Importing (standalone) R graphics into ArcGIS Portal/Dashboard?

[ChristineBaver]

Hello. I frequently create (standalone) graphics and animations using R. The files extensions of these graphics/animations when saved is usually html or gif. Can these be loaded onto an ArcGIS dashboard? I tried copy and pasting HTML code from an interactive R figure under "Source", but the dashboard did not allow me to save the HTML code and there was no error message specifying the issue. 

Just curious if anyone can speak to the possibilities or limitations of uploading graphics or animations created from R into ArcGIS dashboards or other ArcGIS Storyboards.

Thank you!  

[Ed_]

I love R and imo its plotting capabilities are much better than Python. For static R plots you can insert them as images, but for dynamic/interactive plots like something created using ggplotly, what i usually do is that i create a tiny R Shiny Web App of the plot(s) and embed them into ESRI webapps such Dashboards using an iframe. 

The only ESRI webapp/desktop dashboard that is well integrated with R is Insights, you can look into that, but unfortunately Insights is getting deprecated, which is a real bummer. 

Hope this helps,

Happy Plotting 🙂

[ChristineBaver]

Thank you Ed! This was very helpful. I will look into R shiny apps and iframe. I will post again if I'm not able to figure out how to embed using iframe. 

[EricaNova]

Ohh this sounds very interesting! I've not heard of this - if you know of a blog post detailing the method, I'm all ears!

Erica

[SimonSchütte_ct]

Here are some links:

Scripting in Insights—ArcGIS Insights | Documentation

Try the Insights scripting environment

ArcGIS Insights: Python/R Scripting and Advanced Analytics - YouTubeEsri/insights-scripting-guide: (Deprecated: This repository is no longer maintained.) A guide and sa...

[Ed_ · Accepted solution]

@ChristineBaver @EricaNova I don't have a blog post on this, but i can share the code of one my R Shiny Apps that's a web application showing interactive Pyramid plots of Hispanic Population. This web app was then embedded as an iframe into a ESRI web application. If you would like to have the data behind this app to play and learn the code, please dm me, and i can share it with you 🙂.

App URL: https://saadib.shinyapps.io/PopulationPyramidPlots/ 

R Shiny Web App Embedded in StoryMaps: https://storymaps.arcgis.com/stories/885ec2e2359d48bab885da95d20fa810

library(shiny)
library(shinythemes)
library(tidyverse)
library(plotly)
library(janitor)

# Define UI for application 
ui =    fluidPage(
  navbarPage( theme = shinytheme("paper"),
             tabPanel("Pyramid Plots",
                      icon = icon("chart-area"),
                      plotlyOutput(outputId = "PP1",
                                   width = "1024px",
                                   height = "768px",
                                   inline = T),
                      plotlyOutput(outputId = "PP2",
                                   width = "1024px",
                                   height = "768px",
                                   inline = T),
        )
    )
)

# Define server logic 
server = function(input, output) {

  pop_hisp = read_csv("HISPANIC_POPULATION_PYRAMID_DATA.csv")
  
  pop_gen = read_csv("GEN_POP_PYRAMID_DATA.csv")
  pop_hisp = clean_names(pop_hisp)
  pop_hisp = pop_hisp %>%  dplyr::rename(Females = females)
  pop_hisp = pop_hisp %>%  dplyr::rename(Males = males)
  
  pop_gen = clean_names(pop_gen)
  pop_gen = pop_gen %>%  dplyr::rename(Females = females)
  pop_gen = pop_gen %>%  dplyr::rename(Males = males)
  
  # Draw a pyramid plot
  
  # Clean data
  
  pop_hisp_df = pop_hisp %>% select(age_group,
                                    Males,
                                    Females) %>% 
    gather(key = Type, value = Value, -c(age_group))
  
  pop_gen_df = pop_gen %>% select(age_group,
                                  Males,
                                  Females) %>% 
    gather(key = Type, value = Value, -c(age_group))
  
  # Make male values negative
  pop_hisp_df$Value = ifelse(pop_hisp_df$Type == "Males", -1*pop_hisp_df$Value, pop_hisp_df$Value)
  pop_gen_df$Value = ifelse(pop_gen_df$Type == "Males", -1*pop_gen_df$Value, pop_gen_df$Value)
  
  # Change the order of values to reflect them in the plot
  reverse_legend_labels = function(plotly_plot) {
    n_labels <- length(plotly_plot$x$data)
    plotly_plot$x$data[1:n_labels] <- plotly_plot$x$data[n_labels:1]
    plotly_plot
  }
  
  output$PP1 = renderPlotly({ 
    
    # Plot
    gg_pop_hisp = ggplot(pop_hisp_df, aes( x = forcats::as_factor(age_group), y = Value, fill = Type,
                                           text = paste('Age group:', age_group, '\nValue:', abs(Value), '\nType:', Type))) +
      geom_bar(data = subset(pop_hisp_df, Type == "Females"), stat = "identity") +
      geom_bar(data = subset(pop_hisp_df, Type == "Males"), stat = "identity") +
      #geom_text(aes(label = paste0(abs(Value), "%"))) +
      scale_y_continuous(limits=c(-20,20),
                         breaks=c(-15,-10,0,10,15),
                         labels=paste0(c(15,10,0,10,15),"%")) +          # CHANGE
      scale_fill_manual(name = "", values = c("Females"="#FC921F", "Males"="#149ECE"), labels = c("Females", "Males")) +
      ggtitle("FIGURE 3: HISPANIC POPULATION BY GENDER AND AGE GROUP") +
      labs(x = "AGE GROUPS", y = "PERCENTAGE POPULATION", fill = "Gender") +
      theme_minimal() +
      theme(legend.position="bottom") +
      coord_flip()  
    
    # Interactive
    ggplotly(gg_pop_hisp, tooltip = 'text') %>% 
      layout(
        legend = list(
          orientation = 'h', x = 0.3, y = -0.3, 
          title = list(text = '')
        )
      ) %>%
      reverse_legend_labels()
    
    })
  
  output$PP2 = renderPlotly({ 
    
    # Plot
    gg_pop_gen = ggplot(pop_hisp_df, aes(x = forcats::as_factor(age_group), y = Value, fill = Type,
                                         text = paste('Age group:', age_group, '\nValue:', abs(Value), '\nType:', Type)))  +
      geom_bar(data = subset(pop_hisp_df, Type == "Females"), stat = "identity") + 
      geom_bar(data = subset(pop_hisp_df, Type == "Males"), stat = "identity") + 
      #geom_text(aes(label = paste0(abs(Value), "%"))) +
      #scale_y_continuous(labels = function(z) paste0(abs(z), "%")) +          # CHANGE
      scale_y_continuous(
        limits=c(-20,20),
        breaks=c(-15,-10,0,10,15),
        labels=paste0(c(15,10,0,10,15),"%")
      ) + 
      scale_fill_manual(name = "", values = c("Females"="#ED5151", "Males"="#6B6BD6"), labels = c("Females", "Males")) +
      ggtitle("FIGURE 4: TOTAL POPULATION BY AGE AND GENDER") +
      labs(x = "AGE GROUPS", y = "PERCENTAGE POPULATION", fill = "Gender") +
      theme_minimal() +
      theme(legend.position="bottom") +
      coord_flip()
    
    # Interactive
    ggplotly(gg_pop_gen, tooltip = 'text') %>% 
      layout(
        legend = list(
          orientation = 'h', x = 0.3, y = -0.3, 
          title = list(text = '')
        )
      ) %>%
      #reverse_legend_labels() %>% 
      layout(margin = list(l = 50, r = 50, b = 100, t = 50),
             annotations = list(x = 0.3, y = -0.3, text = "<b>Figure 3 & 4</b>: Data for Figure 3 and 4 was retrieved from: \n U.S. Census Bureau, American Community 5-Year Estimates",
                                xref='paper', yref='paper', showarrow = F, 
                                xanchor='right', yanchor='auto', xshift=0, yshift=0,
                                font = list(size = 10)))
    
  })
}
# Run the application 
shinyApp(ui = ui, server = server)

[ChristineBaver]

Hi Ed, 

Thank you! I apologize for not responding earlier, I didn't get any notifications that you had provided another response. Thank you for sharing the code. I will reviewing this closely next week. I will let you know if I'm able to get it to work. Thank you again!!!

[EricaNova]

Nice! I've made Shiny apps before but hadn't thought to embed them in dashboards/story maps. Great idea.