由一个滑块控制的两个子图

2024-05-19 • 问答

在这里存在一个问题，即试图绘制两个均由一个滑块控制的子图。这应该很简单，但是我看不到让它正常工作。我一直在关注：https://plot.ly/python/sliders/ 和许多其他帖子，但似乎仍然有问题。

我在两个子图的每个图上都使用了两个df，并尝试通过滑动条中的步长更改来更改哪一行可见。

这就是我要去的地方。第一次使用plotly，因此任何帮助和建议将不胜感激。

谢谢。

import plotly
import plotly.graph_objects as go
import numpy as np
import pandas as pd
import plotly.express as px
from plotly.subplots import make_subplots
import chart_studio.plotly as py


df = pd.DataFrame({'A':[100,120,100,105,110],'B':[130,'C':[110,110,140,115,120],'D':[140,160,130],'E':[150,130,150]})
df2 = pd.DataFrame({'A':[140,150,'B':[150,'C':[120,'D':[170,125,150],'E':[140,180,140]})


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

# Add traces,one for each slider step
for step in range(len(df.index)):
    fig.append_trace(
        go.Scatter(
            visible=False,line=dict(color="#00CED1",width=2),name="Time = " + str(step),x=df.columns[0:],y=df.loc[step]),row=1,col=1)

#for step in range(len(df2.index)): Tried this does not work

    fig.append_trace(
        go.Scatter(
            visible=False,line=dict(color="red",x=df2.columns[0:],y=df2.loc[step]),row=2,col=1)


fig.data[1].visible = True


# Create and add slider
steps = []
for i in range(len(df.index)):
    step = dict(method="restyle",args=["visible",[False] * len(fig.data)],)
    step["args"][1][i] = True
    #step["args"][1][i+1] = True # This shows them both but still not correct (different row numbers)

    steps.append(step)

sliders = [dict(
    active=0,currentvalue={"prefix": "Time:  "},pad={"t": 50},steps=steps
)]

fig.update_yaxes(title_text="Temperature",range=[-160,260],nticks=30,col=1)
fig.update_yaxes(title_text="Pressure",range=[-169,col=1)
fig.update_layout(sliders=sliders,title="Time Series - Interactive",template ="plotly_white")

fig.update_layout(width=800,height=600,)
fig.show()

import plotly import plotly.graph_objects as go import numpy as np import pandas as pd import plotly.express as px from plotly.subplots import make_subplots import chart_studio.plotly as py import random df = pd.DataFrame({'A':[random.randint(1,200),random.randint(1,200)],'B':[random.randint(1,'C':[random.randint(1,'D':[random.randint(1,'E':[random.randint(1,'F':[random.randint(1,'G':[random.randint(1,'H':[random.randint(1,'I':[random.randint(1,'J':[random.randint(1,'K':[random.randint(1,'L':[random.randint(1,'M':[random.randint(1,'N':[random.randint(1,'O':[random.randint(1,'P':[random.randint(1,200)] }) df2 = pd.DataFrame({'A':[random.randint(1,200)] }) fig = make_subplots(rows=2,cols=1,shared_xaxes=True,vertical_spacing = 0.25) # Add traces,one for each slider step for step in range(len(df.index)): fig.append_trace( go.Scatter( visible=False,line=dict(color="#00CED1",width=2),name="Time = " + str(step),x=df.columns[0:],y=df.loc[step]),row=1,col=1) #for step in range(len(df2.index)):# Tried this does not work fig.append_trace( go.Scatter( visible=False,line=dict(color="red",x=df2.columns[0:],y=df2.loc[step]),row=2,col=1) # Create and add slider steps = [] for i in range(0,len(fig.data),2): step = dict( method="restyle",args=["visible",[False] * len(fig.data)],) step["args"][1][i:i+2] = [True,True] steps.append(step) sliders = [dict( active=0,currentvalue={"prefix": "Time: "},pad={"t": 50},steps=steps )] fig.update_yaxes(title_text="Temperature",range=[-160,260],nticks=30,col=1) fig.update_yaxes(title_text="Pressure",range=[-169,col=1) fig.update_layout(sliders=sliders,title="Time Series - Interactive",template ="plotly_white") plotly.offline.plot(fig,filename='name.html') fig.show()

由一个滑块控制的两个子图

laoying123654 回答：由一个滑块控制的两个子图

大家都在问