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Choropleth 等值线图, U8 K) X* P: J w0 U/ K o
import pandas as pd #读取数据" @6 T0 N( x$ q2 C
from folium import Map,Choropleth,CircleMarker #用到的包
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#包含省的中国地图json
# [% t, P8 N6 {8 A, M china_geo = fhttps://geo.datav.aliyun.com/areas_v2/bound/100000_full.json5 e6 d7 y" d f' a5 D% l3 H* K r
#读取用到的面积数据
. L0 Q3 M: ~1 l+ k* Q* @ datad = pd.read_csv(Desktop/square.csv,index_col=index)
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m=Map(tiles=Stamen Toner) #地图风格, C- n8 u0 M& G4 _0 L0 j! Z
j# h. Z& N2 `; N: _4 i Choropleth(china_geo, #选择json
0 }' R' G. h: t9 @5 b data = datad, #数据" v7 M6 y& M& i1 R% O7 X
columns = [province,square], #列，第一个为key，第二个为value
% M+ f6 X5 e) ? key_on = feature.properties.name,#匹配到json
; e% v+ Y) A+ x' Y fill_color = RdPu, #颜色
! R+ `- v) g5 P$ U# e9 M2 x+ d fill_opacity = 0.8, #填充透明度
1 j& K6 ?9 l1 f2 v line_opactity = 1, #线透明度! G G* v$ O- O" k& @: p0 u
line_weight = 1, #线宽
5 A& X$ Q! ^3 Q5 U k$ } legend_name = 面积 #图例
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).add_to(m)
& i% v( k% n9 V- }7 J CircleMarker(location = [39.907518, 116.397514], #坐标点
* S. i- s5 h- i$ V1 O, |( U) c8 Q4 Q radius = 10, #半径
0 X, C2 f1 V! O0 u# ^5 t% n: [. q fill = True, #填充- |( U7 D4 t0 K) Z6 O
popup = This is beijing, #弹窗; e2 [) h ^8 Q
weight = 1 #circlemarker线宽 ) r o5 q1 V8 w/ T, Y
).add_to(m)
6 E" d% S0 x& T$ _1 v8 j m.fit_bounds(m.get_bounds())1 Z# f% ~4 [$ D# h. {: l
m
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数据地址： square.rar - 蓝奏云
6 {# N7 Z' F; D1 Q* o 两个重要的网站 ) K! ^1 t0 y+ U/ f( S
手动绘制geojson 1 D; Q& d, y7 V b7 X9 z
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目前更新的geojson : n" e4 a1 G; s
: i# Z/ n3 _+ q' X8 h" d' f+ m4 v geojson格式
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"type": "FeatureCollection",
# s( A6 y7 G6 r; A6 Q8 y, j "features": [
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) G: u/ P: I8 H" A "properties": {"name": "Alabama"},
3 g) d# Z6 C$ C2 l' c' [# j3 h "id": "AL",
* \2 k& q; | g3 `8 P, n2 ~5 b: i* v8 X "type": "Feature",* e9 S1 e V( P a0 `7 Q, O+ o; l
"geometry": {
" W6 ]7 [# I, D1 N& Z m& o. ] "type": "Polygon",4 e$ S: P/ [$ [0 g8 Y
"coordinates": [[[-87.359296, 35.00118], ...]]7 T# I! u' F( d/ S7 ^- f' B4 |
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{
/ _& P& o$ S9 z( B6 R% r" { "properties": {"name": "Alaska"},
. E: D9 ]6 X6 [4 I* H "id": "AK",' E5 J. ]& i& N
"type": "Feature"," X6 K6 D) T1 a: J4 F
"geometry": {1 v2 y2 v/ O2 I; \; M* h J# Y
"type": "MultiPolygon",
+ h; @, ^, R8 z% K# F9 N "coordinates": [[[[-131.602021, 55.117982], ... ]]]4 h3 \( W; m+ t& L: ]
}
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}
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. X1 z% e% r* x2 q' @1 B 读取本地的json文件 ; ^' W0 c/ W5 M& c, ]' l3 A
f = open(zhengzhou.json): u/ B+ R( y# y, `* G2 P' A% l
t = json.load(f)4 F# s C6 j& H
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读取网络json
5 b+ x& ?; x& j) o; I url = (
! R% O K9 M4 L) O8 B6 ^- g4 f "https://raw.githubusercontent.com/python-visualization/folium/master/examples/data"
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us_states = f"{url}/us-states.json"' M: p* X, f# z+ |" I1 i
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geo_json_data = json.loads(requests.get(us_states).text)
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