7 I' g% S' b/ ^4 J) {; d Choropleth 等值线图
! Z2 g% U" |9 l( G9 @. D import pandas as pd #读取数据: {9 R% ~7 [+ L; Y5 A
from folium import Map,Choropleth,CircleMarker #用到的包 {3 g% k# b6 n! p$ A) a) e* u
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#包含省的中国地图json; n+ @ L+ F4 }& s( J
china_geo = fhttps://geo.datav.aliyun.com/areas_v2/bound/100000_full.json
$ Y1 S# e5 J; G #读取用到的面积数据
* V! C `4 v" P datad = pd.read_csv(Desktop/square.csv,index_col=index)
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) H7 K9 W: [/ Z5 T! } m=Map(tiles=Stamen Toner) #地图风格
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4 ?5 L! c4 N; u- h/ r3 N: y: z Choropleth(china_geo, #选择json
* M* M5 t% e6 m data = datad, #数据$ U3 J9 A% P9 j! E; ?0 m( b4 l
columns = [province,square], #列，第一个为key，第二个为value
- q. X5 a' X- R, J7 a- i* O4 A; P key_on = feature.properties.name,#匹配到json/ B- b5 K! y! n7 U2 k
fill_color = RdPu, #颜色
5 k1 l6 h& e- X( d6 o" Y' ^' U8 u w fill_opacity = 0.8, #填充透明度0 ?2 _* B; v# |1 d) H
line_opactity = 1, #线透明度
6 \7 ]. x+ V$ R, v) D3 e9 f5 Z4 s line_weight = 1, #线宽, z& Z' R- l: H
legend_name = 面积 #图例4 |" @- ^' I6 b1 q$ L/ z
" A6 ?- I: C9 U) F* q/ x ).add_to(m)0 ]1 f( o- f# E/ M0 J H
CircleMarker(location = [39.907518, 116.397514], #坐标点
5 `1 i: R) P* a. h radius = 10, #半径6 M% g' g; ?4 X6 n, z+ Z5 D' h6 u
fill = True, #填充# R. ^$ E/ b5 h
popup = This is beijing, #弹窗
2 Q* W6 H: B# G3 `% H weight = 1 #circlemarker线宽
8 ~- K% C' q0 j) u1 s0 M ^ ).add_to(m)2 i4 P+ }2 ~2 R3 z# A& H: ^9 J
m.fit_bounds(m.get_bounds())
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0 \# U' {* _! K 数据地址： square.rar - 蓝奏云
/ J3 i0 {) ]& B4 L/ O g* {/ |2 z9 T 两个重要的网站
8 n: d6 S, `5 B) I% t$ b 手动绘制geojson
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! w7 d4 {' F) F% @ 目前更新的geojson * j$ D% }" h/ @5 R
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geojson格式
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"type": "FeatureCollection",
" \8 c, K, a; ^" _5 h( _ "features": [5 T5 {% @+ s# ^" z+ {
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"properties": {"name": "Alabama"},: o3 h! V% a+ a; @ t
"id": "AL",
% @/ x# |! P+ F1 M+ V "type": "Feature",
0 i- |- z, L( ? r& v* d* d "geometry": {
/ W. i; Z" F! C "type": "Polygon",
4 Y% M( I6 X8 b. u* j7 k$ Q "coordinates": [[[-87.359296, 35.00118], ...]]
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},% ?9 F4 y# a6 i# i' G; O
{
+ t) U2 Z4 B, }3 s "properties": {"name": "Alaska"},
7 E, i* F8 w! x: H1 f1 [ "id": "AK",# l( t0 i A. ~# Y
"type": "Feature",
5 Q( A6 J5 m* n8 a: |! X "geometry": {$ i8 ^/ K9 m0 v/ D+ _
"type": "MultiPolygon",) m2 f$ t& p n
"coordinates": [[[[-131.602021, 55.117982], ... ]]]
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...
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读取本地的json文件 , \$ O) `, x# q6 g2 l t4 ~! G0 q
f = open(zhengzhou.json)
* F5 T3 p/ ]& o* F; A/ y t = json.load(f)
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读取网络json ' ^, K( X! W+ @' L
url = (0 s" O4 y! X$ m: B
"https://raw.githubusercontent.com/python-visualization/folium/master/examples/data"" ?/ t/ ?3 k% [! y' U a
)
% f0 O7 e- J4 |" P* V us_states = f"{url}/us-states.json"5 u7 L( y" |; r5 S1 w2 ^8 M; v3 q3 W6 q
& o- i7 t2 h" t. |* m4 [. H1 ?4 ` geo_json_data = json.loads(requests.get(us_states).text)
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