一个滑块控制R中的多个子图

我想使用一个滑块来控制用plotly创建的多个子图。我在Python中找到了以下两个答案:

示例(第二个链接):

import plotly.graph_objs as go
from plotly.tools import make_subplots

fig = make_subplots(1,2)

fig.add_scatter(y=[1,3,2],row=1,col=1,visible=True)
fig.add_scatter(y=[3,1,1.5],visible='legendonly')
fig.add_scatter(y=[2,2,1],visible='legendonly')
fig.add_scatter(y=[1,col=2,visible=True)
fig.add_scatter(y=[1.5,2.5],visible='legendonly')
fig.add_scatter(y=[2.5,1.2,2.9],visible='legendonly')

steps = []
for i in range(3):
    step = dict(
        method = 'restyle',args = ['visible',['legendonly'] * len(fig.data)],)
    step['args'][1][i] = True
    step['args'][1][i+3] = True
    steps.append(step)

sliders = [dict(
    steps = steps,)]

fig.layout.sliders = sliders

go.FigureWidget(fig)

但是我如何在R中实现呢?

lunatic999 回答:一个滑块控制R中的多个子图

实际上与python中的过程完全相同。这是从this派生的示例:

library(plotly)

df <- data.frame(x = 1:5,y = 1:5) 

# create steps for slider
steps <- list(
  list(args = list("marker.color","red"),label = "Red",method = "restyle",value = "1"
  ),list(args = list("marker.color","green"),label = "Green",value = "2"
  ),"blue"),label = "Blue",value = "3"
  )
)

p1 <- p2 <- df %>%
  plot_ly(x = ~x,y = ~y,mode = "markers",marker = list(size = 20,color = 'green'),type = "scatter")

p <- subplot(p1,p2) %>%
  layout(title = "Basic Slider",sliders = list(
           list(
             active = 1,currentvalue = list(prefix = "Color: "),pad = list(t = 60),steps = steps))) 

p

Result

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