{"id":1180546,"date":"2025-01-15T18:38:09","date_gmt":"2025-01-15T10:38:09","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1180546.html"},"modified":"2025-01-15T18:38:14","modified_gmt":"2025-01-15T10:38:14","slug":"python%e5%a6%82%e4%bd%95%e7%bb%98%e5%88%b6%e4%b8%ad%e5%9b%bd%e5%9c%b0%e5%9b%be","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1180546.html","title":{"rendered":"python\u5982\u4f55\u7ed8\u5236\u4e2d\u56fd\u5730\u56fe"},"content":{"rendered":"

\"python\u5982\u4f55\u7ed8\u5236\u4e2d\u56fd\u5730\u56fe\"<\/p>\n

Python \u7ed8\u5236\u4e2d\u56fd\u5730\u56fe\u7684\u65b9\u6cd5\u6709\u5f88\u591a\u79cd\uff0c\u5e38\u7528\u7684\u65b9\u6cd5\u5305\u62ec\uff1a\u4f7f\u7528Basemap\u5e93\u3001\u4f7f\u7528Geopandas\u5e93\u3001\u4f7f\u7528Pyecharts\u5e93\u3001\u4f7f\u7528Folium\u5e93\u3002<\/strong> \u5176\u4e2d\uff0c\u4f7f\u7528Pyecharts\u5e93\u662f\u6bd4\u8f83\u7b80\u5355\u4e14\u529f\u80fd\u4e30\u5bcc\u7684\u4e00\u79cd\u65b9\u6cd5\u3002Pyecharts\u662f\u4e00\u4e2a\u7528\u4e8e\u751f\u6210Echarts\u56fe\u8868\u7684Python\u5e93\uff0c\u652f\u6301\u591a\u79cd\u56fe\u8868\u7c7b\u578b\uff0c\u5176\u4e2d\u5c31\u5305\u62ec\u5730\u56fe\u3002\u4e0b\u9762\u6211\u4eec\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u5982\u4f55\u4f7f\u7528Pyecharts\u5e93\u7ed8\u5236\u4e2d\u56fd\u5730\u56fe\u3002<\/p>\n<\/p>\n

\u4e00\u3001\u5b89\u88c5\u4e0e\u914d\u7f6e<\/h3>\n<\/p>\n

\u5728\u5f00\u59cb\u7ed8\u5236\u4e2d\u56fd\u5730\u56fe\u4e4b\u524d\uff0c\u6211\u4eec\u9700\u8981\u5b89\u88c5\u76f8\u5173\u7684Python\u5e93\u3002\u9996\u5148\u662fPyecharts\u5e93\uff0c\u53ef\u4ee5\u4f7f\u7528pip\u547d\u4ee4\u8fdb\u884c\u5b89\u88c5\uff1a<\/p>\n<\/p>\n

pip install pyecharts<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u6b64\u5916\uff0c\u5982\u679c\u60a8\u9700\u8981\u66f4\u8be6\u7ec6\u7684\u5730\u7406\u6570\u636e\uff0c\u53ef\u4ee5\u5b89\u88c5 pyecharts_snapshot<\/code> \u4ee5\u4fbf\u66f4\u597d\u5730\u4fdd\u5b58\u56fe\u8868\uff1a<\/p>\n<\/p>\n
pip install pyecharts_snapshot<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e8c\u3001\u57fa\u7840\u5730\u56fe\u7ed8\u5236<\/h3>\n<\/p>\n
1\u3001\u7ed8\u5236\u7b80\u5355\u7684\u4e2d\u56fd\u5730\u56fe<\/h4>\n<\/p>\n
\u9996\u5148\uff0c\u6211\u4eec\u6765\u7ed8\u5236\u4e00\u5f20\u7b80\u5355\u7684\u4e2d\u56fd\u5730\u56fe\u3002\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528 Map<\/code> \u7c7b\uff0c\u5e76\u6307\u5b9a\u5730\u56fe\u7c7b\u578b\u4e3a china<\/code>\uff1a<\/p>\n<\/p>\n
from pyecharts.charts import Map<\/p>\n
from pyecharts import options as opts<\/p>\n
\u521b\u5efa\u5730\u56fe\u5bf9\u8c61<\/strong><\/h2>\n
map = Map()<\/p>\n
\u6dfb\u52a0\u4e2d\u56fd\u5730\u56fe\u6570\u636e<\/strong><\/h2>\n
map.add("", [("\u5317\u4eac\u5e02", 1), ("\u4e0a\u6d77\u5e02", 1), ("\u5e7f\u4e1c\u7701", 1)], "china")<\/p>\n
\u8bbe\u7f6e\u5168\u5c40\u914d\u7f6e\u9879<\/strong><\/h2>\n
map.set_global_opts(<\/p>\n
    title_opts=opts.TitleOpts(title="\u4e2d\u56fd\u5730\u56fe\u793a\u4f8b"),<\/p>\n
    visualmap_opts=opts.VisualMapOpts(max_=200),<\/p>\n
)<\/p>\n
\u6e32\u67d3\u5730\u56fe<\/strong><\/h2>\n
map.render("china_map.html")<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u6dfb\u52a0\u7701\u4efd\u6570\u636e<\/h4>\n<\/p>\n
\u6211\u4eec\u53ef\u4ee5\u5728\u5730\u56fe\u4e0a\u6dfb\u52a0\u66f4\u591a\u7684\u7701\u4efd\u6570\u636e\uff0c\u5e76\u8bbe\u7f6e\u4e0d\u540c\u7684\u989c\u8272\u8868\u793a\uff1a<\/p>\n<\/p>\n
from pyecharts.charts import Map<\/p>\n
from pyecharts import options as opts<\/p>\n
\u521b\u5efa\u5730\u56fe\u5bf9\u8c61<\/strong><\/h2>\n
map = Map()<\/p>\n
\u6dfb\u52a0\u4e2d\u56fd\u5730\u56fe\u6570\u636e<\/strong><\/h2>\n
data = [("\u5317\u4eac\u5e02", 100), ("\u4e0a\u6d77\u5e02", 200), ("\u5e7f\u4e1c\u7701", 300), ("\u56db\u5ddd\u7701", 400), ("\u6d59\u6c5f\u7701", 500)]<\/p>\n
map.add("", data, "china")<\/p>\n
\u8bbe\u7f6e\u5168\u5c40\u914d\u7f6e\u9879<\/strong><\/h2>\n
map.set_global_opts(<\/p>\n
    title_opts=opts.TitleOpts(title="\u4e2d\u56fd\u7701\u4efd\u5730\u56fe"),<\/p>\n
    visualmap_opts=opts.VisualMapOpts(max_=500),<\/p>\n
)<\/p>\n
\u6e32\u67d3\u5730\u56fe<\/strong><\/h2>\n
map.render("china_province_map.html")<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e09\u3001\u7ec6\u5316\u5730\u56fe\u7ed8\u5236<\/h3>\n<\/p>\n
1\u3001\u7ed8\u5236\u7701\u4efd\u5730\u56fe<\/h4>\n<\/p>\n
\u9664\u4e86\u7ed8\u5236\u4e2d\u56fd\u5730\u56fe\uff0c\u6211\u4eec\u8fd8\u53ef\u4ee5\u7ed8\u5236\u67d0\u4e2a\u7701\u4efd\u7684\u8be6\u7ec6\u5730\u56fe\u3002\u4f8b\u5982\uff0c\u7ed8\u5236\u5e7f\u4e1c\u7701\u5730\u56fe\uff1a<\/p>\n<\/p>\n
from pyecharts.charts import Map<\/p>\n
from pyecharts import options as opts<\/p>\n
\u521b\u5efa\u5730\u56fe\u5bf9\u8c61<\/strong><\/h2>\n
map = Map()<\/p>\n
\u6dfb\u52a0\u5e7f\u4e1c\u7701\u5730\u56fe\u6570\u636e<\/strong><\/h2>\n
data = [("\u5e7f\u5dde\u5e02", 100), ("\u6df1\u5733\u5e02", 200), ("\u73e0\u6d77\u5e02", 300), ("\u6c55\u5934\u5e02", 400), ("\u4f5b\u5c71\u5e02", 500)]<\/p>\n
map.add("", data, "\u5e7f\u4e1c")<\/p>\n
\u8bbe\u7f6e\u5168\u5c40\u914d\u7f6e\u9879<\/strong><\/h2>\n
map.set_global_opts(<\/p>\n
    title_opts=opts.TitleOpts(title="\u5e7f\u4e1c\u7701\u5730\u56fe"),<\/p>\n
    visualmap_opts=opts.VisualMapOpts(max_=500),<\/p>\n
)<\/p>\n
\u6e32\u67d3\u5730\u56fe<\/strong><\/h2>\n
map.render("guangdong_map.html")<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u6dfb\u52a0\u81ea\u5b9a\u4e49\u6570\u636e<\/h4>\n<\/p>\n
\u6211\u4eec\u53ef\u4ee5\u5728\u5730\u56fe\u4e0a\u6dfb\u52a0\u81ea\u5b9a\u4e49\u7684\u6570\u636e\uff0c\u5e76\u901a\u8fc7\u989c\u8272\u533a\u5206\u4e0d\u540c\u7684\u533a\u57df\u3002\u4f8b\u5982\uff0c\u6dfb\u52a0\u75ab\u60c5\u6570\u636e\uff1a<\/p>\n<\/p>\n
from pyecharts.charts import Map<\/p>\n
from pyecharts import options as opts<\/p>\n
\u521b\u5efa\u5730\u56fe\u5bf9\u8c61<\/strong><\/h2>\n
map = Map()<\/p>\n
\u6dfb\u52a0\u4e2d\u56fd\u5730\u56fe\u6570\u636e<\/strong><\/h2>\n
data = [("\u5317\u4eac\u5e02", 10), ("\u4e0a\u6d77\u5e02", 20), ("\u5e7f\u4e1c\u7701", 30), ("\u56db\u5ddd\u7701", 40), ("\u6d59\u6c5f\u7701", 50)]<\/p>\n
map.add("", data, "china")<\/p>\n
\u8bbe\u7f6e\u5168\u5c40\u914d\u7f6e\u9879<\/strong><\/h2>\n
map.set_global_opts(<\/p>\n
    title_opts=opts.TitleOpts(title="\u4e2d\u56fd\u75ab\u60c5\u5730\u56fe"),<\/p>\n
    visualmap_opts=opts.VisualMapOpts(max_=50),<\/p>\n
)<\/p>\n
\u6e32\u67d3\u5730\u56fe<\/strong><\/h2>\n
map.render("china_covid_map.html")<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u56db\u3001\u8fdb\u9636\u7ed8\u5236\u6280\u5de7<\/h3>\n<\/p>\n
1\u3001\u4f7f\u7528Geopandas\u7ed8\u5236\u5730\u56fe<\/h4>\n<\/p>\n
\u9664\u4e86\u4f7f\u7528Pyecharts\uff0c\u6211\u4eec\u8fd8\u53ef\u4ee5\u4f7f\u7528Geopandas\u5e93\u6765\u7ed8\u5236\u66f4\u4e3a\u590d\u6742\u7684\u5730\u56fe\u3002Geopandas\u662f\u4e00\u4e2a\u7528\u4e8e\u5730\u7406\u6570\u636e\u5904\u7406\u548c\u5206\u6790\u7684Python\u5e93\u3002\u6211\u4eec\u53ef\u4ee5\u5229\u7528\u5b83\u6765\u8bfb\u53d6\u548c\u7ed8\u5236Shapefile\u683c\u5f0f\u7684\u5730\u56fe\u6570\u636e\u3002<\/p>\n<\/p>\n
import geopandas as gpd<\/p>\n
import matplotlib.pyplot as plt<\/p>\n
\u8bfb\u53d6\u4e2d\u56fd\u5730\u56feShapefile\u6570\u636e<\/strong><\/h2>\n
china = gpd.read_file("china_shapefile.shp")<\/p>\n
\u7ed8\u5236\u5730\u56fe<\/strong><\/h2>\n
fig, ax = plt.subplots(1, 1, figsize=(10, 10))<\/p>\n
china.plot(ax=ax, color='white', edgecolor='black')<\/p>\n
\u663e\u793a\u5730\u56fe<\/strong><\/h2>\n
plt.title("\u4e2d\u56fd\u5730\u56fe")<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u4f7f\u7528Folium\u7ed8\u5236\u4ea4\u4e92\u5f0f\u5730\u56fe<\/h4>\n<\/p>\n
Folium\u662f\u4e00\u4e2a\u7528\u4e8e\u751f\u6210\u4ea4\u4e92\u5f0f\u5730\u56fe\u7684Python\u5e93\u3002\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528Folium\u6765\u521b\u5efa\u4ea4\u4e92\u5f0f\u7684\u4e2d\u56fd\u5730\u56fe\uff0c\u5e76\u5728\u5730\u56fe\u4e0a\u6dfb\u52a0\u6807\u8bb0\u548c\u56fe\u5c42\u3002<\/p>\n<\/p>\n
import folium<\/p>\n
\u521b\u5efa\u5730\u56fe\u5bf9\u8c61<\/strong><\/h2>\n
m = folium.Map(location=[35.8617, 104.1954], zoom_start=4)<\/p>\n
\u6dfb\u52a0\u6807\u8bb0<\/strong><\/h2>\n
folium.Marker([39.9042, 116.4074], popup="\u5317\u4eac\u5e02").add_to(m)<\/p>\n
folium.Marker([31.2304, 121.4737], popup="\u4e0a\u6d77\u5e02").add_to(m)<\/p>\n
folium.Marker([23.1291, 113.2644], popup="\u5e7f\u5dde\u5e02").add_to(m)<\/p>\n
\u663e\u793a\u5730\u56fe<\/strong><\/h2>\n
m.save("china_folium_map.html")<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e94\u3001\u5e94\u7528\u5b9e\u4f8b<\/h3>\n<\/p>\n
1\u3001\u7ed8\u5236\u4e2d\u56fd\u5404\u7701GDP\u6570\u636e\u5730\u56fe<\/h4>\n<\/p>\n
\u6211\u4eec\u53ef\u4ee5\u5229\u7528Pyecharts\u7ed8\u5236\u4e2d\u56fd\u5404\u7701\u7684GDP\u6570\u636e\u5730\u56fe\uff0c\u5e76\u901a\u8fc7\u989c\u8272\u6df1\u6d45\u6765\u8868\u793aGDP\u7684\u9ad8\u4f4e\u3002<\/p>\n<\/p>\n
from pyecharts.charts import Map<\/p>\n
from pyecharts import options as opts<\/p>\n
\u521b\u5efa\u5730\u56fe\u5bf9\u8c61<\/strong><\/h2>\n
map = Map()<\/p>\n
\u6dfb\u52a0\u4e2d\u56fd\u5404\u7701GDP\u6570\u636e<\/strong><\/h2>\n
gdp_data = [("\u5317\u4eac\u5e02", 36102), ("\u4e0a\u6d77\u5e02", 38700), ("\u5e7f\u4e1c\u7701", 107671), ("\u56db\u5ddd\u7701", 48598), ("\u6d59\u6c5f\u7701", 61087)]<\/p>\n
map.add("", gdp_data, "china")<\/p>\n
\u8bbe\u7f6e\u5168\u5c40\u914d\u7f6e\u9879<\/strong><\/h2>\n
map.set_global_opts(<\/p>\n
    title_opts=opts.TitleOpts(title="\u4e2d\u56fd\u5404\u7701GDP\u6570\u636e"),<\/p>\n
    visualmap_opts=opts.VisualMapOpts(max_=110000),<\/p>\n
)<\/p>\n
\u6e32\u67d3\u5730\u56fe<\/strong><\/h2>\n
map.render("china_gdp_map.html")<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u7ed8\u5236\u4e2d\u56fd\u5404\u7701\u4eba\u53e3\u5bc6\u5ea6\u5730\u56fe<\/h4>\n<\/p>\n
\u6211\u4eec\u53ef\u4ee5\u5229\u7528Pyecharts\u7ed8\u5236\u4e2d\u56fd\u5404\u7701\u7684\u4eba\u53e3\u5bc6\u5ea6\u5730\u56fe\uff0c\u5e76\u901a\u8fc7\u989c\u8272\u6df1\u6d45\u6765\u8868\u793a\u4eba\u53e3\u5bc6\u5ea6\u7684\u9ad8\u4f4e\u3002<\/p>\n<\/p>\n
from pyecharts.charts import Map<\/p>\n
from pyecharts import options as opts<\/p>\n
\u521b\u5efa\u5730\u56fe\u5bf9\u8c61<\/strong><\/h2>\n
map = Map()<\/p>\n
\u6dfb\u52a0\u4e2d\u56fd\u5404\u7701\u4eba\u53e3\u5bc6\u5ea6\u6570\u636e<\/strong><\/h2>\n
population_density_data = [("\u5317\u4eac\u5e02", 1318), ("\u4e0a\u6d77\u5e02", 3819), ("\u5e7f\u4e1c\u7701", 624), ("\u56db\u5ddd\u7701", 179), ("\u6d59\u6c5f\u7701", 532)]<\/p>\n
map.add("", population_density_data, "china")<\/p>\n
\u8bbe\u7f6e\u5168\u5c40\u914d\u7f6e\u9879<\/strong><\/h2>\n
map.set_global_opts(<\/p>\n
    title_opts=opts.TitleOpts(title="\u4e2d\u56fd\u5404\u7701\u4eba\u53e3\u5bc6\u5ea6"),<\/p>\n
    visualmap_opts=opts.VisualMapOpts(max_=4000),<\/p>\n
)<\/p>\n
\u6e32\u67d3\u5730\u56fe<\/strong><\/h2>\n
map.render("china_population_density_map.html")<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u516d\u3001\u603b\u7ed3\u4e0e\u5c55\u671b<\/h3>\n<\/p>\n
\u901a\u8fc7\u4ee5\u4e0a\u5185\u5bb9\uff0c\u6211\u4eec\u53ef\u4ee5\u770b\u5230\uff0c\u4f7f\u7528Python\u7ed8\u5236\u4e2d\u56fd\u5730\u56fe\u7684\u65b9\u6cd5\u662f\u591a\u79cd\u591a\u6837\u7684\u3002\u65e0\u8bba\u662f\u7b80\u5355\u7684\u9759\u6001\u5730\u56fe\uff0c\u8fd8\u662f\u590d\u6742\u7684\u4ea4\u4e92\u5f0f\u5730\u56fe\uff0c\u90fd\u53ef\u4ee5\u901a\u8fc7\u4e0d\u540c\u7684\u5e93\u6765\u5b9e\u73b0\u3002Pyecharts\u5e93\u7531\u4e8e\u5176\u7b80\u5355\u6613\u7528\u548c\u529f\u80fd\u4e30\u5bcc\uff0c\u6210\u4e3a\u4e86\u7ed8\u5236\u4e2d\u56fd\u5730\u56fe\u7684\u9996\u9009\u5de5\u5177\u3002\u6b64\u5916\uff0cGeopandas\u548cFolium\u4e5f\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u529f\u80fd\uff0c\u53ef\u4ee5\u6ee1\u8db3\u66f4\u9ad8\u7ea7\u7684\u9700\u6c42\u3002<\/p>\n<\/p>\n
\u5728\u672a\u6765\uff0c\u6211\u4eec\u53ef\u4ee5\u8fdb\u4e00\u6b65\u63a2\u7d22\u66f4\u591a\u7684\u5730\u56fe\u7ed8\u5236\u6280\u5de7\u548c\u5e94\u7528\u573a\u666f\u3002\u4f8b\u5982\uff0c\u7ed3\u5408\u6570\u636e\u5206\u6790\u548c\u673a\u5668\u5b66\u4e60<\/a>\u6280\u672f\uff0c\u5728\u5730\u56fe\u4e0a\u5c55\u793a\u66f4\u4e3a\u590d\u6742\u7684\u6570\u636e\u5173\u7cfb\uff1b\u6216\u8005\u7ed3\u5408Web\u6280\u672f\uff0c\u5f00\u53d1\u66f4\u52a0\u4ea4\u4e92\u548c\u52a8\u6001\u7684\u5730\u56fe\u5e94\u7528\u3002\u8fd9\u4e9b\u90fd\u662f\u503c\u5f97\u6211\u4eec\u8fdb\u4e00\u6b65\u7814\u7a76\u548c\u5c1d\u8bd5\u7684\u65b9\u5411\u3002<\/p>\n<\/p>\n
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