如获取省市等特定区域经纬度进行可视化，从而辅助判断、决策

#!/usr/bin/env python # coding: utf-8 # In[ ]: import re import os import sys import json import nltk import time import pickle import random import base64 import datetime import requests import openpyxl import readline import itertools import numpy as np import pandas as pd from PIL import Image from tqdm import tqdm, trange from bs4 import BeautifulSoup import matplotlib.pyplot as plt from collections import Counter from pypinyin import lazy_pinyin, Style from joblib import Parallel, delayed from sklearn.linear_model import LinearRegression import warnings warnings.filterwarnings('ignore') pd.set_option('display.width', 500) pd.set_option('display.max_rows', 200) pd.set_option('display.max_columns', 200) pd.set_option('display.max_colwidth', 1000) # step 1： 浙江省边界数据 zjbj_url = "https://up.caup.net/guihuayun/json/330000.json" zjbj_datas = requests.get( zjbj_url ) zjbj_datas_json = json.loads( zjbj_datas.content ) zjbj_datas_json_list = zjbj_datas_json['geometry']['coordinates'][-1] zjbj_points = zjbj_datas_json_list[0] zjbj_merged_points = merge_points( zjbj_points, threshold=5000 ) print( len(zjbj_merged_points), len( zjbj_points ) ) # step 2： 杭州市边界数据 hzbj_url = "https://up.caup.net/guihuayun/json/330100.json" datas = requests.get( hzbj_url ) datas_json = json.loads( datas.content ) datas_json_list = datas_json['geometry']['coordinates'][0] points = datas_json_list merged_points = merge_points(points, threshold=4000) print(len(merged_points), len(points)) # In[ ]: import math EARTH_RADIUS = 6371000 # 地球平均半径，单位：米 def haversine(lat1, lon1, lat2, lon2): """计算两个经纬度点之间的距离（单位：米）""" lat1, lon1, lat2, lon2 = map(math.radians, [lat1, lon1, lat2, lon2]) # 将经纬度转换为弧度 dlon = lon2 - lon1 # Haversine公式 dlat = lat2 - lat1 a = math.sin(dlat/2)**2 + math.cos(lat1) * math.cos(lat2) * math.sin(dlon/2)**2 c = 2 * math.asin(math.sqrt(a)) r = EARTH_RADIUS return c * r def merge_points(points, threshold=10): """合并距离在threshold（单位：米）以内的经纬度点""" merged_points = [] merged_points.append( points[0] ) for point in points: distance = haversine( point[0], point[1], merged_points[-1][0], merged_points[-1][1] ) if distance <= threshold: continue else: merged_points.append( point ) return merged_points # step 1： 浙江省边界数据 zjbj_url = "https://up.caup.net/guihuayun/json/330000.json" zjbj_datas = requests.get( zjbj_url ) zjbj_datas_json = json.loads( zjbj_datas.content ) zjbj_datas_json_list = zjbj_datas_json['geometry']['coordinates'][-1] zjbj_points = zjbj_datas_json_list[0] zjbj_merged_points = merge_points( zjbj_points, threshold=5000 ) print( len(zjbj_merged_points), len( zjbj_points ) ) # step 2： 杭州市边界数据 hzbj_url = "https://up.caup.net/guihuayun/json/330100.json" datas = requests.get( hzbj_url ) datas_json = json.loads( datas.content ) datas_json_list = datas_json['geometry']['coordinates'][0] points = datas_json_list merged_points = merge_points(points, threshold=4000) print(len(merged_points), len(points)) import folium import pandas as pd _titles = 'http://webrd02.is.autonavi.com/appmaptile?lang=zh_cn&size=1&scale=1&style=7&x={x}&y={y}&z={z}' _gd_tiles='http://webrd02.is.autonavi.com/appmaptile?lang=zh_cn&size=1&scale=1&style=7&x={x}&y={y}&z={z}' san_map=folium.Map(location=[30.245853, 120.209947], zoom_start=14, tiles= _gd_tiles, attr='default') data=pd.read_excel(r'.\gsddw_youli.xlsx') data2 = data[['youli_dz', 'youli_jd', 'youli_wd']] data2.columns = ['qymc','lng','lat'] data2 = data2[(data2.lng.notna()) & (data2.lng>118) & (data2.lng<121)] # data=pd.read_csv('./stlz.csv',encoding='gbk') data2.head(3) for ii in data2.iterrows(): qymc, lon, lat = ii[1][0], ii[1][1], ii[1][2] folium.Marker([lat,lon], popup=folium.Popup(qymc, max_width=100), tooltip=qymc, icon=folium.Icon(icon='cloud', color='green')).add_to(san_map) folium.Circle([lat,lon], 500, color='yellow', fill_color='yellow', fillOpacity=0.3).add_to(san_map) for ii in merged_points: lon, lat = ii[0], ii[1] folium.Marker([lat, lon], popup=folium.Popup(qymc, max_width=100), tooltip=qymc, icon=folium.Icon(color='red', icon='info-sign')).add_to(san_map) folium.Circle([lat, lon], 500, color='red', fill_color='red', fillOpacity=0.3).add_to(san_map) for ii in zjbj_merged_points: lon, lat = ii[0], ii[1] folium.Marker([lat, lon], popup=folium.Popup(qymc, max_width=100), tooltip=qymc, icon=folium.Icon(color='blue', icon='info-sign')).add_to(san_map) folium.Circle([lat, lon], 500, color='blue', fill_color='blue', fillOpacity=0.3).add_to(san_map) san_map.save('sy_youli_vis.html') html_lis_vis = open( r'./sy_youli_vis.html', encoding='utf8').readlines() html_str_vis = ''.join(html_lis_vis) html_str_vis2 = html_str_vis.replace( 'https://cdn.jsdelivr.net/npm/[email protected]/dist/leaflet.js','./leaflet.js' ) .replace( 'https://code.jquery.com/jquery-3.7.1.min.js','./jquery-3.7.1.min.js' ) # .replace( 'https://cdn.jsdelivr.net/npm/[email protected]/dist/js/bootstrap.bundle.min.js','./bootstrap.bundle.min.js' ) \ # .replace( 'https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.js','./leaflet.awesome-markers.js' ) \ # .replace( 'https://cdn.jsdelivr.net/npm/[email protected]/dist/leaflet.css','./leaflet.css' ) \ # .replace( 'https://cdn.jsdelivr.net/npm/[email protected]/dist/css/bootstrap.min.css','./bootstrap.min.css' ) \ # .replace( 'https://cdn.jsdelivr.net/npm/@fortawesome/[email protected]/css/all.min.css','./all.min.css' ) \ # .replace( 'https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.css','./leaflet.awesome-markers.css' ) \ # .replace( 'https://netdna.bootstrapcdn.com/bootstrap/3.0.0/css/bootstrap.min.css','./bootstrap.min.css' ) html_str_vis2_html = r"sy_youli_vis_new.html" f = open( html_str_vis2_html,'w', encoding='utf8') f.write( html_str_vis2 ) f.close()