Facet chart in a Shiny web app with lots of plots

[Piranha]

Hello,

I am trying to create a shiny app so that my colleagues can quickly visualize the trends in a very large database. The database that I am using is very similar in structure to the gapminder database, so I will use that as a toy example.

Here is what I have:

library(shiny)
library(tidyverse)
library(gapminder)

### Pre-process data

## functions
pct_change <- function(x) {
  ((x - lag(x,1)) / lag (x,1)) * 100
}

## data frame to be used in shiny app
df <- gapminder %>% 
  select(country, year, gdpPercap) %>% 
  group_by(country) %>% 
  mutate(gdpPercap_change = pct_change(gdpPercap)) %>% 
  mutate(gdpPercap_change = round(gdpPercap_change, 2)) %>%  
  mutate(growth_group = case_when(year == 2007 & gdpPercap_change > 20                        ~ "high growth",
                                  year == 2007 & gdpPercap_change < 20 & gdpPercap_change > 0 ~ "moderate growth",
                                  year == 2007 & gdpPercap_change < 0                         ~ "declining",
                                  TRUE                                                        ~ as.character(NA)
  )) %>% 
  fill(growth_group, .direction = "up") %>% 
  na.omit()


### UI portion
ui <- fluidPage(
  titlePanel("Gapminder: Dashboard"),
  
  sidebarLayout(
    sidebarPanel(
      selectInput(inputId="group", label="Choose a Growth Group", 
                  choices=unique(df$growth_group), selected="declining")
    ),
    mainPanel(
      plotOutput("chart_1")
    )
  )
)


### Server portion
server <- function(input, output) {
  
  output$chart_1 <- renderPlot({
    chart <- df %>% 
      filter(growth_group == input$group) %>% 
      ggplot(aes(x=year, y=gdpPercap_change)) +
      geom_line() +
      geom_hline(yintercept = 0) +
      facet_wrap(~ country, scales = "free_y")
    chart
  })
}

### run shiny app
shinyApp(ui = ui, server = server)

My data frame looks like this:

  country      year gdpPercap gdpPercap_change growth_group
  <fct>       <int>     <dbl>            <dbl> <chr>       
1 Afghanistan  1957      821.             5.31 high growth 
2 Afghanistan  1962      853.             3.93 high growth 
3 Afghanistan  1967      836.            -1.98 high growth 
4 Afghanistan  1972      740.           -11.5  high growth 
5 Afghanistan  1977      786.             6.23 high growth 
6 Afghanistan  1982      978.            24.4  high growth 
> 

The countries are broken out into 3 "growth_groups" or buckets:

  growth_group        n
  <chr>           <int>
1 declining          12
2 high growth        61
3 moderate growth    69

I want my colleagues to quickly see a chart with all of the individual countries placed within their respective growth_group. I chose to use facet_wrap for this purpose. However, with so many countries in each group, the chart quickly becomes unreadable.

Example: with 69 countries in the "moderate" growth group. This is very hard to read.

Two questions:

1. Is there a way to make a facet grid "scroll-able"? Since we are rendering on a web page, scrolling down a long list of charts should be quite intuitive to users. The users are expecting to see lots of charts, but not expecting them to be crammed into a small printable area. I cannot seem to find a way to do this.

2. Alternatively, if facet_wrap is not the right solution here, what other techniques would should I look into? I tried facet_grid, but that seems to make things worse!

Any help would be greatly appreciated!

Thanks in advance

[FJCC]

Two ideas:

1. Use the ncol argument of facet_wrap to set the number of columns in the output.

facet_wrap(~ country, scales = "free_y", ncol = 5)

This will make the output taller and possibly more legible.
2. Group the countries by some characteristic, their continent or alphabetically, and display each group on its own tab. If the facet plot on each tab fits comfortably in the vertical space, then switching from tab to tab is less disorienting than scrolling through a long series of plots. Check out tabsetPanel() in the shiny help.

[Piranha]

Thank you. Will try this out. I think it will work.