Switch displayed traces via plotly dropdown menu

Question

I am working with the R programming language. I am trying to replicate this tutorial over here for my own data: https://plotly.com/r/dropdowns/

I created some fake data and made 4 plots:

#load libraries 

library(plotly)
library(MASS)
library(dplyr)


# create data

x <- sample( LETTERS[1:4], 731, replace=TRUE, prob=c(0.25, 0.25, 0.25, 0.25) )
y <- rnorm(731,10,10)
z <- rnorm(731,5,5)
date= seq(as.Date("2014/1/1"), as.Date("2016/1/1"),by="day")
    
    df <- data.frame(x,y, z, date)
df$x = as.factor(df$x)



# plot 1 : time series

 aggregate = df %>%
        mutate(date = as.Date(date)) %>%
        group_by(month = format(date, "%Y-%m")) %>%
        summarise( mean = mean(y))

ts_1 <- ggplot(aggregate) + geom_line(aes(x = month, y = mean, group = 1)) +  theme(axis.text.x = element_text(angle = 90)) + ggtitle("time series 1")

plot_1 = ggplotly(ts_1)



#plot 2 : box plot

plot_2 <- plot_ly(df, y = ~y, color = ~x, type = "box") %>% layout(title = "boxplot")



#plot 3, 4 : scatter plots

df_1 <- df[which(df$x == "A"),]
df_2 <- df[which(df$x == "B"),]


plot_3 <- plot_ly( data = df_1, type = "scatter", mode = "markers", x = ~ y, y = ~z) %>% layout(title = "graph 3")

plot_4 <- plot_ly( data = df_2, type = "scatter", mode = "markers", x = ~ y, y = ~z) %>% layout(title = "graph 4")

Once these 4 plots have been created, I know how to save them together:

sub = subplot(plot_1, plot_2, plot_3, plot_4, nrows = 2)
#view result
sub

Now what I am trying to do, is have the user "toggle" (switch) between these graphs (as seen here: https://plotly.com/r/dropdowns/)

In a previous post (R: Switching Between Graphs ), I learned how to "glue" similar graphs together (e.g. 4 scatter plots). Now, I am trying to do so with different graphs (2 scatter plots, 1 time series and 1 box plot). I tried to adapt the code from the previous post to suit my example:

fig <- df %>% 
  add_trace(name = "A", plot_1) %>% 
  add_trace (name = "B" , df, y = ~y, color = ~x, type = "box") %>% layout(title = "boxplot")
  add_trace (name = "C" , data = df_1, type = "scatter", mode = "markers", x = ~ y, y = ~z) %>% layout(title = "graph 3") %>%
  add_trace( name = "D", data = df_2, type = "scatter", mode = "markers", x = ~ y, y = ~z) %>% layout(title = "graph 4") %>% 
  layout(xaxis = list(domain = c(0.1, 1)),
         yaxis = list(title = "y"),
         updatemenus = list(
           list(
             y = 0.7,
             buttons = list(
               list(method = "restyle",
                    args = list("visible", list(TRUE, FALSE, FALSE, FALSE)),
                    label = "A"),
               list(method = "restyle",
                    args = list("visible", list(FALSE, TRUE, FALSE, FALSE)),
                    label = "B"),
               list(method = "restyle",
                    args = list("visible", list(FALSE, FALSE, TRUE, FALSE)),
                    label = "C"),
               list(method = "restyle",
                    args = list("visible", list(FALSE, FALSE, FALSE, TRUE)),
                    label = "D")))))

But this produces the following errors:

Error: $ operator is invalid for atomic vectors
Error in add_data(p, data) : argument "p" is missing, with no default

Can someone please show me if it is possible to fix this problem? Instead of using the "add_trace" approach, is it somehow possible to individually call each plotly graph object by its name (e.g. subplot(plot_1, plot_2, plot_3, plot_4, nrows = 2)), "glue" all the graphs together, and then add a "toggle button" that lets the user switch between them?

(note: I need to be able to save the final result as a "html" file)

Thanks

Answer 1

First of all, you should take care about plots which add multiple traces (see nTracesA etc.)

Besides changing the trace visibility you'll need to seperate categorial and numerical data onto separate x and y-axes and manage their visibility, too (see xaxis2, xaxis3, xaxis4 - this also works with a single y-axis but in this case the grid isn't displayed properly)

As described in the docs:

The updatemenu method determines which plotly.js function will be used to modify the chart. There are 4 possible methods:

• "restyle": modify data or data attributes
• "relayout": modify layout attributes
• "update": modify data and layout attributes
• "animate": start or pause an animation (only available offline)

Accordingly the following, is using the update method (a lot of repition here - needs some cleanup, but I think it's better to understand this way):

# load libraries
library(dplyr)
library(plotly)

# create data
x <- sample(LETTERS[1:4],
            731,
            replace = TRUE,
            prob = c(0.25, 0.25, 0.25, 0.25))
y <- rnorm(731, 10, 10)
z <- rnorm(731, 5, 5)
date <- seq(as.Date("2014/1/1"), as.Date("2016/1/1"), by = "day")

df <- data.frame(x, y, z, date)
df$x = as.factor(df$x)

nTracesA <- nTracesC <- nTracesD <- 1
nTracesB <- length(unique(df$x))

plotA <- plot_ly(data = df %>%
                   mutate(date = as.Date(date)) %>%
                   group_by(month = format(date, "%Y-%m")) %>%
                   summarise(mean = mean(y)),
                 type = 'scatter', mode = 'lines', x= ~ month, y= ~ mean, name = "plotA", visible = TRUE, xaxis = "x", yaxis = "y")

plotAB <- add_trace(plotA, data = df, x = ~x, y = ~y, color = ~ x, name = ~ paste0("plotB_", x), 
                    type = "box", xaxis = "x2", yaxis = "y2", visible = FALSE, inherit = FALSE)

plotABC <- add_trace(plotAB, data = df[which(df$x == "A"),], 
                     type = "scatter", mode = "markers", x = ~ y, y = ~ z, 
                     name = "plotC", xaxis = "x3", yaxis = "y3", visible = FALSE, inherit = FALSE)

plotABCD <- add_trace(plotABC, data = df[which(df$x == "B"),], x = ~ y, y = ~ z,
                      type = "scatter", mode = "markers", name = "plotD", xaxis = "x4", yaxis = "y4", visible = FALSE, inherit = FALSE)

fig <- layout(plotABCD, title = "Initial Title",
              xaxis = list(domain = c(0.1, 1), visible = TRUE, type = "date"),
              xaxis2 = list(overlaying = "x", visible = FALSE),
              xaxis3 = list(overlaying = "x", visible = FALSE), 
              xaxis4 = list(overlaying = "x", visible = FALSE),
              yaxis = list(title = "y"),
              yaxis2 = list(overlaying = "y", visible = FALSE),
              yaxis3 = list(overlaying = "y", visible = FALSE),
              yaxis4 = list(overlaying = "y", visible = FALSE),
              updatemenus = list(
                list(
                  y = 0.7,
                  buttons = list(
                    list(label = "A",
                         method = "update",
                         args = list(list(name = paste0("new_trace_name_", 1:7), visible = unlist(Map(rep, x = c(TRUE, FALSE, FALSE, FALSE), each = c(nTracesA, nTracesB, nTracesC, nTracesD)))),
                                     list(title = "title A",
                                          xaxis = list(visible = TRUE),
                                          xaxis2 = list(overlaying = "x", visible = FALSE),
                                          xaxis3 = list(overlaying = "x", visible = FALSE),
                                          xaxis4 = list(overlaying = "x", visible = FALSE),
                                          yaxis = list(visible = TRUE),
                                          yaxis2 = list(overlaying = "y", visible = FALSE),
                                          yaxis3 = list(overlaying = "y", visible = FALSE),
                                          yaxis4 = list(overlaying = "y", visible = FALSE)))
                    ),
                    list(label = "B",
                         method = "update",
                         args = list(list(visible = unlist(Map(rep, x = c(FALSE, TRUE, FALSE, FALSE), each = c(nTracesA, nTracesB, nTracesC, nTracesD)))),
                                     list(title = "title B",
                                          xaxis = list(visible = FALSE),
                                          xaxis2 = list(overlaying = "x", visible = TRUE),
                                          xaxis3 = list(overlaying = "x", visible = FALSE),
                                          xaxis4 = list(overlaying = "x", visible = FALSE),
                                          yaxis = list(visible = FALSE),
                                          yaxis2 = list(overlaying = "y", visible = TRUE),
                                          yaxis3 = list(overlaying = "y", visible = FALSE),
                                          yaxis4 = list(overlaying = "y", visible = FALSE)))),
                    list(label = "C",
                         method = "update",
                         args = list(list(visible = unlist(Map(rep, x = c(FALSE, FALSE, TRUE, FALSE), each = c(nTracesA, nTracesB, nTracesC, nTracesD)))),
                                     list(title = "title C",
                                          xaxis = list(visible = FALSE),
                                          xaxis2 = list(overlaying = "x", visible = FALSE),
                                          xaxis3 = list(overlaying = "x", visible = TRUE),
                                          xaxis4 = list(overlaying = "x", visible = FALSE),
                                          yaxis = list(visible = FALSE),
                                          yaxis2 = list(overlaying = "y", visible = FALSE),
                                          yaxis3 = list(overlaying = "y", visible = TRUE),
                                          yaxis4 = list(overlaying = "y", visible = FALSE)))),
                    list(label = "D",
                         method = "update",
                         args = list(list(visible = unlist(Map(rep, x = c(FALSE, FALSE, FALSE, TRUE), each = c(nTracesA, nTracesB, nTracesC, nTracesD)))),
                                     list(title = "title D",
                                          xaxis = list(visible = FALSE),
                                          xaxis2 = list(overlaying = "x", visible = FALSE),
                                          xaxis3 = list(overlaying = "x", visible = FALSE),
                                          xaxis4 = list(overlaying = "x", visible = TRUE),
                                          yaxis = list(visible = FALSE),
                                          yaxis2 = list(overlaying = "y", visible = FALSE),
                                          yaxis3 = list(overlaying = "y", visible = FALSE),
                                          yaxis4 = list(overlaying = "y", visible = TRUE))))
                  ))))

print(fig)

# htmlwidgets::saveWidget(partial_bundle(fig), file = "fig.html", selfcontained = TRUE)
# utils::browseURL("fig.html")

Some related info: https://plotly.com/r/custom-buttons/ https://plotly.com/r/multiple-axes/

Answer 2

A user on the Rstudio community forum provided an answer : https://community.rstudio.com/t/gluing-graphs-together-switch-toggle-between-graphs-in-r-plotly/95891/3

I am still trying to figure out how to format the axis - maybe someone could take a look at this?

#load libraries 

library(plotly)
library(MASS)
library(dplyr)


# create data

x <- sample( LETTERS[1:4], 731, replace=TRUE, prob=c(0.25, 0.25, 0.25, 0.25) )
y <- rnorm(731,10,10)
z <- rnorm(731,5,5)
date= seq(as.Date("2014/1/1"), as.Date("2016/1/1"),by="day")
    
    df <- data.frame(x,y, z, date)
df$x = as.factor(df$x)



# plot 1 : time series

 aggregate = df %>%
        mutate(date = as.Date(date)) %>%
        group_by(month = format(date, "%Y-%m")) %>%
        summarise( mean = mean(y))

ts_1 <- ggplot(aggregate) + geom_line(aes(x = month, y = mean, group = 1)) +  theme(axis.text.x = element_text(angle = 90)) + ggtitle("time series 1")

plot_1 = ggplotly(ts_1)



#plot 2 : box plot

plot_2 <- plot_ly(df, y = ~y, color = ~x, type = "box") %>% layout(title = "boxplot")



#plot 3, 4 : scatter plots

df_1 <- df[which(df$x == "A"),]
df_2 <- df[which(df$x == "B"),]


plot_3 <- plot_ly( data = df_1, type = "scatter", mode = "markers", x = ~ y, y = ~z) %>% layout(title = "graph 3")

plot_4 <- plot_ly( data = df_2, type = "scatter", mode = "markers", x = ~ y, y = ~z) %>% layout(title = "graph 4")


fig = plot_ly()
fig = fig %>% add_trace(data = df %>%
                          mutate(date = as.Date(date)) %>%
                          group_by(month = format(date, "%Y-%m")) %>%
                          summarise( mean = mean(y)), type = 'scatter', mode = 'lines', x= ~month, y= ~mean,
                        name = "timeseries")
fig = fig %>%  add_trace(data = df[which(df$x == "A"),], y = ~y, color = ~x, 
                         type = "box", name = "boxplot") 
fig = fig %>%  add_trace( data = df[which(df$x == "B"),], 
                          type = "scatter", mode = "markers", x = ~ y, y = ~z, 
                          name= "graph2")
fig = fig %>%  add_trace(data = df[which(df$x == "A"),], y = ~y, color = ~x, 
                         type = "box", name = "boxplot2") 


fig %>% layout(xaxis = list(domain = c(0.1, 1)),
               yaxis = list(title = "y"),
               updatemenus = list(
                 list(
                   y = 0.7,
                   buttons = list(
                     list(method = "restyle",
                          args = list("visible", list(TRUE, FALSE, FALSE, FALSE)),
                          label = "A"),
                     list(method = "restyle",
                          args = list("visible", list(FALSE, TRUE, FALSE, FALSE)),
                          label = "B"),
                     list(method = "restyle",
                          args = list("visible", list(FALSE, FALSE, TRUE, FALSE)),
                          label = "C"),
                     list(method = "restyle",
                          args = list("visible", list(FALSE, FALSE, FALSE, TRUE)),
                          label = "D")))))

Answer 3

This is just a guess from the documentation but there is no add_data() call so maybe try this for your first line:

fig <- plot_ly() %>% add_data(df) %>%

See docs example:

plot_ly() %>% add_data(economics) %>% add_trace(x = ~date, y = ~pce)