可視化神器Plotly玩轉(zhuǎn)漏斗圖
本文中詳細(xì)介紹的是如何利用plotly來繪制漏斗圖
image
認(rèn)識(shí)漏斗圖
漏斗圖是銷售領(lǐng)域一種十分常用的圖表，主要是用來分析在各個(gè)階段的流失和轉(zhuǎn)化情況。比如在某個(gè)商城中，我們統(tǒng)計(jì)用戶在不同階段的人數(shù)來分析轉(zhuǎn)化率：
- 商城UV：商城每天的訪問人數(shù)
- 搜索人數(shù)：在商城有過搜索行為的用戶數(shù)
- 加購人數(shù)：有加購行為的用戶數(shù)
- 提交訂單：有多少用戶提交訂單
- 點(diǎn)擊支付：提交訂單之后有多少用戶點(diǎn)擊支付按鈕
- 支付成功：最終支付成功的用戶數(shù)
從搜索人數(shù)開始到支付成功，每個(gè)階段用戶都存在一定的流失，漏斗圖就能很好地將這種流失和轉(zhuǎn)化情況顯示出來。
除去柱狀圖、餅圖、折線圖，漏斗圖應(yīng)該是自己在工作畫的最為頻繁的一種圖表。下面我們通過模擬某個(gè)電商網(wǎng)站的用戶行為來繪制漏斗圖。
整體效果
導(dǎo)入庫
基于兩種方式實(shí)現(xiàn)：
- plotly_express ：px
- plotly.graph_objects：go
import pandas as pd
import numpy as np
# plotly兩個(gè)繪圖接口
import plotly_express as px
import plotly.graph_objects as go
基于px實(shí)現(xiàn)
基礎(chǔ)漏斗圖
模擬一份商城數(shù)據(jù)：
data1 = pd.DataFrame({
"number": [1200,900,700,400,180,100],
"stage": ["瀏覽網(wǎng)站","搜索","加購","提交訂單","點(diǎn)擊支付","支付成功"]}
)
data1
image
繪制一個(gè)基礎(chǔ)漏斗圖：
# 繪圖
fig = px.funnel(
data1, # 待繪圖數(shù)據(jù)
x="number", # x軸的數(shù)據(jù)
y="stage" # y軸的數(shù)據(jù)
)
fig.show()
image
我們還可以加上一個(gè)顏色參數(shù)color：
# 加上顏色參數(shù)color
fig = px.funnel(
data1,
x="number",
y="stage",
color="number" # 顏色參數(shù)
)
fig.show()
image
如果我們的顏色設(shè)置成number列，用數(shù)值意義似乎不準(zhǔn)確，更好地應(yīng)該是不同的階段表示，換成stage：
# 加上顏色參數(shù)color
fig = px.funnel(
data1,
x="number",
y="stage",
color="stage" # ?。?！改成stage
)
fig.show()
image
看生成的漏斗圖：最上面的是支付成功，通常我們希望的是數(shù)值最大的在最上面，于是我們將傳入的數(shù)據(jù)翻轉(zhuǎn)一下：
# 加上顏色參數(shù)color
fig = px.funnel(
data1[::-1], # ?。?！數(shù)據(jù)翻轉(zhuǎn)
x="number",
y="stage",
color="stage" # ！?。「某蓅tage
)
fig.show()
image
分組漏斗
分組漏斗表示的含義將不同組別的漏斗圖放在一個(gè)畫布中，比如：看今年3月和2020年3月的數(shù)據(jù)對(duì)比情況，這叫做同比
同比：相同時(shí)期的對(duì)比，比如：2021年3月和2020年3月
環(huán)比：相鄰時(shí)期的對(duì)比，比如：2021年3月和2021年2月
1、2020年3月份數(shù)據(jù)
image
2、2021年3月份數(shù)據(jù)
image
3、使用concat函數(shù)合并兩組數(shù)據(jù)
image
4、繪制漏斗圖
# 繪圖
fig = px.funnel(df3,x="number",y="stages",color="time")
fig.show()
image
繪制面積漏斗圖
還是使用最上面的數(shù)據(jù)：
image
fig = px.funnel_area(
data1,
names = "stage",
values = "number",
)
fig.show()
image
我們觀察到：面積漏斗圖默認(rèn)繪制的百分比，而普通漏斗圖是數(shù)值
基于go實(shí)現(xiàn)
繪制基礎(chǔ)漏斗圖
from plotly import graph_objects as go
fig = go.Figure(go.Funnel(
x=[1000,800,400,100],
y=["瀏覽網(wǎng)站","加購","點(diǎn)擊支付","支付成功"]
))
fig.show()
image
改變漏斗圖的顏色和邊框
from plotly import graph_objects as go
fig = go.Figure(go.Funnel(
x=[1000,800,400,100], # 數(shù)據(jù)
y=["瀏覽網(wǎng)站","加購","點(diǎn)擊支付","支付成功"], # 每個(gè)階段的名稱
textposition = "inside", # 文本位置：['inside', 'outside', 'auto', 'none']
textinfo = "value + percent initial", # 顯示文本信息 ['label', 'text', 'percent initial', 'percent previous', 'percent total', 'value'] 前面選項(xiàng)的任意組合
opacity = 0.65,
marker = {"color": ["deepskyblue", "lightsalmon", "tan", "silver"],
"line": {"width": [4, 2, 3, 1, 1],
"color": ["wheat", "wheat", "blue", "yellow"]}},
connector = {"line": {"color": "royalblue", "dash": "dot", "width": 3}})
)
fig.show()
image
我們需要主題textinfo參數(shù)的使用，它有3種使用方式：
- percent initial：相對(duì)于初始值
- percent previous：相對(duì)于前一個(gè)值
- percent total：相對(duì)于整體數(shù)值
上面這個(gè)漏斗圖使用的是percent initial（相對(duì)于初始值），百分比是這樣來的：
1000/1000 = 100%
800 / 1000 = 80%
400 / 1000 = 40%
100 / 1000 = 10%
如果是percent previous：
image
1000/1000 = 100%
800 / 1000 = 80%
400 / 800 = 50%
100 / 400 = 25%
如果是percent total：
image
我們看看第一個(gè)百分比是如何計(jì)算的：
image
分組漏斗
from plotly import graph_objects as go
stage = ["瀏覽網(wǎng)站","加購","點(diǎn)擊支付","支付成功"]
fig = go.Figure()
fig.add_trace(go.Funnel(
name = "2020年3月", # 圖形軌跡名稱
x = [1000,800,400,200], # 數(shù)據(jù)
y = stage, # 每個(gè)階段名稱
orientation = "h", # 方位
textposition = "inside", # 文本內(nèi)容的位置
textinfo = "value+percent previous" # 顯示文本內(nèi)容
))
fig.add_trace(go.Funnel(
name = "2021年2月", # 名稱和數(shù)據(jù)需要改變
x = [1200,900,500,240],
y = stage,
orientation = "h",
textposition = "inside",
textinfo = "value+percent total"
))
fig.add_trace(go.Funnel(
name = "2021年3月", # 名稱和數(shù)據(jù)需要改變
x = [1500,1000,450,300],
y = stage,
orientation = "h",
textposition = "inside",
textinfo = "label+percent initial"
))
fig.show()
image
在上面的圖中，既可以觀察到同比情況（2020年3月和2021年3月），也可以觀察到環(huán)比情況（2021年3月和2月）
面積漏斗
from plotly import graph_objects as go
fig = go.Figure(go.Funnelarea(
text = ["瀏覽網(wǎng)站","加購","點(diǎn)擊支付","支付成功"],
values = [5000, 2000, 800, 500],
))
fig.show()
image
設(shè)置面積漏斗的顏色和邊框
from plotly import graph_objects as go
fig = go.Figure(go.Funnelarea(
values = [3000, 2000, 800, 500],
text = ["瀏覽網(wǎng)站","加購","點(diǎn)擊支付","支付成功"],
marker = {"colors": ["deepskyblue", "lightsalmon", "teal", "silver"], # 顏色
"line": {"color": ["red", "blue", "wheat", "wheat"], # 邊框顏色和線條寬度
"width": [0, 1, 3, 5]}},
textfont = {"family": "Old Standard TT, serif", "size": 13, # 字體設(shè)置
"color": "black"},
opacity = 0.65)) # 透明度
fig.show()
image
多組面積漏斗
不同組別的漏斗圖我們也可以分開放，將它們放在一個(gè)大的畫布中：
from plotly import graph_objects as go
fig = go.Figure()
# 添加四組數(shù)據(jù)：第一季度到第四季度
fig.add_trace(go.Funnelarea(
scalegroup = "first", # 組別名稱
text = ["瀏覽網(wǎng)站","搜索","加購","提交訂單","點(diǎn)擊支付","支付成功"],
values = [500, 450, 340, 230, 220, 110], # 數(shù)據(jù)
textinfo = "value", # 顯示文本信息
title = {"position": "top center", # 標(biāo)題頂部居中
"text": "第一季度" # 標(biāo)題內(nèi)容
},
domain = {"x": [0, 0.5], # 圖形位置
"y": [0, 0.5]
}))
fig.add_trace(go.Funnelarea(
scalegroup = "first",
text = ["瀏覽網(wǎng)站","搜索","加購","提交訂單","點(diǎn)擊支付","支付成功"],
values = [600, 500, 400, 300, 200, 100],
textinfo = "value",
title = {"position": "top center",
"text": "第二季度"},
domain = {"x": [0, 0.5],
"y": [0.55, 1]}))
fig.add_trace(go.Funnelarea(
scalegroup = "second",
text = ["瀏覽網(wǎng)站","搜索","加購","提交訂單","點(diǎn)擊支付","支付成功"],
values = [510, 480, 440, 330, 220, 100],
textinfo = "value",
title = {"position": "top left",
"text": "第三季度"},
domain = {"x": [0.55, 1],
"y": [0, 0.5]}))
fig.add_trace(go.Funnelarea(
scalegroup = "second",
text = ["瀏覽網(wǎng)站","搜索","加購","提交訂單","點(diǎn)擊支付","支付成功"],
values = [360, 250, 240, 130, 120, 60],
textinfo = "value",
title = {"position": "top right",
"text": "第四季度"},
domain = {"x": [0.55, 1],
"y": [0.55, 1]}))
fig.update_layout(
margin = {"l": 100, "r": 100}, # 整個(gè)圖形到左右邊框的距離
shapes = [
{"x0": 0, "x1": 0.5, "y0": 0, "y1": 0.5}, # 添加4組位置
{"x0": 0, "x1": 0.5, "y0": 0.55, "y1": 1},
{"x0": 0.55, "x1": 1, "y0": 0, "y1": 0.5},
{"x0": 0.55, "x1": 1, "y0": 0.55, "y1": 1}
])
fig.show()
image
漏斗圖真的很好用，能夠觀察到數(shù)據(jù)在不同階段的轉(zhuǎn)化情況。畢竟領(lǐng)導(dǎo)每個(gè)月都要看一下??
