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I am trying to create an R Markdown document that includes a tabset of interactive plots created using ggplotly. My goal is to generate these plots using loops like for, lapply, or purrr::map. While this approach successfully creates the tabs, the plots all appear at the last tab, all at once. However, when I remove ggplotly and use only ggplot, the code works fine. Similarly, when I create separate chunks for individual figures without using a loop, the plots are correctly generated in their respective tabs. What would be the underlying logic here to get the plots each for each tab?

I tried the answer from Interactive ggplotly graph is not plotted from inside for loop in Rmd file in R among others. I tried plot.new() but that removed the plots even from the last tab.

## **Count Distribution** {.tabset} ```{r, results='asis', warning=FALSE} # List of dataframes for the first tabset library(ggplot2) library(reshape2) library(plotly) hist_func <- function(matrix) { hist_plot <- ggplot(melt(as.data.frame(matrix))) + geom_line(stat = 'density', aes(x = value, ..scaled.., colour = variable)) + labs(x = NULL) + theme(legend.position = 'right') + scale_x_log10() return(hist_plot) } # Set seed set.seed(42) # Generate random gene count matrix c1 <- matrix(sample(0:10000, 10 * 1000, replace = TRUE), nrow = 10) c2 <- matrix(sample(0:10000, 10 * 1000, replace = TRUE), nrow = 10) c3 <- matrix(sample(0:10000, 10 * 1000, replace = TRUE), nrow = 10) c4 <- matrix(sample(0:10000, 10 * 1000, replace = TRUE), nrow = 10) c5 <- matrix(sample(0:10000, 10 * 1000, replace = TRUE), nrow = 10) # List of dataframes for the tabset dataframes_tab1 <- list(counts = c1, rawlog2 = c2, TMM = c3, DESEQ2 = c4, VOOM = c5) plt <- htmltools::tagList() # Generate tabset content using loop plotlist=list() for (i in seq_along(dataframes_tab1)) { df_name <- names(dataframes_tab1)[i] plotlist[[i]] <- ggplotly(hist_func(dataframes_tab1[[df_name]])) cat(paste('### ', df_name, '\n \n')) cat(' \n') # trying multiple approaches plt[[i]] <- as.widget(ggplotly(plotlist[[i]])) # to check if either method works #as taglist or without plotlist[[i]] plt[[i]] cat(' \n\n') } ```
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Adapting this answer from me to your case you could achieve your desired result like so.

First, as you want one chart per tab it is not necessary to create a list. Instead you can directly print your chart by wrapping in print(htmltools::tagList(...)). Second, the important part in my approach to add an initialization step to add the plotly JS dependencies needed to render the charts.

Note: I stripped down your example data to make it more minimal.

--- title: "Untitled" output: html_document date: "2023-08-31" --- ```{r setup, include=FALSE} knitr::opts_chunk$set(echo = FALSE) ``` ```{r, include=FALSE} library(ggplot2) library(reshape2) library(plotly) ``` ## **Count Distribution** {.tabset} ```{r} hist_func <- function(matrix) { hist_plot <- ggplot(melt(as.data.frame(matrix))) + geom_line(stat = "density", aes(x = value, ..scaled.., colour = variable)) + labs(x = NULL) + theme(legend.position = "right") + scale_x_log10() return(hist_plot) } ``` ```{r} # Set seed set.seed(42) # Generate random gene count matrix c1 <- matrix(sample(seq(100), 100, replace = TRUE), nrow = 10) c2 <- matrix(sample(seq(100), 100, replace = TRUE), nrow = 10) c3 <- matrix(sample(seq(100), 100, replace = TRUE), nrow = 10) c4 <- matrix(sample(seq(100), 100, replace = TRUE), nrow = 10) c5 <- matrix(sample(seq(100), 100, replace = TRUE), nrow = 10) # List of dataframes for the tabset dataframes_tab1 <- list(counts = c1, rawlog2 = c2, TMM = c3, DESEQ2 = c4, VOOM = c5) ``` ```{r include=FALSE} # Init step to include the JS dependencies plot_ly() ``` ```{r, results='asis', warning=FALSE} for (i in names(dataframes_tab1)) { cat(paste("### ", i, "\n \n")) cat("\n") print( htmltools::tagList( ggplotly(hist_func(dataframes_tab1[[i]])) ) ) cat("\n\n") } ```

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Thank you! I was beating my head against this and this solved it. I found so many other "solutions" for similar problems that didn't do the trick, but this one did.

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