python可视化大屏-疫情监控图（2）玫瑰图

结果截图

 

 数据准备

导入库

from pyecharts import options as opts
from pyecharts.charts import Geo
from pyecharts.globals import ChartType, SymbolType
from pyecharts.charts import Map
import pandas as pd
from pyecharts.charts import Bar
from pyecharts.globals import ThemeType

from pyecharts.charts import Map,Page

 

玫瑰图（使用软件：jupyter python3）

from pyecharts import options as opts
import pandas as pd
data_age = pd.read_excel(\'实时更新：新型冠状病毒肺炎疫情地图3.xlsx\')
# 年龄数据分箱
data_age[\'确诊区间\'] = pd.cut(data_age[\'确诊数\'],
                       bins = [0,60,120,200],
                       labels = [\'60以下\',\'60-120\',\'120以上\'])
# data_age
# 年龄区间数量统计
age_counts = data_age[\'确诊区间\'].value_counts()
# age_counts
# 数据结构重组
charts_data_age = [z for z in zip(age_counts.index,age_counts.tolist())]
from pyecharts.charts import Pie
from pyecharts.globals import ThemeType
pie = (
    Pie(init_opts=opts.InitOpts(width="600px", height="400px",theme=ThemeType.DARK)) # 设置背景的大小
    .add(
        series_name = "确诊数", # 必须项
        data_pair = charts_data_age,
        radius=["20%", "50%"], # 设置环的大小
        rosetype="radius", # 设置玫瑰图类型
        label_opts=opts.LabelOpts(formatter="{a}：{b}\n个数：{c}\n占比：{d}%"), # 设置标签内容格式
    )
    .set_global_opts(title_opts=opts.TitleOpts(title="确诊比例"))
)
pie.render_notebook()

运行结果

 

 

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