Echart：
ECharts，一個純 Javascript 的圖表庫，可以流暢的運作在 PC 和移動裝置上，相容目前絕大部分浏覽器（IE8/9/10/11，Chrome，Firefox，Safari等），底層依賴輕量級的 Canvas 類庫 ZRender，提供直覺，生動，可互動，可高度個性化定制的資料可視化圖表。
ECharts 提供了正常的折線圖，柱狀圖，散點圖，餅圖，K線圖，用于統計的盒形圖，用于地理資料可視化的地圖，熱力圖，線圖，用于關系資料可視化的關系圖，treemap，多元資料可視化的平行坐标，還有用于 BI 的漏鬥圖，儀表盤，并且支援圖與圖之間的混搭。
在本次内容中，使用Pyechats來實作新冠肺炎疫情地圖的繪制。
第一步：擷取實時的新冠肺炎資料
import requests
from lxml import etree
import re
import json
class Get_data():
#擷取資料
def get_data(self):
response = requests.get("https://voice.baidu.com/act/newpneumonia/newpneumonia/")
with open(\'html.txt\', \'w\') as file:
file.write(response.text)
#提取更新時間
def get_time(self):
with open(\'html.txt\',\'r\') as file:
text = file.read()
#正規表達式，傳回的是清單，提取最新更新時間
time = re.findall(\'"mapLastUpdatedTime":"(.*?)"\', text)[0]
return time
#解析資料
def parse_data(self):
with open(\'html.txt\', \'r\') as file:
text = file.read()
html = etree.HTML(text)
result = html.xpath(\'//script[@type="application/json"]/text()\')
result = result[0]
result = json.loads(result)
#轉換成字元串
result = json.dumps(result[\'component\'][0][\'caseList\'])
with open(\'data.json\', \'w\') as file:
file.write(result)
print(\'資料已寫入json檔案。。。\')
第二步：繪制地圖
pyecharts的地圖官方源碼：
from pyecharts import options as opts
from pyecharts.charts import Map
from pyecharts.faker import Faker
c = (
Map()
.add("商家A", [list(z) for z in zip(Faker.provinces, Faker.values())], "china")
.set_global_opts(
title_opts=opts.TitleOpts(title="Map-VisualMap（連續型）"),
visualmap_opts=opts.VisualMapOpts(max_=200),
)
)
效果：
第二步：資料可視化地圖
from pyecharts import options as opts
from pyecharts.charts import Map
from pyecharts.faker import Faker
import os
class Draw_map():
#判斷是否存在存放地圖的檔案夾，沒有的話建立檔案夾
def __init__(self):
if not os.path.exists(\'./map/china\'):
os.makedirs(\'./map/china\')
#将RGB轉換為繪制地圖需要的十六進制的表達形式
def get_colour(self,a,b,c):
result = \'#\' + \'\'.join(map((lambda x: "%02x" % x), (a,b,c)))
return result.upper()
#繪制每個城市的地圖
def to_map_city(self,area, variate,province,update_time):
#顯示辨別欄的顔色分層表示
pieces = [
{"max": 99999999, "min": 10000, "label": "≥10000", "color": self.get_colour(102, 2, 8)},
{"max": 9999, "min": 1000, "label": "1000-9999", "color": self.get_colour(140, 13, 13)},
{"max": 999, "min": 500, "label": "500-999", "color": self.get_colour(204, 41, 41)},
{"max": 499, "min": 100, "label": "100-499", "color": self.get_colour(255, 123, 105)},
{"max": 99, "min": 50, "label": "50-99", "color": self.get_colour(255, 170, 133)},
{"max": 49, "min": 10, "label": "10-49", "color": self.get_colour(255,202,179)},
{"max": 9, "min": 1, "label": "1-9", "color": self.get_colour(255,228,217)},
{"max": 0, "min": 0, "label": "0", "color": self.get_colour(255,255,255)},
]
#繪制地圖
c = (
# 設定地圖大小
Map(init_opts=opts.InitOpts(width = \'1000px\', height=\'880px\'))
.add("累計确診人數", [list(z) for z in zip(area, variate)], province, is_map_symbol_show=False)
# 設定全局變量 is_piecewise設定資料是否連續，split_number設定為分段數，pices可自定義資料分段
# is_show設定是否顯示圖例
.set_global_opts(
title_opts=opts.TitleOpts(title="%s地區疫情地圖分布"%(province), subtitle = \'截止%s %s省疫情分布情況\'%(update_time,province), pos_left = "center", pos_top = "10px"),
legend_opts=opts.LegendOpts(is_show = False),
visualmap_opts=opts.VisualMapOpts(max_=200,is_piecewise=True,
pieces=pieces,
),
)
.render("./map/china/{}疫情地圖.html".format(province))
)
# 繪制全國的地圖
def to_map_china(self, area,variate,update_time):
pieces = [{"max": 999999, "min": 1001, "label": ">10000", "color": "#8A0808"},
{"max": 9999, "min": 1000, "label": "1000-9999", "color": "#B40404"},
{"max": 999, "min": 100, "label": "100-999", "color": "#DF0101"},
{"max": 99, "min": 10, "label": "10-99", "color": "#F78181"},
{"max": 9, "min": 1, "label": "1-9", "color": "#F5A9A9"},
{"max": 0, "min": 0, "label": "0", "color": "#FFFFFF"},
]
c = (
# 設定地圖大小
Map(init_opts=opts.InitOpts(width=\'1000px\', height=\'880px\'))
.add("累計确診人數", [list(z) for z in zip(area, variate)], "china", is_map_symbol_show=False)
.set_global_opts(
title_opts=opts.TitleOpts(title="中國疫情地圖分布", subtitle=\'截止%s 中國疫情分布情況\'%(update_time), pos_left="center", pos_top="10px"),
legend_opts=opts.LegendOpts(is_show=False),
visualmap_opts=opts.VisualMapOpts(max_=200, is_piecewise=True,
pieces=pieces,
),
)
.render("./map/中國疫情地圖.html")
)
第三步：
使用資料來繪制地圖：
import json
import map_draw
import data_get
with open(\'data.json\',\'r\') as file:
data = file.read()
data = json.loads(data)
map = map_draw.Draw_map()
datas = data_get.Get_data()
datas.get_data()
update_time = datas.get_time()
datas.parse_data()
#中國疫情地圖資料
def china_map():
area = []
confirmed = []
for each in data:
area.append(each[\'area\'])
confirmed.append(each[\'confirmed\'])
map.to_map_china(area,confirmed,update_time)
#省份疫情地圖資料
def province_map():
for each in data:
city = []
confirmeds = []
province = each[\'area\']
for each_city in each[\'subList\']:
city.append(each_city[\'city\']+"市")
confirmeds.append(each_city[\'confirmed\'])
map.to_map_city(city,confirmeds,province,update_time)
if province == \'上海\' or \'北京\' or \'天津\' or \'重慶\' or \'香港\':
for each_city in each[\'subList\']:
city.append(each_city[\'city\'])
confirmeds.append(each_city[\'confirmed\'])
map.to_map_city(city,confirmeds,province,update_time)
效果：
全國：
内蒙古自治區：
本次内容參考自：
https://pyecharts.org/#/zh-cn/intro
http://gallery.pyecharts.org/#/Map/README
https://www.jianshu.com/p/3e71d73694fa
https://www.jianshu.com/p/d2474e9bce6e
https://www.bilibili.com/medialist/play/ml317727151