=1018.2118.3001.4187

参考代码：

# -*- coding: utf-8 -*-import pandasimport csvimport reimport timeimport jsonfrom urllib.request import urlopenimport urllib# 原数据文件格式：序号 + 起点纬度 + 起点经度 + 终点纬度 + 终点经度origin_path = 'E://data/起点终点坐标.xlsx'   # 原始坐标文件路径result_path = 'E://data/result122901.txt'   # 爬取数据文件保存路径"""# 百度地图提供的api服务网址"http://api.map.baidu.com/routematrix/v2/driving?output=json"  # 驾车(routematrix 批量算路)'http://api.map.baidu.com/routematrix/v2/riding?output=json'  # 骑行'http://api.map.baidu.com/routematrix/v2/walking?output=json'  # 步行'http://api.map.baidu.com/direction/v2/transit?output=json'  # bus(direction路线规划)"""# 声明坐标格式,bd09ll(百度经纬度坐标);bd09mc(百度摩卡托坐标);gcj02(国测局加密坐标),wgs84(gps设备获取的坐标)cod = r"&coord_type=bd09ll"# AK为从百度地图网站申请的秘钥AK = ['4KQuylnCQEIWYG65tEMQ9spP4FFBvNoI',]dfBase = pandas.read_excel(origin_path, names=['序号','起点纬度','起点经度','终点纬度','终点经度'])dfBase.head()dataList = []  # 储存获取的路线数据akn = 0  # 使用第几个akfor i in range(len(dfBase)):    print(i)    ak = AK[akn]    out_lat = dfBase.at[i,'起点纬度']    out_lng = dfBase.at[i,'起点经度']    des_lat = dfBase.at[i,'终点纬度']    des_lng = dfBase.at[i,'终点经度']    """    # 获取驾车路径:常规路线规划(不考虑路况)     以下是可选参数    #  tactics =10不走高速;=11常规路线;=12距离较短;=13距离较短    """    url_drive = r"http://api.map.baidu.com/routematrix/v2/driving?output=json&origins={0},{1}&destinations={2},{3}&{4}&tactics=11&ak={4}".format(out_lat,out_lng,des_lat,des_lng,ak)    result_drive = json.loads(urlopen(url_drive).read())  # json转dict    status_drive = result_drive['status']    print('ak秘钥：{0}  获取驾车路线状态码status：{1}'.format(ak, status_drive))    if status_drive == 0:  # 状态码为0：无异常        distance_drive = result_drive['result'][0]['distance']['value']  # 里程(米)        timesec_drive = result_drive['result'][0]['duration']['value']  # 耗时(秒)    elif status_drive == 302 or status_drive == 210 or status_drive == 201:  # 302:额度不足;210:IP验证未通过        distance_drive = timesec_drive = 'AK错误'        akn += 1        ak = AK[akn]    else:        distance_drive = timesec_drive = '请求错误'    """    ### 以下是乘车规划    可选参数    tac_bus = r'&tactics_incity=0'    # 市内公交换乘策略 可选，默认为0      0推荐；1少换乘；2少步行；3不坐地铁；4时间短；5地铁优先    city_bus = r'&tactics_intercity=0'    # 跨城公交换乘策略  可选，默认为0    0时间短；1出发早；2价格低；    city_type = r'&trans_type_intercity=0'    # 跨城交通方式策略  可选，默认为0  0火车优先；1飞机优先；2大巴优先；    """    url_bus = r'http://api.map.baidu.com/direction/v2/transit?output=json&origin={0},{1}&destination={2},{3}&{4}&ak={4}'.format(out_lat,out_lng,des_lat,des_lng,ak)    print(url_bus)    result_bus = json.loads(urlopen(url_bus).read())    status_bus = result_bus['status']    print('ak秘钥：{0}  获取乘车路线状态码status：{1}'.format(ak, status_bus))    if status_bus == 0:        rsls = result_bus['result']['routes']        if rsls == []:    # 无方案时状态也为0，但只返回一个空list            distance_bus = timesec_bus = cost_bus = '无公交方案'        else:            distance_bus = result_bus['result']['routes'][0]['distance']  # 乘车路线距离总长(米)            timesec_bus = result_bus['result']['routes'][0]['duration']  # 乘车时间(秒)            cost_bus = result_bus['result']['routes'][0]['price']  # 乘车费用(元)    elif status_bus == 302 or status_bus == 210 or status_bus == 201:        distance_bus = timesec_bus = cost_bus = 'AK错误'        akn += 1        ak = AK[akn]    elif status_bus == 1001:        distance_bus = timesec_bus = cost_bus = '无公交方案'    else:  # 其他类型状态码(服务器错误)        distance_bus = timesec_bus = cost_bus = '请求错误'    dataList.append([ak,status_drive,distance_drive,timesec_drive,status_bus,distance_bus,timesec_bus,cost_bus])dfAll = pandas.DataFrame(dataList, columns=['ak','status_drive','distance_drive','timesec_drive','status_bus','distance_bus','timesec_bus','cost_bus'])dfAllresult_path = r'E://data/路线规划结果.xls'   # 爬取数据文件保存路径dfAll.to_excel(result_path )