Plotly：如何为每个子图添加下拉菜单？

Question

我需要为每个图表创建两个带有下拉菜单和标题的子图。 （并排比较）。另外，我想要一个共享的 y 轴。

就目前而言，我只有一个下拉菜单可以更改两个图表。

代码如下：（注意 df 由 2 列和 datetimeindex 组成）。

    import plotly.offline as py
    import plotly.graph_objs as go
    from plotly.offline import init_notebook_mode, iplot, plot
    from plotly import tools
    
    labels = ["Vol", "R"]
    
    
    fig = tools.make_subplots(rows=1, cols=2)
    
    trace1 = go.Scatter(x=df.index,
                             y=df['Stock1'].rolling(window=12).std(),
                             mode='lines'
                            )
    trace2 = go.Scatter(x=df.index,
                             y=df['Stock1'],
                             mode='lines'
                            )
    
    fig.append_trace(trace1, 1, 1)
    fig.append_trace(trace2, 1, 1)
    
    trace1 = go.Scatter(x=df.index,
                             y=df['Stock2'].rolling(window=12).std(),
                             mode='lines'
                            )
    trace2 = go.Scatter(x=df.index,
                             y=df['Stock2'],
                             mode='lines'
                            )   
    fig.append_trace(trace1, 1, 2)
    fig.append_trace(trace2, 1, 2)
    
    
    # Create buttons for drop down menu
    buttons = []
    for i, label in enumerate(labels):
        visibility = [i==j for j in range(len(labels))]
        button = dict(
                     label =  label,
                     method = 'update',
                     args = [{'visible': visibility},
                         {'title': label}])
        buttons.append(button)
    
    updatemenus = list([
        dict(active=-1,
             x=-0.15,
             buttons=buttons
        )
    ])
    
    fig['layout']['title'] = 'Title'
    fig['layout']['showlegend'] = False
    fig['layout']['updatemenus'] = updatemenus
    
    iplot(fig, filename='dropdown')

Answer 1

根据 Plotly 论坛中的empet's helpful answer，重要的是要知道visible 键的长度等于fig.data 中的跟踪总数。

在您的情况下，您有四个跟踪，分别对应于 Stock 1 (Vol)、Stock 1 (R)、Stock 2 (Vol) 和 Stock 2 (R)，这是您添加这些跟踪的顺序。因此我们可以创建 4 个按钮来切换每个跟踪的可见性功能，并将它们作为列表传递给 updatemenus 字典。

import numpy as np
import pandas as pd

import plotly.offline as py
import plotly.graph_objs as go
from plotly.offline import init_notebook_mode, iplot, plot
from plotly import tools

## recreate some random data
np.random.seed(42)
df = pd.DataFrame(data=np.random.randint(0,100,(365,2)), columns=['Stock1','Stock2'], index=pd.date_range(start='1/1/2019', end='12/31/2019'))

labels = ["Vol", "R"]


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

trace1 = go.Scatter(x=df.index,
                         y=df['Stock1'].rolling(window=12).std(),
                         mode='lines'
                        )
trace2 = go.Scatter(x=df.index,
                         y=df['Stock1'],
                         mode='lines'
                        )

fig.append_trace(trace1, 1, 1)
fig.append_trace(trace2, 1, 1)

trace1 = go.Scatter(x=df.index,
                         y=df['Stock2'].rolling(window=12).std(),
                         mode='lines'
                        )
trace2 = go.Scatter(x=df.index,
                         y=df['Stock2'],
                         mode='lines'
                        )   
fig.append_trace(trace1, 1, 2)
fig.append_trace(trace2, 1, 2)


## visible key for traces are in the order you append them

button1 = dict(method='update', 
               args=[{"visible": [True, False, False, False] }], 
               label="Stock 1, Vol" )
button2 = dict(method='update', 
               args=[{"visible": [False, True, False, False] }], 
               label="Stock 1, R" )   
button3 = dict(method='update', 
               args=[{"visible": [False, False, True, False] }], 
               label="Stock 2, Vol" )
button4 = dict(method='update', 
               args=[{"visible": [False, False, False, True] }], 
               label="Stock 2, R" )   

updatemenus = list([
    dict(active=-1,
         x=-0.15,
         buttons=[button1, button2, button3, button4]
    )
])

fig['layout']['title'] = 'Title'
fig['layout']['showlegend'] = False
fig['layout']['updatemenus'] = updatemenus

iplot(fig, filename='dropdown')