Adding dates to a reactive graph

[fitzer23]

I previously asked this question before here : How to add dates as an input into a reactive graph but have since changed my filtering method and now the dates cause an error for the graphs. How do I go about getting all the graphs to change based on the dates selected.
UI:

dateInput("startdate", "Start Date:", value = "2019-08-01", format = "dd-mm-yyyy",
                min = "2000-01-01", max = "2019-09-04"),
      
      dateInput("enddate", "End Date:", value = "2019-09-05", format = "dd-mm-yyyy",
                min = "2000-01-02", max = "2019-09-05")

Server:

server <- function(input, output, session) {
filteredData <- reactive({
    filtNgo <- newngo
if(!is.null(input$victimGender)) {
      filtNgo <- filtNgo %>% filter(Victim.Gender %in% input$victimGender)
    }
    if(!is.null(input$traffickingType)) {
      filtNgo <- filtNgo %>% filter(Trafficking.Type %in% input$traffickingType)
    }
    if(!is.null(input$traffickingSubType)) {
      filtNgo <- filtNgo %>% filter(Trafficking.Sub.Type %in% input$traffickingSubType)
    }
    if(!is.null(input$Source)) {
      filtNgo <- filtNgo %>% filter(Data.Source %in% input$Source)
    }
filtNgo
  })

output$traff <- renderPlotly({
    plot_ly(filteredData(), labels = ~Trafficking.Type, type = "pie",
            marker = list(colors = colors,
                          line = list(color = '#FFFFFF', width = 1))) %>%
      layout(showlegend = FALSE)
  })
  
  output$Sub <- renderPlotly({
    ggplot(filteredData(), aes(x=Trafficking.Sub.Type)) + geom_bar()
  })
  
  output$vGender <- renderPlotly({
    ggplot(filteredData(), aes(x=Victim.Gender)) + geom_bar()
  })

I have attached a few of the graphs ensure that more than one graph will work.

[hadley]

As I've mentioned in the past, you will be much more likely to get help if you create a reprex as described in http://mastering-shiny.org/action-workflow.html#reprex. As well as making it easier for people help you, creating reprexes will also help you build up your own Shiny skills.

[fitzer23]

I have created a reprex to test it out, if anything else needs to be added please let me know.

library(shinyjs)
library(shiny)
library(shinydashboard)
library(ggplot2)
library(dplyr)
library(plotly)
library(shinyWidgets)

tType = c("Forced Labour", "Forced Labour", "Sexual Exploitation", "Sexual Exploitation", "Sexual Exploitation", "Sexual Exploitation")
start = c("11/05/2005", "02/09/2008","5/24/2009","11/23/2011", "11/23/2011", "11/23/2011")
end = c("11/05/2005", "02/09/2008","5/24/2009","11/23/2011", "11/23/2011", "11/23/2011")

newngo = c(tType, start, end)
newngo = as.data.frame(newngo)

UI:

ui <- dashboardPage(skin = ("black"),
                    dashboardHeader(title = "Human Trafficking"),
                    
                    dashboardSidebar(
                      sidebarMenu(
                        
                        dateInput("start", "Start Date:", value = "2019-08-01", format = "dd-mm-yyyy",
                                  min = "2000-01-01", max = "2019-09-04"),
                        
                        dateInput("end", "End Date:", value = "2019-09-05", format = "dd-mm-yyyy",
                                  min = "2000-01-02", max = "2019-09-05")
                      )
                    ),
                    
                    dashboardBody(
                      fluidRow(     
                        box(width = 6, solidHeader = TRUE, status = "success",
                            title = "Trafficking Type", 
                            selectInput("traffickingType", "Choose a trafficking type: ", 
                                        choices = sort(unique(newngo$tType)), selected = NULL,
                                        multiple = TRUE, selectize = TRUE, width = NULL, size = NULL),
                            plotlyOutput("traff", width = '750px', height = '300px')
                        )
                        )
)
)

Server:

server <- function(input, output, session) {
  filteredData <- reactive({
    filtNgo <- newngo
    
    if(!is.null(input$traffickingType)) {
      filtNgo <- filtNgo %>% filter(tType %in% input$traffickingType)
    }
    
    filtNgo
  })
  
  output$traff <- renderPlotly({
    #newngo %>% filter(start >= input$startdate, end <= input$end) %>%
      plot_ly(filteredData(), labels = tType, type = "pie",
              marker = list(colors = colors,
                            line = list(color = '#FFFFFF', width = 1))) %>%
      layout(showlegend = FALSE)
  })
  
}

shinyApp(ui, server)

[hadley]

This is a good start, but it's not a reprex because I can't easily copy and paste it into my R session. You also seem to have a lot of code that is unrelated to the problem you're experiencing; I'd recommend removing that so it's easier to see exactly what the problem is.

[fitzer23]

I have edited my answer above and think I have got it right this time. Thanks for the help too

[hadley]

A minimal reprex would look more like this:

library(shiny)
library(plotly)

newngo <- data.frame(
  tType = c("Forced Labour", "Forced Labour", "Sexual Exploitation", "Sexual Exploitation", "Sexual Exploitation", "Sexual Exploitation"),
  start =  c("11/05/2005", "02/09/2008", "5/24/2009", "11/23/2011", "11/23/2011", "11/23/2011"),
  end = c("11/05/2005", "02/09/2008", "5/24/2009", "11/23/2011", "11/23/2011", "11/23/2011")
)

ui <- fluidPage(
  dateInput("start", "Start Date:",
    value = "2019-08-01", format = "dd-mm-yyyy",
    min = "2000-01-01", max = "2019-09-04"
  ),
  dateInput("end", "End Date:",
    value = "2019-09-05", format = "dd-mm-yyyy",
    min = "2000-01-02", max = "2019-09-05"
  ),
  plotlyOutput("traff", width = "750px", height = "300px")
)

server <- function(input, output, session) {
  output$traff <- renderPlotly({
    # newngo %>% filter(start >= input$startdate, end <= input$end) %>%
    plot_ly(newngo, color = ~tType, type = "pie")
  })
}

shinyApp(ui, server)

However, that doesn't work at all, and I don't know enough about plotly to diagnose the problem.

[andresrcs]

You have to pass numeric values for the pie chart, you just have to count the categories first

library(shiny)
library(plotly)
library(dplyr)
library(lubridate)

newngo <- data.frame(stringsAsFactors = FALSE,
  tType = c("Forced Labour", "Forced Labour", "Sexual Exploitation", "Sexual Exploitation", "Sexual Exploitation", "Sexual Exploitation"),
  start =  c("11/05/2005", "02/09/2008", "5/24/2009", "11/23/2011", "11/23/2011", "11/23/2011"),
  end = c("11/05/2005", "02/09/2008", "5/24/2009", "11/23/2011", "11/23/2011", "11/23/2011")
)

ui <- fluidPage(
  dateInput("start", "Start Date:",
            value = "2005-05-01", format = "dd-mm-yyyy",
            min = "2000-01-01", max = "2019-09-04"
  ),
  dateInput("end", "End Date:",
            value = "2019-09-05", format = "dd-mm-yyyy",
            min = "2000-01-02", max = "2019-09-05"
  ),
  plotlyOutput("traff", width = "750px", height = "300px")
)

server <- function(input, output, session) {
  output$traff <- renderPlotly({
    newngo %>%
      mutate_at(c("start", "end"), ~mdy(.)) %>% 
      filter(start >= ymd(input$start), end <= ymd(input$end)) %>%
      count(tType) %>% 
      plot_ly(values = ~n, labels = ~tType, type = "pie")
  })
}

shinyApp(ui, server)

[fitzer23]

@andresrcs Thanks for the help, that works just one small problem. When I run the code some of the data doesn't go through and I get the error Warning: 35 failed to parse. What would be the best way to deal with this and get the data to not fail. Thanks

[andresrcs]

Warning: 35 failed to parse. What would be the best way to deal with this and get the data to not fail.

I can't know without seeing sample data that produces this warning message.