Python画出好看的地图基于folium

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Choropleth 等值线图

import pandas as pd #读取数据 0 b8 _2 }) [) ^+ a from folium import Map,Choropleth,CircleMarker #用到的包 1 G, i. r, s) \% P% q

#包含省的中国地图json 9 R: r' _3 m7 n" n china_geo = fhttps://geo.datav.aliyun.com/areas_v2/bound/100000_full.json : g9 ^1 v9 r. k+ d6 i0 T3 Q #读取用到的面积数据 datad = pd.read_csv(Desktop/square.csv,index_col=index)

m=Map(tiles=Stamen Toner) #地图风格 3 H4 H% ~/ d8 e2 ^1 ^, d Choropleth(china_geo, #选择json 0 Z6 ?0 |0 t6 Z data = datad, #数据 columns = [province,square], #列，第一个为key，第二个为value key_on = feature.properties.name,#匹配到json $ \) ~5 W- p6 u `3 u2 W; U% A0 a- T* R fill_color = RdPu, #颜色 6 g3 S! Q- c2 k: N! G8 _ fill_opacity = 0.8, #填充透明度 8 r. Q2 Y, t$ l line_opactity = 1, #线透明度 line_weight = 1, #线宽 0 K9 x/ C W- ^* B3 y legend_name = 面积 #图例 * k4 s; B+ t/ C) `! j: j% H ).add_to(m) & R! o# N' X0 L/ Y# D CircleMarker(location = [39.907518, 116.397514], #坐标点 radius = 10, #半径 fill = True, #填充 popup = This is beijing, #弹窗 6 _) l* q) `2 u6 v# C; W weight = 1 #circlemarker线宽 ).add_to(m) m.fit_bounds(m.get_bounds()) m

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数据地址： square.rar - 蓝奏云

两个重要的网站

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手动绘制geojson

geojson.io​geojson.io/

目前更新的geojson

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地图选择器​datav.aliyun.com/tools/atlas/index.html

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geojson格式

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{ "type": "FeatureCollection", "features": [ { " Y5 W1 N4 l& k% T. }" l* } "properties": {"name": "Alabama"}, "id": "AL", 9 t0 q5 P) q J8 ]& K5 X2 F, x2 t3 { "type": "Feature", 1 U0 \9 A) j3 n7 G4 W1 ^: y "geometry": { / j( l" J( E( V2 P% b5 R "type": "Polygon", 1 g/ a$ l2 J1 J3 q2 j9 q6 B+ h; ^ "coordinates": [[[-87.359296, 35.00118], ...]] } }, & A& C5 ^. x% z0 X, w; ]7 F { "properties": {"name": "Alaska"}, ' n* _0 E" {* }9 x& F/ q h "id": "AK", "type": "Feature", 3 K. P1 |& j0 w, q- i "geometry": { - D% S/ n, N9 V6 x" y B "type": "MultiPolygon", ! Z7 l0 ?4 A# x9 i. f "coordinates": [[[[-131.602021, 55.117982], ... ]]] 5 X' ]0 \8 i9 B3 K v } }, / E, e1 E3 q7 y& \' { ... ] } 3 L b9 u9 ~" E# z6 x

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读取本地的json文件

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f = open(zhengzhou.json) t = json.load(f) ; l) r/ Y* I; d8 Q0 n; R" N

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读取网络json

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url = ( "https://raw.githubusercontent.com/python-visualization/folium/master/examples/data" ) us_states = f"{url}/us-states.json" ! q) d0 g: P- Y3 _3 K( z4 ~9 l1 j geo_json_data = json.loads(requests.get(us_states).text) + {5 U B4 X/ s

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