是否可以使用 plotly.express 创建子图？

Question

I would like to create a subplot with 2 plot generated with the function plotly.express.line , is it possible? Given the 2 plot:

fig1 =px.line(df, x=df.index, y='average')
fig1.show()

fig2 = px.line(df, x=df.index, y='Volume')
fig2.show()

I would like to generate an unique plot formed by 2 subplot (in the example fig1 and fig2)

Answer 1

No, not directly (as DerekO has concisely described). But since plotly express can do some pretty amazing stuff with fairly complicated datasets, I see no reason why you should not stumple upon cases where you would like to use elements of a plotly express figure as a source for a subplot. And that is very possible.

Below is an example where I've built to plotly express figures using px.line on the px.data.stocks() dataset. Then I go on to extract some elements of interest using add_trace and go.Scatter in a For Loop to build a subplot setup. You could certainly argue that you could just as easily do this directly on the data source. But then again, as initially stated, plotly express can be an excellent data handler in itself.

Subplot using plotly express figures as source:

Complete code:

import plotly.graph_objects as go
import plotly.express as px
import pandas as pd

from plotly.subplots import make_subplots

df = px.data.stocks().set_index('date')

fig1 = px.line(df[['GOOG', 'AAPL']])
fig2 = px.line(df[['AMZN', 'MSFT']])

fig = make_subplots(rows=2, cols=1)

for d in fig1.data:
    fig.add_trace((go.Scatter(x=d['x'], y=d['y'], name = d['name'])), row=1, col=1)
        
for d in fig2.data:
    fig.add_trace((go.Scatter(x=d['x'], y=d['y'],  name = d['name'])), row=2, col=1)
    
fig.show()

Answer 2

From the documentation, Plotly expressdoes not support arbitrary subplot capabilities . You can instead use graph objects and traces (note that go.Scatter is equivalent):

import pandas as pd

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

## create some random data
df = pd.DataFrame(
    data={'average':[1,2,3], 'Volume':[7,3,6]}, 
    index=['a','b','c']
)

fig = make_subplots(rows=1, cols=2)

fig.add_trace(
    go.Scatter(x=df.index, y=df.average, name='average'),
    row=1, col=1
)

fig.add_trace(
    go.Scatter(x=df.index, y=df.Volume, name='Volume'),
    row=1, col=2
)

fig.show()

Answer 3

There is no need to use graph_objects module if you have just already generated px figures for making subplots. Here is the full code.

import plotly.express as px
import pandas as pd
from plotly.subplots import make_subplots

df = px.data.stocks().set_index('date')

fig1 = px.line(df[['GOOG', 'AAPL']])
fig2 = px.line(df[['AMZN', 'MSFT']])

fig = make_subplots(rows=2, cols=1)

fig.add_trace(fig1['data'][0], row=1, col=1)
fig.add_trace(fig1['data'][1], row=1, col=1)
fig.add_trace(fig2['data'][0], row=2, col=1)
fig.add_trace(fig2['data'][1], row=2, col=1)
    
fig.show()

If there are more than two variables in each plot, one can use for loop also to add the traces using fig.add_trace method.