Plotly/Python 创建嵌套 x 轴条形图

Question

我想知道Plotly是否可以开始支持嵌套X/多个X轴？ 例如，如果使用标准“提示”数据，添加在（五美分图、JMP 或 Origin ）中实现的功能将是有益的。 即

import plotly.express as px
df = px.data.tips()
%load_ext autoreload
%autoreload 2
%matplotlib inline
import fivecentplots as fcp
import pandas as pd
import numpy as np
import os, sys, pdb
osjoin = os.path.join
db = pdb.set_trace
fcp.boxplot(df=df, y=‘tip’, groups=[‘time’, ‘sex’, ‘day’], legend=‘smoker’)

会生成： 嵌套 X 轴条形图

如果此功能已经存在 - 请添加评论。

Answer 1

这是可行的，但比您当前使用的方法需要更多步骤。使用plotly 实现这一目标的一种解决方案是创建具有多维轴的子图，一个用于午餐，一个用于晚餐，两者之间的空间为零，因此它看起来像一个单独的图。

import plotly.express as px
import pandas as pd
import numpy as np
from pandas.api.types import CategoricalDtype

df = px.data.tips()

#set order for days
days = CategoricalDtype(
    ['Thur', 'Fri', 'Sat', 'Sun'],
    ordered=True
    )

df['day'] = df['day'].astype(days)

#sort df
df.sort_values(['time', 'sex', 'day'], inplace=True)

#create framework
fig = make_subplots(rows=1,
            cols=2,
            shared_yaxes=True,
            horizontal_spacing=0,
            column_widths=[7/11, 4/11])

#create "Dinner" boxplots
fig.add_trace(go.Box(x=[df['sex'][df['time']=='Dinner'].tolist(), df['day'][df['time']=='Dinner'].tolist()],
             y=df['tip'][df['time']=='Dinner'],
             boxpoints=False,
             pointpos=0,
             line=dict(color='gray',
                   width=1),
             fillcolor='white',
             showlegend=False),
          row=1,
          col=1)
#add "Dinner" smokers
fig.add_trace(go.Scatter(x=[df['sex'][(df['time']=='Dinner') & (df['smoker']=='Yes')].tolist(), df['day'][(df['time']=='Dinner') & (df['smoker']=='Yes')].tolist()],
             y=df['tip'][(df['time']=='Dinner') & (df['smoker']=='Yes')],
             mode='markers',
             marker=dict(color='red',
                     symbol='circle-open',
                     size=10),
             name='Yes'
             ),
          row=1,
          col=1)

#add "Dinner" non-smokers
fig.add_trace(go.Scatter(x=[df['sex'][(df['time']=='Dinner') & (df['smoker']=='No')].tolist(), df['day'][(df['time']=='Dinner') & (df['smoker']=='No')].tolist()],
             y=df['tip'][(df['time']=='Dinner') & (df['smoker']=='No')],
             mode='markers',
             marker=dict(color='green',
                     symbol='cross-thin-open',
                     size=10),
             name='No'
             ),
          row=1,
          col=1)

df_mean = df[['sex', 'day', 'tip']][df['time']=='Dinner'].groupby(['sex', 'day']).mean().reset_index().dropna()

#add "Dinner" mean line
fig.add_trace(go.Scatter(x=[df_mean['sex'].tolist(), df_mean['day'].tolist()],
             y=df_mean['tip'].tolist(),
             showlegend=False,
             marker=dict(color='black')
             ),
          row=1,
          col=1)

#create "Lunch" boxplots
fig.add_trace(go.Box(x=[df['sex'][df['time']=='Lunch'].tolist(), df['day'][df['time']=='Lunch'].tolist()],
             y=df['tip'][df['time']=='Lunch'],
             boxpoints=False,
             pointpos=0,
             line=dict(color='gray',
                   width=1),
             fillcolor='white',
             showlegend=False),
          row=1,
          col=2)
#add "Lunch" smokers
fig.add_trace(go.Scatter(x=[df['sex'][(df['time']=='Lunch') & (df['smoker']=='Yes')].tolist(), df['day'][(df['time']=='Lunch') & (df['smoker']=='Yes')].tolist()],
             y=df['tip'][(df['time']=='Lunch') & (df['smoker']=='Yes')],
             mode='markers',
             marker=dict(color='red',
                     symbol='circle-open',
                     size=10),
             showlegend=False
             ),
          row=1,
          col=2)
#add "Lunch" non-smokers
fig.add_trace(go.Scatter(x=[df['sex'][(df['time']=='Lunch') & (df['smoker']=='No')].tolist(), df['day'][(df['time']=='Lunch') & (df['smoker']=='No')].tolist()],
             y=df['tip'][(df['time']=='Lunch') & (df['smoker']=='No')],
             mode='markers',
             marker=dict(color='green',
                     symbol='cross-thin-open',
                     size=10),
             showlegend=False
             ),
          row=1,
          col=2)

df_mean = df[['sex', 'day', 'tip']][df['time']=='Lunch'].groupby(['sex', 'day']).mean().reset_index().dropna()

#add "Lunch" mean line
fig.add_trace(go.Scatter(x=[df_mean['sex'].tolist(), df_mean['day'].tolist()],
             y=df_mean['tip'].tolist(),
             showlegend=False,
             marker=dict(color='black')
             ),
          row=1,
          col=2)

fig.update_xaxes(title='Dinner', col=1)
fig.update_xaxes(title='Lunch', col=2)
fig.update_yaxes(title='tip', col=1)
fig.update_layout(legend_title='Smoker')
fig.show()

性能更新：

使用循环使其更快以及其他细微更改

import pandas as pd
import plotly.graph_objects as go
from plotly.subplots import make_subplots

df = px.data.tips()

#set order for days
days = CategoricalDtype(['Thur', 'Fri', 'Sat', 'Sun'],
                        ordered=True)

df['day'] = df['day'].astype(days)

#sort df
df = df.sort_values(['time', 'sex', 'day']).reset_index(drop=True)

#create framework
fig = make_subplots(rows=1,
                    cols=2,
                    shared_yaxes=True,
                    horizontal_spacing=0,
                    column_widths=[4/11, 7/11])

col_order = {'Lunch':1, 'Dinner':2}
for t, col in col_order.items():
    cond = df['time']==t
    #add mean line
    df_mean = df[cond].groupby(['sex', 'day'], observed=True)['tip'].mean().reset_index()
    fig.add_trace(go.Scatter(x=[df_mean['sex'].tolist(), df_mean['day'].tolist()],
                             y=df_mean['tip'].tolist(),
                             showlegend=False,
                             marker=dict(color='black')
                             ),
                  row=1,
                  col=col)
    #add boxplots
    fig.add_trace(go.Box(x=[df[cond]['sex'].tolist(), df[cond]['day'].tolist()],
                         y=df[cond]['tip'],
                         boxpoints=False,
                         pointpos=0,
                         line=dict(color='gray',
                                   width=1),
                         fillcolor='white',
                         showlegend=False),
                  row=1,
                  col=col)
    #add smokers and non-smokers
    sl = True if col==1 else False #avoid duplicate legend entries
    smoker_dict = {'Yes':['red', 'circle-open'], 'No':['green', 'cross-thin-open']}
    for s, marker_vals in smoker_dict.items():
        color = marker_vals[0]
        symbol = marker_vals[1]
        cond = (df['time']==t) & (df['smoker']==s)
        fig.add_trace(go.Box(x=[df[cond]['sex'].tolist(), df[cond]['day'].tolist()],
                                 y=df[cond]['tip'],
                                 marker=dict(color=color,
                                             symbol=symbol,
                                             size=10),
                                 fillcolor='rgba(255,255,255,0)',
                                 line_color='rgba(255,255,255,0)',
                                 boxpoints='all',
                                 pointpos=0,
                                 name=s,
                                 showlegend=sl,
                                 ),
                      row=1,
                      col=col)
    fig.update_xaxes(title=t, col=col)
fig.update_yaxes(title='tip', col=1)
fig.update_xaxes(showline=True,
                 linecolor='black',
                 linewidth=1,
                 mirror=True)
fig.update_yaxes(showline=True,
                 linecolor='black',
                 linewidth=1,
                 mirror=True)
fig.update_yaxes(mirror=False, col=1) #center line was too thick
fig.update_traces(selector=dict(type='box'), jitter=1) #optional jitter
fig.update_layout(legend_title='Smoker',
                  plot_bgcolor='whitesmoke',
                  height=800, width=800)
fig.show()