【武汉加油⛽️】基于Pyecharts的疫情数据可视化～
前言
疫情终将过去，静待春暖花开～
本文使用的数据源来自https://lab.isaaclin.cn/nCoV/zh；
运行本项目需要将pyecharts版本更新至v1.6.2，!pip install pyecharts == 1.6.2；
⚡️更好的阅读体验访问我的Kesci Lab：点我跳转；
相关教程：
- ✨Pyecharts教程：超详细Pyecharts 1.x教程，让你的图表动起来～
获取数据
- ☀️接口地址：https://lab.isaaclin.cn/nCoV/api/area
- 请求方式：GET
- ❄️主要字段：
| 变量名 | 注释 |
|---|---|
| currentConfirmedCount | 现存确诊人数 |
| confirmedCount | 累计确诊人数 |
| suspectedCount | 疑似感染人数 |
| curedCount | 治愈人数 |
| deadCount | 死亡人数 |
代码 & 效果
导库 & 数据请求
import requests
import pyecharts
from pyecharts.charts import *
from pyecharts import options as opts
from pyecharts.commons.utils import JsCode
from datetime import date
# 数据来源于 Github DXY-COVID-19-Data， 原作者为 Isaac Lin
url = 'https://lab.isaaclin.cn/nCoV/api/area'
data = requests.get(url).json()
# 生成更新日期
update_date = date.today()
全球疫情地图
oversea_confirm = []
for item in data['results']:
if item['countryEnglishName']:
oversea_confirm.append((item['countryEnglishName'].replace('United States of America', 'United States')
.replace('United Kiongdom', 'United Kingdom'),
item['confirmedCount']))
_map = (
Map(init_opts=opts.InitOpts(theme='dark'))
.add("累计确诊人数", oversea_confirm, "world",is_map_symbol_show=False)
.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
.set_global_opts(
title_opts=opts.TitleOpts(title="新型冠状病毒全球疫情地图",
subtitle="更新日期：{}".format(update_date)),
legend_opts=opts.LegendOpts(is_show=False),
visualmap_opts=opts.VisualMapOpts(is_show=True, max_=50,
is_piecewise=False,
range_color=['#FFFFE0', '#FFFFE0', '#FFA07A', '#CD5C5C', '#8B0000']),
graphic_opts=[
opts.GraphicGroup(
graphic_item=opts.GraphicItem(
bounding="raw",
right=150,
bottom=50,
z=100,
),
children=[
opts.GraphicRect(
graphic_item=opts.GraphicItem(
left="center", top="center", z=100
),
graphic_shape_opts=opts.GraphicShapeOpts(
width=200, height=50
),
graphic_basicstyle_opts=opts.GraphicBasicStyleOpts(
fill="rgba(0,0,0,0.3)"
),
),
opts.GraphicText(
graphic_item=opts.GraphicItem(
left="center", top="center", z=100
),
graphic_textstyle_opts=opts.GraphicTextStyleOpts(
text=JsCode("['钻石号邮轮', '累计确诊人数：{}人'].join('\\n')"
.format(dict(oversea_confirm)['Diamond Princess Cruise Ship'])),
font="bold 16px Microsoft YaHei",
graphic_basicstyle_opts=opts.GraphicBasicStyleOpts(
fill="#fff"
),
),
),
],
)
],
)
)
_map.render_notebook()
全国疫情地图
province_data = []
for item in data['results']:
if item['countryName'] == '中国':
province_data.append((item['provinceShortName'], item['confirmedCount']))
_map = (
Map(init_opts=opts.InitOpts(theme='dark'))
.add("累计确诊人数", province_data, "china",is_map_symbol_show=False)
.set_series_opts(label_opts=opts.LabelOpts(is_show=True))
.set_global_opts(
title_opts=opts.TitleOpts(title="新型冠状病毒全国疫情地图",
subtitle="更新日期：{}".format(update_date)),
legend_opts=opts.LegendOpts(is_show=False),
visualmap_opts=opts.VisualMapOpts(is_show=True, max_=1000,
is_piecewise=False,
range_color=['#FFFFE0', '#FFA07A', '#CD5C5C', '#8B0000'])
)
)
_map.render_notebook()
湖北省内确诊情况
for item in data['results']:
if item['provinceShortName'] == '湖北':
hubei_data = item['cities']
bar = (
Bar(init_opts=opts.InitOpts(theme='dark'))
.add_xaxis([x['cityName'] for x in hubei_data])
.add_yaxis("累计确诊人数", [x['confirmedCount'] for x in hubei_data])
.add_yaxis("当前确诊人数", [x['currentConfirmedCount'] for x in hubei_data])
.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
.set_global_opts(
title_opts=opts.TitleOpts(title="新型冠状病毒湖北省内确诊情况",
subtitle="更新日期：{}".format(update_date)),
xaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(rotate=45)),
legend_opts=opts.LegendOpts(is_show=True),
graphic_opts=[
opts.GraphicGroup(
graphic_item=opts.GraphicItem(
bounding="raw",
right=300,
top=120
),
children=[
opts.GraphicRect(
graphic_item=opts.GraphicItem(
left="center", top="center"
),
graphic_shape_opts=opts.GraphicShapeOpts(
width=200, height=60
),
graphic_basicstyle_opts=opts.GraphicBasicStyleOpts(
fill="rgba(0,0,0,0.3)"
),
),
opts.GraphicText(
graphic_item=opts.GraphicItem(
left="center", top="center", z=1
),
graphic_textstyle_opts=opts.GraphicTextStyleOpts(
text=JsCode("['当前确诊人数：', '','累计确诊人数-死亡人数-治愈人数'].join('\\n')"),
font="bold 12px Microsoft YaHei",
graphic_basicstyle_opts=opts.GraphicBasicStyleOpts(
fill="#fff"
),
),
),
],
)
],
)
)
bar.render_notebook()
全国确诊热力地图
cities_data = []
for item in data['results']:
if item['countryName'] == '中国':
cities_data.extend((item['cities']))
geo = (
Geo(init_opts=opts.InitOpts(theme='dark'))
.add_schema(maptype="china", zoom=3, center=[114.31,30.52])
.add("累计确诊人数",
[(i['cityName'], i['currentConfirmedCount']) for i in cities_data
if i['cityName'] in pyecharts.datasets.COORDINATES.keys()],
type_='heatmap',
symbol_size=3,
progressive=50)
.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
.set_global_opts(
title_opts=opts.TitleOpts(title="新型冠状病毒全国疫情热力图",
subtitle="更新日期：{}".format(update_date),
pos_left='right'),
legend_opts=opts.LegendOpts(is_show=False),
visualmap_opts=opts.VisualMapOpts(is_show=True,
is_piecewise=False,
range_color=['blue', 'green', 'yellow', 'yellow', 'red'])
)
)
geo.render_notebook()
- Coding不易，欢迎点赞支持～