import pandas as pd #導(dǎo)入數(shù)據(jù)分析模塊
from pyecharts.charts import Geo #導(dǎo)入地理信息處理模塊
from pyecharts import options as opts ?#配置
from pyecharts.render import make_snapshot #快照
from snapshot_selenium import snapshot?
from pyecharts.globals import ChartType, SymbolType #全局配置

data=pd.read_excel("D:\數(shù)有引力\魔都商圈\辦公項(xiàng)目.xlsx") ?#讀取數(shù)據(jù)
geo_sight_coord={data['項(xiàng)目名稱'][i].strip(): [data['經(jīng)度'][i], data['緯度'][i]] for i in range(len(data))} #構(gòu)造位置字典數(shù)據(jù)
data_pair=[(data['項(xiàng)目名稱'][i].strip(), data['日租金'][i]) for i in range(len(data))] #構(gòu)造項(xiàng)目租金數(shù)據(jù)

g=Geo() #地理初始化
g.add_schema(maptype="上海") #限定上海市范圍
for key, value in geo_sight_coord.items(): #對(duì)地理點(diǎn)循環(huán)
? ? g.add_coordinate(key, value[0], value[1]) #追加點(diǎn)位置

g.add("", data_pair, symbol_size=2) #追加項(xiàng)目名稱和租金
g.set_series_opts(label_opts=opts.LabelOpts(is_show=False), type='scatter') ?#星散點(diǎn)圖scatter

pieces = [
? ? ? ? {'max': 3, 'label': '<3', 'color': '#00B2EE'},
? ? ? ? {'min': 3, 'max': 6, '3~6': 'love', 'color': '#71C671'},
? ? ? ? {'min': 6, 'max': 10, '6~10': 'always', 'color': '#CD4F39'},
? ? ? ? {'min': 10, ?'label': '10+', 'color': '#FF0000'} # 有下限無上限
? ? ? ? ?]

g.set_global_opts(visualmap_opts=opts.VisualMapOpts(is_piecewise=True, pieces=pieces), title_opts=opts.TitleOpts(title="辦公項(xiàng)目分布")) #辦公項(xiàng)目分布圖

make_snapshot(snapshot, g.render("上海市辦公項(xiàng)目.html"), "上海市辦公項(xiàng)目.png") #渲染成html格式和png格式

geo_sight_coord={data['項(xiàng)目名稱'][i].strip(): [data['經(jīng)度'][i], data['緯度'][i]] for i in range(len(data))}?

{"新橋大廈": 121.472534, 31.246122}

data_pair=[(data['項(xiàng)目名稱'][i].strip(), data['日租金'][i]) for i in range(len(data))]

("新橋大廈": 4.3 )