3 E3 \) Z! ^. k Choropleth 等值线图. z3 @; b4 k: ?% l) ?2 r* N
import pandas as pd #读取数据
/ x2 M- B, X0 L2 _9 g from folium import Map,Choropleth,CircleMarker #用到的包
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#包含省的中国地图json
6 K8 s/ V$ S! O% }1 E2 ^, g china_geo = fhttps://geo.datav.aliyun.com/areas_v2/bound/100000_full.json$ u% s$ v* B0 p% E9 \7 |
#读取用到的面积数据
; q- K: g) g. k4 s! I( O; K4 F datad = pd.read_csv(Desktop/square.csv,index_col=index)
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. U% J9 N5 l W0 Z0 L( g. t. k m=Map(tiles=Stamen Toner) #地图风格
& s7 p+ O. C7 |# u" O: h
/ Y% ]! l1 O' f Choropleth(china_geo, #选择json, I9 t; r) e3 t m! j
data = datad, #数据2 h3 f& p7 {& O. y1 H. {
columns = [province,square], #列，第一个为key，第二个为value
8 M; t+ b3 n1 G+ I7 @8 l# I key_on = feature.properties.name,#匹配到json
; Y( d" i! i6 \" d F fill_color = RdPu, #颜色
/ ^9 V, t/ ^3 K7 c8 Q( A fill_opacity = 0.8, #填充透明度$ F) U n( \% t: ~- m; S }
line_opactity = 1, #线透明度
# v8 y* [" {! h line_weight = 1, #线宽; f: I) I0 w1 h) _, j
legend_name = 面积 #图例
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# T" Z. ^$ n9 ], C, j ).add_to(m)
: U# R& h/ o' V0 e7 C5 y CircleMarker(location = [39.907518, 116.397514], #坐标点0 j6 m1 i* i" V. L. H
radius = 10, #半径
: L2 C( E: A$ a% K& I; B fill = True, #填充
. b6 {; N3 E8 ?' B# i! O popup = This is beijing, #弹窗
: E+ M4 L; c1 c D& M& w8 { weight = 1 #circlemarker线宽 . J4 `7 X. N: T' [
).add_to(m)
! ?/ N$ [: q* q+ j+ E m.fit_bounds(m.get_bounds())& t1 O* j+ t( I
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5 t0 k4 D% c3 s 数据地址： square.rar - 蓝奏云 6 A9 t6 S( @4 r8 `/ E$ A M
两个重要的网站 " _0 ~6 S" p# G" F5 H
手动绘制geojson ) t& b+ X+ ^: Z3 X$ }
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目前更新的geojson 3 Z& B f3 E i5 }9 A0 i0 _
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geojson格式
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4 H6 n' \5 ]! X) a* N6 J8 F# H "type": "FeatureCollection",7 |) q/ z0 O: k( K c1 N
"features": [
1 g6 y, i' Q) e8 H8 e. f {
4 @2 _- x$ B! B7 _6 r0 K "properties": {"name": "Alabama"},
; f9 f; e- I- m( y "id": "AL",
/ W% a3 a1 Y1 n$ ?5 ?2 n "type": "Feature",0 ?: Z, L" n7 i( w. p2 |4 @9 {) B
"geometry": {
$ b8 T( O3 G+ R1 k& ^; A. H "type": "Polygon",4 j8 I! @ v1 E* S# E; |1 Y3 V @
"coordinates": [[[-87.359296, 35.00118], ...]]. Q4 \0 z( c3 t5 V& Y8 ^
}; z6 N, e- K+ w
},
8 F8 e, H9 p- C% L$ j {
6 n1 c( E2 P# H+ v( B s" U/ ] "properties": {"name": "Alaska"},& z9 Y: }+ L6 r2 f I! O
"id": "AK",) q. a6 J. p" {
"type": "Feature",# t2 |/ T7 T' x2 b
"geometry": {
# L0 o/ A7 V4 k% f# Z7 ? "type": "MultiPolygon",. E; _! u: a( G8 c+ [* h1 \
"coordinates": [[[[-131.602021, 55.117982], ... ]]]$ k( M8 t" j7 \. B, d) d0 K K
}
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! T- w& e# i$ k" G ...
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读取本地的json文件 ! U; f& _5 O8 ~% C
f = open(zhengzhou.json)* |- e# j0 q" }+ _$ ]2 g
t = json.load(f)
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读取网络json
8 N2 b' o8 K* H7 z4 y, J& e url = ( @( f( X% @# E2 A: n
"https://raw.githubusercontent.com/python-visualization/folium/master/examples/data"
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) N ^8 ~; j* q us_states = f"{url}/us-states.json"
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: @9 N: b' m6 O* e# ^" |7 p$ L+ u0 c geo_json_data = json.loads(requests.get(us_states).text)0 `- A) k4 A6 X5 R
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