Styjun

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Add a legend into the sidebar of a shiny flexdashboard

reproducing shiny using flexdashboard templateR + Shiny which hammer? straight Shiny, flexdashboard or shinydashboard?Flexdashboard Storyboard Shinycrosstalk's filter_select doesn't filter the graphflexdashboard .storyboard ShinyShiny flexdashboard - plot not renderingCreate reactive selectInput - flexdashboard with ShinyMinMax plot as ggplotscoping in shiny flexdashboardR flexdashboard and shiny interactive plot

.everyoneloves__top-leaderboard:empty,.everyoneloves__mid-leaderboard:empty,.everyoneloves__bot-mid-leaderboard:empty margin-bottom:0;

0

Am after some advice in fine-tuning a legend in the sidebar of my flexdashboard. (I'm basically on a journey of recreating Tableau functionality with R).

As you can see I've managed to get something together but I'd really be interested in:

• matching the background colour to the sidebar




• positioning it better, so that there is less "white space" around it and it's left aligned




• sizing of the font (and squares) a bit bigger than it's currently
  appearing.

Really appreciate any tips you all might be able to provide.

Extra bonus points of you can offer any guidance towards achieving this with a ggplotly (my next step), so that the legend is interactive via clicks).

---
title: "dash"
output: flexdashboard::flex_dashboard
runtime: shiny
---

```r setup, include=FALSE

library(tidyverse)
library(plotly)

data_set <- iris %>% 
 gather(key, value, -Species) %>% 
 group_by(Species, key) %>% 
 summarise(average_value = mean(value))

```


SideBar .sidebar
---

```r

# radio button
radioButtons("species_filter", "Species:", choices = c("All", levels(data_set$Species)), selected = "All")


# this function retrieves the legend out of the ggplot
g_legend <- function(a.gplot)
tmp <- ggplot_gtable(ggplot_build(a.gplot))
leg <- which(sapply(tmp$grobs, function(x) x$name) == "guide-box")
legend <- tmp$grobs[[leg]]
return(legend)

# plot the extracted legend in the sidebar
renderPlot(gridExtra::grid.arrange(g_legend(plot())))

```


Column
-----------------------------------------------------------------------

### Chart A

```r

# stacked bar plot

plot <- reactive(

 data_set %>% 
 if (input$species_filter == "All") . 
 else filter(., Species == input$species_filter) %>% 
 ggplot() +
 aes(key, average_value, fill = Species) %>%
 geom_bar(stat = "identity")

 )

renderPlot(plot() + theme(legend.position="none"))

```

r ggplot2 shiny flexdashboard ggplotly

share|improve this question

asked Mar 27 at 2:00

Julian TagellJulian Tagell

1344 bronze badges

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  I'm assuming this is a limitation of Flexdashboard, at the moment. But would love those plotly legends that allow clicking to filter... feature request, I guess.
  
  – Julian Tagell
  Apr 2 at 23:35
  

  
  
  
  

add a comment | 

0

Am after some advice in fine-tuning a legend in the sidebar of my flexdashboard. (I'm basically on a journey of recreating Tableau functionality with R).

As you can see I've managed to get something together but I'd really be interested in:

• matching the background colour to the sidebar




• positioning it better, so that there is less "white space" around it and it's left aligned




• sizing of the font (and squares) a bit bigger than it's currently
  appearing.

Really appreciate any tips you all might be able to provide.

Extra bonus points of you can offer any guidance towards achieving this with a ggplotly (my next step), so that the legend is interactive via clicks).

---
title: "dash"
output: flexdashboard::flex_dashboard
runtime: shiny
---

```r setup, include=FALSE

library(tidyverse)
library(plotly)

data_set <- iris %>% 
 gather(key, value, -Species) %>% 
 group_by(Species, key) %>% 
 summarise(average_value = mean(value))

```


SideBar .sidebar
---

```r

# radio button
radioButtons("species_filter", "Species:", choices = c("All", levels(data_set$Species)), selected = "All")


# this function retrieves the legend out of the ggplot
g_legend <- function(a.gplot)
tmp <- ggplot_gtable(ggplot_build(a.gplot))
leg <- which(sapply(tmp$grobs, function(x) x$name) == "guide-box")
legend <- tmp$grobs[[leg]]
return(legend)

# plot the extracted legend in the sidebar
renderPlot(gridExtra::grid.arrange(g_legend(plot())))

```


Column
-----------------------------------------------------------------------

### Chart A

```r

# stacked bar plot

plot <- reactive(

 data_set %>% 
 if (input$species_filter == "All") . 
 else filter(., Species == input$species_filter) %>% 
 ggplot() +
 aes(key, average_value, fill = Species) %>%
 geom_bar(stat = "identity")

 )

renderPlot(plot() + theme(legend.position="none"))

```

r ggplot2 shiny flexdashboard ggplotly

share|improve this question

asked Mar 27 at 2:00

Julian TagellJulian Tagell

1344 bronze badges

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  I'm assuming this is a limitation of Flexdashboard, at the moment. But would love those plotly legends that allow clicking to filter... feature request, I guess.
  
  – Julian Tagell
  Apr 2 at 23:35
  

  
  
  
  

add a comment | 

Am after some advice in fine-tuning a legend in the sidebar of my flexdashboard. (I'm basically on a journey of recreating Tableau functionality with R).

As you can see I've managed to get something together but I'd really be interested in:

• matching the background colour to the sidebar




• positioning it better, so that there is less "white space" around it and it's left aligned




• sizing of the font (and squares) a bit bigger than it's currently
  appearing.

Really appreciate any tips you all might be able to provide.

Extra bonus points of you can offer any guidance towards achieving this with a ggplotly (my next step), so that the legend is interactive via clicks).

---
title: "dash"
output: flexdashboard::flex_dashboard
runtime: shiny
---

```r setup, include=FALSE

library(tidyverse)
library(plotly)

data_set <- iris %>% 
 gather(key, value, -Species) %>% 
 group_by(Species, key) %>% 
 summarise(average_value = mean(value))

```


SideBar .sidebar
---

```r

# radio button
radioButtons("species_filter", "Species:", choices = c("All", levels(data_set$Species)), selected = "All")


# this function retrieves the legend out of the ggplot
g_legend <- function(a.gplot)
tmp <- ggplot_gtable(ggplot_build(a.gplot))
leg <- which(sapply(tmp$grobs, function(x) x$name) == "guide-box")
legend <- tmp$grobs[[leg]]
return(legend)

# plot the extracted legend in the sidebar
renderPlot(gridExtra::grid.arrange(g_legend(plot())))

```


Column
-----------------------------------------------------------------------

### Chart A

```r

# stacked bar plot

plot <- reactive(

 data_set %>% 
 if (input$species_filter == "All") . 
 else filter(., Species == input$species_filter) %>% 
 ggplot() +
 aes(key, average_value, fill = Species) %>%
 geom_bar(stat = "identity")

 )

renderPlot(plot() + theme(legend.position="none"))

```

r ggplot2 shiny flexdashboard ggplotly

share|improve this question

asked Mar 27 at 2:00

Julian TagellJulian Tagell

1344 bronze badges

---
title: "dash"
output: flexdashboard::flex_dashboard
runtime: shiny
---

```r setup, include=FALSE

library(tidyverse)
library(plotly)

data_set <- iris %>% 
 gather(key, value, -Species) %>% 
 group_by(Species, key) %>% 
 summarise(average_value = mean(value))

```


SideBar .sidebar
---

```r

# radio button
radioButtons("species_filter", "Species:", choices = c("All", levels(data_set$Species)), selected = "All")


# this function retrieves the legend out of the ggplot
g_legend <- function(a.gplot)
tmp <- ggplot_gtable(ggplot_build(a.gplot))
leg <- which(sapply(tmp$grobs, function(x) x$name) == "guide-box")
legend <- tmp$grobs[[leg]]
return(legend)

# plot the extracted legend in the sidebar
renderPlot(gridExtra::grid.arrange(g_legend(plot())))

```


Column
-----------------------------------------------------------------------

### Chart A

```r

# stacked bar plot

plot <- reactive(

 data_set %>% 
 if (input$species_filter == "All") . 
 else filter(., Species == input$species_filter) %>% 
 ggplot() +
 aes(key, average_value, fill = Species) %>%
 geom_bar(stat = "identity")

 )

renderPlot(plot() + theme(legend.position="none"))

```

share|improve this question

asked Mar 27 at 2:00

Julian TagellJulian Tagell

1344 bronze badges

share|improve this question

asked Mar 27 at 2:00

Julian TagellJulian Tagell

1344 bronze badges

asked Mar 27 at 2:00

Julian TagellJulian Tagell

1344 bronze badges

asked Mar 27 at 2:00

Julian TagellJulian Tagell

1344 bronze badges