python_0">流程图（四）利用python绘制漏斗图

漏斗图（Funnel Chart）简介

漏斗图经常用于展示生产经营各环节的关键数值变化，以较高的头部开始，较低的底部结束，可视化呈现各环节的转化效率与变动大小。一般重点关注落差较大的环节。

快速绘制

1. 基于plotly

   python"># 基本漏斗图
   from plotly import graph_objects as go
   
   fig = go.Figure(go.Funnel(
       y = ["Website visit", "Downloads", "Potential customers", "Requested price", "invoice sent"],
       x = [39, 27.4, 20.6, 11, 2]))
   
   fig.show()
   

   

   python"># 分类漏斗图
   from plotly import graph_objects as go
   
   fig = go.Figure()
   
   fig.add_trace(go.Funnel(
       name = 'Montreal',
       y = ["Website visit", "Downloads", "Potential customers", "Requested price"],
       x = [120, 60, 30, 20],
       textinfo = "value+percent initial"))
   
   fig.add_trace(go.Funnel(
       name = 'Toronto',
       orientation = "h",
       y = ["Website visit", "Downloads", "Potential customers", "Requested price", "invoice sent"],
       x = [100, 60, 40, 30, 20],
       textposition = "inside",
       textinfo = "value+percent previous"))
   
   fig.add_trace(go.Funnel(
       name = 'Vancouver',
       orientation = "h",
       y = ["Website visit", "Downloads", "Potential customers", "Requested price", "invoice sent", "Finalized"],
       x = [90, 70, 50, 30, 10, 5],
       textposition = "outside",
       textinfo = "value+percent total"))
   
   fig.show()
   

   

2. 基于pyecharts

   python">from pyecharts import options as opts
   from pyecharts.charts import Funnel
   
   # 自定义数据
   x = [39, 27.4, 20.6, 11, 2]
   y = ["Website visit", "Downloads", "Potential customers", "Requested price", "invoice sent"]
   
   c = (
       Funnel()
       .add("商品", [list(z) for z in zip(y, x)])
       .set_global_opts(title_opts=opts.TitleOpts(title="基本漏斗图"))
   )
   
   c.render_notebook()
   

   

   总结

   以上通过plotly、pyecharts快速绘漏斗图。

   共勉～