8 `- q8 H8 N$ k( o8 o1 K( o Choropleth 等值线图
9 {0 s- d% x: d! ?+ z import pandas as pd #读取数据
p% G( ~0 V9 w; \, r9 j# H from folium import Map,Choropleth,CircleMarker #用到的包
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4 g7 D. \ M) {9 O* z #包含省的中国地图json) x3 V8 U+ Y* v/ {4 n( U& V2 i" B. B
china_geo = fhttps://geo.datav.aliyun.com/areas_v2/bound/100000_full.json" ^; f% ~$ O c2 N u1 G" ?; f- {* l
#读取用到的面积数据& D! v! o5 D; K' e* K/ B U
datad = pd.read_csv(Desktop/square.csv,index_col=index)
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m=Map(tiles=Stamen Toner) #地图风格
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Choropleth(china_geo, #选择json
% X) o1 H* _ D data = datad, #数据6 _ v3 }- v- H8 D" @
columns = [province,square], #列，第一个为key，第二个为value
( b: s# h" u. k E+ i key_on = feature.properties.name,#匹配到json
% ?2 f9 I6 q9 |0 }. k E8 t fill_color = RdPu, #颜色1 m0 P4 M' q* {& N$ B. ~2 H
fill_opacity = 0.8, #填充透明度
2 t, U$ x c7 R4 p. M line_opactity = 1, #线透明度, X7 ^. q8 O) ~
line_weight = 1, #线宽; a# A9 S1 W$ q# L- _
legend_name = 面积 #图例
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).add_to(m)
* L8 a; X( W" j CircleMarker(location = [39.907518, 116.397514], #坐标点
1 H8 s2 q& I. p0 w5 S1 a4 s radius = 10, #半径# z& j5 n* [4 k* R3 ]& R
fill = True, #填充
2 c0 E! ?" O. E popup = This is beijing, #弹窗" e; }8 f6 w# f: X! W) x
weight = 1 #circlemarker线宽
# Z1 p7 C7 ?/ v7 ?: k6 T ).add_to(m)/ J, B6 m8 N5 E3 w; Y) ^0 O
m.fit_bounds(m.get_bounds())& O) y+ p( L6 u1 W( m0 C! \3 N
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! s$ z$ o( V4 U6 I 数据地址： square.rar - 蓝奏云 ' @6 m" n8 G/ Y. c) P6 ~& w
两个重要的网站
: E1 f* ], A2 `! k 手动绘制geojson * j' d5 g+ k7 z/ ]
6 C3 Y* p& B3 k& K3 t ` 目前更新的geojson
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geojson格式
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"type": "FeatureCollection",
, T' e8 ?3 K8 M6 K3 o) Q m( M "features": [, J+ e. Y, B R& P- s4 q
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"properties": {"name": "Alabama"},
: e: r6 M$ X9 u9 a" l1 j "id": "AL",: q7 g% _" B2 O* _4 s
"type": "Feature",
& {& G3 ]* K/ s- s) i# ? "geometry": {
2 {3 t- ~. f3 c; r0 j% X4 k z "type": "Polygon",
$ `$ g9 O: I3 p% \. p B "coordinates": [[[-87.359296, 35.00118], ...]]
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"properties": {"name": "Alaska"},9 e/ d! X1 q- f% ~
"id": "AK",
. D- r5 J5 n, V# I "type": "Feature",
+ k( V; c0 W* A# V "geometry": {
7 N, W$ P. I& s; N/ M; ]( o# Y "type": "MultiPolygon",9 ?$ @ v# g% v
"coordinates": [[[[-131.602021, 55.117982], ... ]]]
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5 h1 B1 h5 q& C8 X( h5 } 读取本地的json文件 ; l: F% C( `0 {! E) x/ c9 f
f = open(zhengzhou.json)
: p5 E8 r0 K6 f/ m$ P& T t = json.load(f)8 {) R1 p; @- ^- n# j% k0 F4 d
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读取网络json 4 r; @+ Z9 x" Q! `/ c
url = (7 C) Q, x6 p# y/ H9 r7 A
"https://raw.githubusercontent.com/python-visualization/folium/master/examples/data"
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& Z2 { C3 S! |" b+ ` us_states = f"{url}/us-states.json"
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geo_json_data = json.loads(requests.get(us_states).text)0 I1 q$ T8 p: ]5 B) X2 \
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