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

基于plotly

python 复制代码

# 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 复制代码

# 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()

基于pyecharts

python 复制代码

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～