python-地图可视化组件folium的操作

import folium
import webbrowser
m=folium.Map(location=[40.009867,116.485994],zoom_start=10) # 绘制地图，确定聚焦点
folium.Marker([40.2,116.7],popup=\'<b>浮标上面的那个文字</b>\').add_to(m) # 定一个点，放到地图m上
folium.Marker([40.22,116.72],popup=\'<b>浮标上面的那个文字</b>\',icon=folium.Icon(color=\'red\')).add_to(m)
# 把浮标变成红色
folium.Marker([40.24,116.74],popup=\'<b>浮标上面的那个文字</b>\',icon=folium.Icon(color=\'green\',icon=\'info-sign\')).add_to(m)
# 浮标改图样
#标记一个空心的圈
folium.Circle(
 location=[40.2,117.7],
 radius=10000,
 color=\'crimson\',
 popup=\'popup\',
 fill=False
).add_to(m)
#标记一个实心圆
folium.CircleMarker(
 location=[39.2,117.7],
 radius=100,
 popup=\'popup\',
 color=\'#DC143C\',#圈的颜色
 fill=True,
 fill_color=\'#6495ED\' #填充颜色
).add_to(m)
m.save(\'f1.html\')
webbrowser.open(\'f1.html\')

import folium
import webbrowser as wb
# 地图上悬浮显示经纬度
m = folium.Map(
 location=[36.68159, 117.103565],
 zoom_start=10
)
m.add_child(folium.LatLngPopup())
# 手动打点功能
m.add_child(
 folium.ClickForMarker(popup=\'Waypoint\')
)
m.save(\'f2.html\')
wb.open(\'f2.html\')

import numpy as np
import pandas as pd
import seaborn as sns
import folium
import webbrowser
from folium.plugins import HeatMap
#导入数据集：
posi = pd.read_excel(\"D:/Python/File/Cities2015.xlsx\")
posi = posi.dropna()
#生成所需要的数组格式数据：
lat = np.array(posi[\"lat\"][0:len(posi)])
lon = np.array(posi[\"lon\"][0:len(posi)])
pop = np.array(posi[\"pop\"][0:len(posi)],dtype=float)
gdp = np.array(posi[\"GDP\"][0:len(posi)],dtype=float)
data1 = [[lat[i],lon[i],pop[i]] for i in range(len(posi))]
#创建以高德地图为底图的密度图：
map_osm = folium.Map(
 location=[35,110],
 zoom_start=5,
 tiles=\'http://webrd02.is.autonavi.com/appmaptile?lang=zh_cn&size=1&scale=1&style=8&x={x}&y={y}&z={z}\',
 attr=\"&copy; <a href=\"http://ditu.amap.com/\" rel=\"external nofollow\" >高德地图</a>\"
 )
#创建以腾讯地图为底图的密度图：
map_osm = folium.Map(
 location=[35,110],
 zoom_start=5,
 tiles=\'http://rt{s}.map.gtimg.com/realtimerender?z={z}&x={x}&y={y}&type=vector&style=0\',
 attr=\"&copy; <a href=\"http://map.qq.com/\" rel=\"external nofollow\" >腾讯地图</a>\"
 )
#生成交互式地图：
HeatMap(data1).add_to(map_osm)
file_path = r\"D:/Python/Image/People.html\"
map_osm.save(file_path)
webbrowser.open(file_path)

import pandas as pd
import numpy as np
import os
import folium
from folium import plugins
import webbrowser
import geopandas as gp
#数据导入：
full = pd.read_excel(\"D:/Python/File/Cities2015.xlsx\")
full = full.dropna()
#创建地图对象：
schools_map = folium.Map(location=[full[\'lat\'].mean(), full[\'lon\'].mean()], zoom_start=10)
marker_cluster = plugins.MarkerCluster().add_to(schools_map) 
#标注数据点：
for name,row in full.iterrows():
 folium.Marker([row[\"lat\"], row[\"lon\"]], popup=\"{0}:{1}\".format(row[\"cities\"], row[\"GDP\"])).add_to(marker_cluster) 
#逐行读取经纬度，数值，并且打点
#folium.RegularPolygonMarker([row[\"lat\"], row[\"lon\"]], popup=\"{0}:{1}\".format(row[\"cities\"], row[\"GDP\"]),number_of_sides=10,radius=5).add_to(marker_cluster)
schools_map.save(\'schools_map.html\') #保存到本地
webbrowser.open(\'schools_map.html\') #在浏览器中打开

# _*_ coding: utf-8 _*_
__author__ = \'xbr\'
__date__ = \'2019/1/9 15:47\'
 
import numpy as np
import pandas as pd
import folium
import webbrowser
from folium.plugins import HeatMap
 
 
# 读取csv文件,以Dataframe形式保存
df = pd.read_csv(r\"D:\\data\\PM25-20180101.csv\")
# 获取数据个数
num = df.shape[0]
# 获取纬度
lat = np.array(df[\"lat\"][0:num])
# 获取经度
lon = np.array(df[\"lon\"][0:num])
# 获取PM2.5，转化为numpy浮点型
pm25 = np.array(df[\"PM25\"][0:num], dtype=float)
# 将数据制作成[lats, lons, weights]的形式
data1 = [[lat[i], lon[i], pm25[i]] for i in range(num)]
# 绘制Map，中心经纬度[32, 120],开始缩放程度是5倍
map_osm = folium.Map(location=[32, 120], zoom_start=5)
# 将热力图添加到前面建立的map里
HeatMap(data1).add_to(map_osm)
 
file_path = r\"D:\\AirQualityMap.html\"
# 保存为html文件
map_osm.save(file_path)
# 默认浏览器打开
webbrowser.open(file_path)