2025年python 抓取行政区划

科技前沿 • 2025-02-10 19:59 • 阅读 44

大家好，我是讯享网，很高兴认识大家。

这是《地图时空大数据爬取》第6章的内容，这篇博客主要是抓取一下行政区划数据，最小是能抓到区县的行政区划数据。然后书里是用arcpy和arcgis再加上python一起来处理的，有些麻烦，我统一用python来处理了，改写了下代码，因为很简单，就不多说了，直接放代码。

讯享网

import basics import geopandas as gpd import pandas as pd import numpy as np import matplotlib.pyplot as plt import json import urllib from urllib.parse import quote import string from shapely.geometry import Point from shapely.geometry import Polygon from shapely.geometry import LineString import pyproj

讯享网

讯享网# 功能：采集行政区域边界 # 返回保存边界信息的BoundryWithAttr对象 def getDistrictBoundry(ak,citycode): districtBoundryUrl = "http://restapi.amap.com/v3/config/district?key="+ak+"&keywords="+citycode+"&subdistrict=0&extensions=all" print(districtBoundryUrl) districtBoundryUrl = quote(districtBoundryUrl, safe=string.printable) json_obj = urllib.request.urlopen(districtBoundryUrl) # json_obj = response.read().decode('utf-8','ignore').replace(u'\xa9', u'') json_data=json.load(json_obj) districts=json_data['districts'] try: polyline = districts[0]['polyline'] centerLon=districts[0]['center'].split(',')[0] centerLat=districts[0]['center'].split(',')[1] except Exception as e: print("error!") pointscoords=polyline.split(';') point=basics.PointWithAttr(0,centerLon,centerLat,"行政区域",citycode) districtBoundry=basics.BoundryWithAttr(point,pointscoords) return districtBoundry

ak = "放上你的ak就行" citycodes={ 
   '上城区':'','下城区':'','江干区':'',"拱墅区":'',"西湖区":'','滨江区':'', '萧山区':'','余杭区':'','富阳区':'','临安区':'','桐庐县':'','淳安县':'', '建德市':''} polygon_list = [] centerX_list = [] centerY_list = [] for citycode in citycodes.keys(): districtBoundry = getDistrictBoundry(ak,citycode) tmp = districtBoundry.boundrycoords for i in range(len(tmp)): tmp[i] = [float(tmp[i].split(',')[0]) , float(tmp[i].split(',')[1])] tmp = Polygon(tmp) polygon_list.append(tmp) centerX_list.append(districtBoundry.point.lon) centerY_list.append(districtBoundry.point.lat)

讯享网# 将爬取得到的杭州市行政区保存为shp文件 gdf = { 
   'geometry':polygon_list , 'centerLon':centerX_list , 'centerLat':centerY_list , 'name':citycodes.keys(),'adacode':citycodes.values()} gdf = gpd.GeoDataFrame(gdf , crs = None) gdf

2025年python 抓取行政区划

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