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Choropleth 等值线图
0 X1 @* z8 d/ Y! i; ~7 G# n U- A7 r import pandas as pd #读取数据/ o" \: S- m6 j
from folium import Map,Choropleth,CircleMarker #用到的包: S( Z) J7 C3 @0 [+ F) ?
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#包含省的中国地图json! i) X5 }+ h4 \1 m8 x# T' J
china_geo = fhttps://geo.datav.aliyun.com/areas_v2/bound/100000_full.json
5 { @5 }( T2 V1 ?# Z5 q+ u( \6 d4 L #读取用到的面积数据9 Y, ~( q# S% M+ b7 X
datad = pd.read_csv(Desktop/square.csv,index_col=index)# q2 D- ?" G1 w$ T$ T7 S
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7 i) u, y8 B P2 B/ q# m5 r* x m=Map(tiles=Stamen Toner) #地图风格
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Choropleth(china_geo, #选择json9 X* g# l3 N' D3 u# K- r3 N& c5 f: H
data = datad, #数据7 ?0 l8 R" k% @+ Z
columns = [province,square], #列，第一个为key，第二个为value+ z, [5 D/ e+ _% J6 r3 U* Z
key_on = feature.properties.name,#匹配到json
) Q$ f7 q6 @% k0 S6 f fill_color = RdPu, #颜色
( c8 `- D5 N0 C( F* I- W fill_opacity = 0.8, #填充透明度9 F0 l$ N+ H! V) x0 V G" l1 Q9 f
line_opactity = 1, #线透明度
# c) _9 G% j5 G; k" E, C line_weight = 1, #线宽/ ^+ q) {. ?# H
legend_name = 面积 #图例
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/ H' s9 T: N9 N' w2 c: C0 ] ).add_to(m), B b; C/ |6 x3 B
CircleMarker(location = [39.907518, 116.397514], #坐标点( ? V# n9 J G. ~8 ^% B, o' P
radius = 10, #半径
- w0 n9 _! U# ~$ T/ |" Z fill = True, #填充
0 z4 w' a6 ]0 o3 D# M! O popup = This is beijing, #弹窗- X+ k U0 c& e. ?3 K7 {
weight = 1 #circlemarker线宽 + A' Z! f. N1 m h# Z \$ `
).add_to(m)
1 Y6 W; e N; N m.fit_bounds(m.get_bounds())7 {/ R% Y' k( ^7 y
m
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数据地址： square.rar - 蓝奏云
/ ?, e: R& ?8 d2 v' L8 M/ x 两个重要的网站
) r! D; m: Q. }( W 手动绘制geojson ; u. k, F# f1 d
. H# w1 j: N# P. a, q/ h# u; ^2 p' l 目前更新的geojson ; D4 D, c/ s# t3 q2 O
" K2 ~. K2 d/ t/ y, J geojson格式 8 m$ A$ Q* Y4 j' N
{% A, p1 K8 a/ e. B( D
"type": "FeatureCollection",
3 ^! ^- H) j2 ]+ k% c "features": [
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"properties": {"name": "Alabama"},2 Z; L! u) |3 X1 @+ }% J9 W! x
"id": "AL",0 b* y* c1 T1 Q2 y. d& N. f8 O+ a1 I
"type": "Feature", @8 i' [+ z; Q7 f3 h
"geometry": {4 S ~' ~) q$ n: r P/ e
"type": "Polygon",
% K- I B) _& t: t$ G "coordinates": [[[-87.359296, 35.00118], ...]]
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"properties": {"name": "Alaska"},# m g7 F H. E; e/ j8 L; b
"id": "AK",$ X) R1 ^5 o; q$ Z" t
"type": "Feature",
0 u8 G: x* ^5 ? ?8 j "geometry": {
2 B) A# M: h& k: ]+ c- `. S: b, N "type": "MultiPolygon",
5 A; J6 u. D4 x; m8 q "coordinates": [[[[-131.602021, 55.117982], ... ]]]/ N/ `* Q; E6 ]
}
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]
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# @( y5 f4 [. |7 u! B 9 q* q( q. n& E" x/ d2 R
读取本地的json文件
. s K# D% [% ?; b' B- C f = open(zhengzhou.json)% P5 ]# v [# @" ~9 g/ y1 i
t = json.load(f)
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1 ^8 N& X. M l) B' k% L 读取网络json
' X: N) k- ~6 D url = (: u, S: j1 | B/ d/ ?; p
"https://raw.githubusercontent.com/python-visualization/folium/master/examples/data"
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us_states = f"{url}/us-states.json"
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, m1 N0 D2 z6 u$ X, z- d5 N: `7 k geo_json_data = json.loads(requests.get(us_states).text)
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