1
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。
基于plotly
# 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()
2
# 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()
3
基于pyecharts
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()
4
以上通过plotly、pyecharts快速绘漏斗图。
共勉~