基于folium做地图可视化

本文主要是介绍基于folium做地图可视化，希望对大家解决编程问题提供一定的参考价值，需要的开发者们随着小编来一起学习吧！

由于内网环境,缺少地图~所以就考虑了使用folium+geojson来做简单的可视化.

import json
import folium
with open('天津市.json', 'r', encoding='utf-8') as f:china_geojson = json.load(f)# 创建一个没有背景瓦片的地图对象
m = folium.Map(location=[35, 105], zoom_start=4, tiles=None)# 添加geojson数据到地图中
folium.GeoJson(china_geojson,style_function=lambda feature: {'fillColor': '#ffff00','color': 'black','weight': 2,'dashArray': '5, 5'}
).add_to(m)# 在notebook中展示地图
m

使用pandas读取位置数据,然后可视化.

def visualize_trajectory(data):# 创建一个Folium地图对象with open('天津市.json', 'r', encoding='utf-8') as f:china_geojson = json.load(f)# 创建一个没有背景瓦片的地图对象m = folium.Map(location=[35, 105], zoom_start=4, tiles=None)# 添加geojson数据到地图中folium.GeoJson(china_geojson,style_function=lambda feature: {'fillColor': '#ffff00','color': 'black','weight': 2,'dashArray': '5, 5'}).add_to(m)# 对于每个轨迹点，添加标记for i in range(len(data)):folium.Marker(location=[data['Latitude'].iloc[i], data['Longitude'].iloc[i]], popup=data['User_ID'].iloc[i]).add_to(m)# 使用轨迹点创建一条线，表示移动路径for i in range(len(data) - 1):folium.PolyLine([[data['Latitude'].iloc[i], data['Longitude'].iloc[i]], [data['Latitude'].iloc[i + 1], data['Longitude'].iloc[i + 1]]], color='blue', weight=2).add_to(m)# 返回可视化的地图return m

模拟:

visualized_map = visualize_trajectory(example_df)
visualized_map

模拟数据生成脚本:

import pandas as pd
import random
import timedef generate_user_ids(num_users):"""生成指定数量的用户ID"""return [f"User_{i}" for i in range(num_users)]def generate_timestamps(start_time, num_points):"""生成一系列连续的时间戳"""return [start_time + i for i in range(num_points)]def generate_random_point(center_lat, center_lon, max_distance):"""生成在给定经纬度为中心，指定距离范围内的随机经纬度点"""# 将距离转换为角度max_distance_angle = max_distance / 6371.0# 生成随机角度dlat = random.uniform(-max_distance_angle, max_distance_angle)dlon = random.uniform(-max_distance_angle, max_distance_angle)# 计算新的经纬度new_lat = center_lat + dlatnew_lon = center_lon + dlonreturn (new_lat, new_lon)def simulate_trajectory(num_users, start_time, num_points, center_lat, center_lon, max_distance):"""生成轨迹数据"""user_ids = generate_user_ids(num_users)all_data = []for user_id in user_ids:timestamps = generate_timestamps(start_time, num_points)current_point = (center_lat, center_lon)for timestamp in timestamps:current_point = generate_random_point(*current_point, max_distance)all_data.append([user_id, timestamp] + list(current_point))# 创建DataFramecolumns = ['User_ID', 'Timestamp', 'Latitude', 'Longitude']df = pd.DataFrame(all_data, columns=columns)return df
# #############
#example_df = simulate_trajectory(122, int(time.time()), 10, 39.129484,117.220074, 1000)

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