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【python011】经纬度点位可视化html生成(有效方案)

2024-08-04 00:08:51 前端知识 前端哥 138 439 我要收藏

1.熟悉、梳理、总结项目研发实战中的Python开发日常使用中的问题、知识点等,如获取省市等边界区域经纬度进行可视化,从而辅助判断、决策。
2.欢迎点赞、关注、批评、指正,互三走起来,小手动起来!
3.欢迎点赞、关注、批评、指正,互三走起来,小手动起来!

  • 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
  • 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
  • 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

文章目录

    • 1.省市边界经纬度`json`获取并解析
    • 2.读取特定区域经纬度点位`execl`解析并自动生成html文件
    • 3.可视效果

1.省市边界经纬度json获取并解析

  • 经纬度点位初步压缩
    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))
    

2.读取特定区域经纬度点位execl解析并自动生成html文件

  • 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/leaflet@1.9.3/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/bootstrap@5.2.2/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/leaflet@1.9.3/dist/leaflet.css','./leaflet.css' ) \
    #                              .replace( 'https://cdn.jsdelivr.net/npm/bootstrap@5.2.2/dist/css/bootstrap.min.css','./bootstrap.min.css' ) \
    #                              .replace( 'https://cdn.jsdelivr.net/npm/@fortawesome/fontawesome-free@6.2.0/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()
    

3.可视效果

  • 在这里插入图片描述
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