! p& q4 k ^, {( ? Choropleth 等值线图+ O# K5 B$ X5 S- |0 N( E
import pandas as pd #读取数据3 ]* r0 d$ l z; w' \# z$ v2 [
from folium import Map,Choropleth,CircleMarker #用到的包
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2 ]& `2 T8 w1 {9 x. W, N2 n #包含省的中国地图json9 J# r, W g, E, S6 l7 L
china_geo = fhttps://geo.datav.aliyun.com/areas_v2/bound/100000_full.json
* K/ E' ~6 Z$ i8 O #读取用到的面积数据
) t x) y* T: [3 e1 B 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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# Z7 F: Y% T: f Choropleth(china_geo, #选择json q; H( @( z+ r; Y6 H0 C9 L
data = datad, #数据2 D# ?0 o! t5 F3 h; `1 k M
columns = [province,square], #列，第一个为key，第二个为value
5 l4 g! b H% x: H& p key_on = feature.properties.name,#匹配到json
( x8 a4 a- X. n fill_color = RdPu, #颜色
# U( r. J5 r) V; V0 g `) e( z fill_opacity = 0.8, #填充透明度* G, `& J- A( I' L" k
line_opactity = 1, #线透明度
: a# O9 U# H& E( @' I1 D line_weight = 1, #线宽8 M, Z8 `8 H( G9 h
legend_name = 面积 #图例
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).add_to(m)# z0 Y2 q/ H1 O: O
CircleMarker(location = [39.907518, 116.397514], #坐标点9 I i7 A8 E( k* c, ~
radius = 10, #半径! C$ b- Y( j8 h7 k0 n" F
fill = True, #填充
$ m4 j' k6 f% N3 L' c" l+ a- D p popup = This is beijing, #弹窗% H$ R% c6 C0 t4 g+ E; m% w
weight = 1 #circlemarker线宽
J! v' ?) f/ x/ D2 g/ T! T3 W ).add_to(m)
k- \* D4 \. A' S9 j% O m.fit_bounds(m.get_bounds())
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数据地址： square.rar - 蓝奏云
* B- N/ A3 [; e. F# ^; z8 L 两个重要的网站 & ]! e6 G! L3 o
手动绘制geojson " B0 y. p: {: a0 _: F
6 \' M8 [9 g- C( f. B! a4 o 目前更新的geojson
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geojson格式 1 d1 l% N$ p* [; U+ A
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"type": "FeatureCollection",
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{
4 G: i$ k g# H, Q9 t; }) O "properties": {"name": "Alabama"},' v, k: \# ]6 T4 Y
"id": "AL",$ P. G& O4 s/ C- A+ R6 ^& h/ e
"type": "Feature", Z4 m) Z9 w0 P9 r( x$ F
"geometry": {& `6 Y8 K0 b; P ?2 n
"type": "Polygon",- e* { M) t5 I7 y) D. ?
"coordinates": [[[-87.359296, 35.00118], ...]]. D5 z8 V7 f. }* C
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},
6 i7 R6 h6 c+ ~. A4 z {
) r+ Q6 i& `1 Y "properties": {"name": "Alaska"},
% s1 }* F3 N4 s% ~, ?* G3 L "id": "AK",' P6 a6 O# z. O; {, y! z
"type": "Feature",
4 r- C, W) c5 N* B: B2 } "geometry": {
5 E$ P9 E. `9 B "type": "MultiPolygon",
. L" V5 ^5 ?& ]8 d5 w3 H "coordinates": [[[[-131.602021, 55.117982], ... ]]]
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},
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]
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' ^2 l/ y K: u$ `+ c& E 读取本地的json文件 ' K" H/ \( E2 t+ T& Q/ e
f = open(zhengzhou.json)% M) f# j2 T$ P$ f
t = json.load(f)6 A1 }1 n8 g. l/ V! J
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读取网络json 4 p F3 M) M( _' A" g, H- g1 O
url = (3 N$ I H; V _' \, { Q
"https://raw.githubusercontent.com/python-visualization/folium/master/examples/data"
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! P- a# y0 ^ p/ M: n3 M# r9 J us_states = f"{url}/us-states.json"
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geo_json_data = json.loads(requests.get(us_states).text)
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