Plotly - 当悬停在共享 x 轴的两个子图上时如何显示 y 值

Question

I have two subplots sharing x-axis, but it only shows the y-value of one subplot not both. I want the hover-display to show y values from both subplots.

Here is what is showing right now:

But I want it to show y values from the bottom chart as well even if I am hovering my mouse on the top chart and vice versa.

Here's my code:

title = 'Price over time'
err = 'Price'


fig = make_subplots(rows=2, cols=1,
                    vertical_spacing = 0.05,
                    shared_xaxes=True,
                    subplot_titles=(title,""))

# A
fig.add_trace(go.Scatter(x= A_error['CloseDate'], 
                         y = A_error[err], 
                         line_color = 'green',
                         marker_color = 'green',
                         mode = 'lines+markers',
                         showlegend = True,
                         name = "A",
                         stackgroup = 'one'),
              row = 1,
              col = 1,
              secondary_y = False)

# B
fig.add_trace(go.Scatter(x= B_error['CloseDate'], 
                         y = B_error[err], 
                         line_color = 'blue',
                         mode = 'lines+markers',
                         showlegend = True,
                         name = "B",
                         stackgroup = 'one'),
              row = 2,
              col = 1,
              secondary_y = False)

fig.update_yaxes(tickprefix = '$')
fig.add_hline(y=0, line_width=3, line_dash="dash", line_color="black")

fig.update_layout(#height=600, width=1400, 
                  hovermode = "x unified",
                  legend_traceorder="normal")

Answer 1

At this time, I do not believe a Unified hovermode across the subplot is offered. I got the basis for this from here . There seems to be a workaround , although it will affect some features. In your example the horizontal line does not appear on both graphs. Since you did not present your data, I applied your code using the data in the reference. In conclusion, you need to decide whether to adopt the horizontal line or the hover line across the subplots.

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

df = px.data.stocks()

title = 'Price over time'
err = 'Price'

fig = make_subplots(rows=2, cols=1,
                    vertical_spacing = 0.05,
                    shared_xaxes=True,
                    subplot_titles=(title,""))

# A
fig.add_trace(go.Scatter(x = df['date'], 
                         y = df['GOOG'], 
                         line_color = 'green',
                         marker_color = 'green',
                         mode = 'lines+markers',
                         showlegend = True,
                         name = "A",
                         stackgroup = 'one'),
              row = 1,
              col = 1,
              secondary_y = False)

# B
fig.add_trace(go.Scatter(x= df['date'], 
                         y = df['AMZN'], 
                         line_color = 'blue',
                         mode = 'lines+markers',
                         showlegend = True,
                         name = "B",
                         stackgroup = 'one'),
              row = 2,
              col = 1,
              secondary_y = False)

fig.update_yaxes(tickprefix = '$')
fig.update_xaxes(type='date', range=[df['date'].min(),df['date'].max()])

fig.add_hline(y=0, line_width=3, line_dash="dash", line_color="black")

fig.update_layout(#height=600, width=1400, 
                  hovermode = "x unified",
                  legend_traceorder="normal")
fig.update_traces(xaxis='x2')

fig.show()

Answer 2

import plotly.graph_objects as go

from plotly.subplots import make_subplots

def plotly_stl( results ):

fig = make_subplots( rows=3+len(results.seasonal.columns), cols=1,
                     shared_xaxes=False,
                   )

precision = 2
customdataName=[results.observed.name.capitalize(),
                results.trend.name.capitalize(),
                results.seasonal.columns[0].capitalize(),
                results.seasonal.columns[1].capitalize(),
                results.resid.name.capitalize(),
               ]
customdata=np.stack((results.observed,
                     results.trend,
                     results.seasonal[results.seasonal.columns[0]],
                     results.seasonal[results.seasonal.columns[1]],
                     results.resid,
                     ), 
                     axis=-1
                   )
#print(customdata)
fig.append_trace( go.Scatter( name=customdataName[0], 
                      mode ='lines', 
                      x=results.observed.index,
                      y=results.observed,
                      line=dict(shape = 'linear', #color = 'blue', #'rgb(100, 10, 100)', 
                                width = 2, #dash = 'dash'
                               ),
                      customdata=customdata,                                 
                      hovertemplate='<br>'.join(['Datetime: %{x:%Y-%m-%d:%h}',
                          '<b>'+customdataName[0]+'</b><b>'+f": %{{y:.{precision}f}}"+'</b>',
                          customdataName[1] + ": %{customdata[1]:.2f}",
                          customdataName[2] + ": %{customdata[2]:.2f}",
                          customdataName[3] + ": %{customdata[3]:.2f}",
                          customdataName[4] + ": %{customdata[4]:.2f}",
                          '<extra></extra>',
                                                ]), 
                      showlegend=False,
                      ),
                  row=1, col=1,
                )
fig['layout']['yaxis']['title']= customdataName[0]

fig.append_trace( go.Scatter( name=customdataName[1], 
                      mode ='lines', 
                      x=results.trend.index,
                      y=results.trend,
                      line=dict(shape = 'linear', #color = 'blue', #'rgb(100, 10, 100)', 
                                width = 2, #dash = 'dash'
                               ),
                      customdata=customdata,                                 
                      hovertemplate='<br>'.join(['Datetime: %{x:%Y-%m-%d:%h}',
                          '<b>'+customdataName[1]+'</b><b>'+f": %{{y:.{precision}f}}"+'</b>',
                          customdataName[0] + ": %{customdata[0]:.2f}",
                          customdataName[2] + ": %{customdata[2]:.2f}",
                          customdataName[3] + ": %{customdata[3]:.2f}",
                          customdataName[4] + ": %{customdata[4]:.2f}",
                          '<extra></extra>'
                                                ]),
                      showlegend=False,
                      ),
                  row=2, col=1,
                )
fig['layout']['yaxis2']['title']= customdataName[1]

for i in range( len(results.seasonal.columns) ):
    another=3-i
    fig.append_trace( go.Scatter( name=customdataName[2+i], 
                      mode ='lines', 
                      x=results.seasonal.index,
                      y=results.seasonal[results.seasonal.columns[i]],
                      line=dict(shape = 'linear', #color = 'blue', #'rgb(100, 10, 100)', 
                                width = 2, #dash = 'dash'
                               ),
                      customdata=customdata,           
                      hovertemplate='<br>'.join(['Datetime: %{x:%Y-%m-%d:%h}',
                          '<b>'+customdataName[2+i]+'</b><b>'+f": %{{y:.{precision}f}}"+'</b>',
                          customdataName[0] + ": %{customdata[0]:.2f}",
                          customdataName[1] + ": %{customdata[1]:.2f}",
                          customdataName[another] + f": %{{customdata[{another}]:.{precision}f}}",
                          customdataName[4] + ": %{customdata[4]:.2f}",
                          '<extra></extra>',
                                                ]), 
                      showlegend=False,
                      ),
                  row=3+i, col=1,
                )
    fig['layout']['yaxis'+str(3+i)]['title']= customdataName[2+i]
    
fig.append_trace( go.Scatter( name=customdataName[4], 
                      mode ='lines', 
                      x=results.resid.index,
                      y=results.resid,
                      line=dict(shape = 'linear', #color = 'blue', #'rgb(100, 10, 100)', 
                                width = 2, #dash = 'dash'
                               ),   
                      customdata=customdata,                                 
                      hovertemplate='<br>'.join(['Datetime: %{x:%Y-%m-%d:%h}',
                          '<b>'+customdataName[4]+'</b><b>'+f": %{{y:.{precision}f}}"+'</b>',
                          customdataName[0] + ": %{customdata[0]:.2f}",
                          customdataName[1] + ": %{customdata[1]:.2f}",
                          customdataName[2] + ": %{customdata[2]:.2f}",
                          customdataName[3] + ": %{customdata[3]:.2f}",
                           '<extra></extra>',
                          ]),                            
                      showlegend=False,
                      ),
                  row=3+len(results.seasonal.columns), col=1,
                )
fig['layout']['yaxis'+str(3+len(results.seasonal.columns))]['title']= customdataName[-1]
fig['layout']['xaxis'+str(3+len(results.seasonal.columns))]['title']= 'Datetime'


fig.update_layout(height=800, width=1000,
                  legend_tracegroupgap = 330,
                  hovermode='x unified',#####
                  legend_traceorder="normal",#####
                  #plot_bgcolor='rgba(0,0,0,0)',
                 )
fig.update_traces( xaxis='x{}'.format(str(3+len(results.seasonal.columns))) )#####
                                      
fig.show()

plotly_stl( results_mstl )

you can see the complete code ：https://blog.csdn.net/Linli522362242/article/details/128760927 enter image description here another solution code: https://blog.csdn.net/Linli522362242/article/details/128760927 enter image description here