I'm creating an Rshiny with two tabs. The data is a list of students, and the plots/tables are to be filtered through the input of grade selection on a drop-down list. The table I have on tab one is working fine, but everything I have tried to do to connect the last two plots on the second tab to the input are not working. Now I have it to where it is just showing totals without using the input filter of grade. Can anyone detail how to connect my input to both output plots? I'll put my code below
library(shiny)
library(tidyverse)
students = read.csv("C:/Users/j062d273/Downloads/RShiny Grade EX.csv",
stringsAsFactors = FALSE)
# Define UI for application that draws a histogram
ui <- fluidPage(
# Application title
headerPanel("Student Data"),
# tabs set up
tabsetPanel(
tabPanel(title = "Students by Grade",
mainPanel(width = 12, align = "center",
selectInput("grade", "Select Grade", choices=unique(sort(students$Grade,
decreasing = FALSE)), selected = 1),
submitButton("Go"),
tags$h3("Student List"),
div(style = "border:1px black solid;width:80%",tableOutput("student_list"))
)),
tabPanel(title = "Trends by Grade",
mainPanel(width = 12,align = "center",
div(style = "float:left;width:36%;",plotOutput("male_fem_dist")),
div(style = "float:right;width:64%;",plotOutput("ethnicity_plot")))
)))
# Define server logic required to draw plot
server <- function(input, output) {
output$student_list <- renderTable({
gradefilter <- subset(students, students$Grade == input$grade)
})
output$male_fem_dist <- renderPlot({
ggplot(students, aes(x=Gender)) +
geom_bar(fill = "blue", color = "red") +
ggtitle("Gender Count by Selected Grade")
})
output$ethnicity_plot <- renderPlot({
ggplot(students, aes(x=Ethnicity)) +
geom_bar(fill = "red", color = "blue") +
ggtitle("Ethnicity Count by Selected Grade")
})
}
# Run the application
shinyApp(ui = ui, server = server)
Filter the dataset first, and then use it in both table and plot.
Try this
server <- function(input, output) {
gradefilter <- reactive({subset(students, students$Grade == input$grade)})
output$student_list <- renderTable({gradefilter()})
output$male_fem_dist <- renderPlot({
ggplot(gradefilter(), aes(x=Gender)) +
geom_bar(fill = "blue", color = "red") +
ggtitle("Gender Count by Selected Grade")
})
output$ethnicity_plot <- renderPlot({
ggplot(gradefilter(), aes(x=Ethnicity)) +
geom_bar(fill = "red", color = "blue") +
ggtitle("Ethnicity Count by Selected Grade")
})
}
Related
I would like click-select points and group them based on color.
I can save selected points with color information into a new data frame and plot it, however I would like to keep track and see what was already selected on the interactive plot.
How can I show/label already selected points or make it permanent after "Add selection"?
library(shiny)
library(tidyverse)
library(DT)
library(colourpicker)
ui = fluidPage(
colourInput("col", "Select colour", "purple"),
actionButton("addToDT", "Add selection", icon = icon("plus")), hr(),
plotOutput("plot", click = "plot_click", dblclick = "plot_reset"),
DT::dataTableOutput('plot_DT'), hr(),
textOutput("clickcoord"),
DT::dataTableOutput('final_DT'),
plotOutput("plotSelected")
)
server = function(input, output, session) {
selectedPoint = reactiveVal(rep(FALSE, nrow(mtcars)))
output$clickcoord <- renderPrint({
print(input$plot_click)
})
observeEvent(input$plot_click, {
clicked = nearPoints(mtcars, input$plot_click, allRows = TRUE)$selected_
selectedPoint(clicked | selectedPoint())
})
observeEvent(input$plot_reset, {
selectedPoint(rep(FALSE, nrow(mtcars)))
})
output$plot_DT = DT::renderDataTable({
mtcars$sel = selectedPoint()
mtcars = dplyr::filter(mtcars, sel == TRUE) %>% mutate(group_color = input$col)
})
final_DT = reactiveValues()
final_DT$df = data.frame()
FinalData = eventReactive(input$addToDT, {
mtcars$sel = selectedPoint()
mtcars = dplyr::filter(mtcars, sel == TRUE) %>% mutate(group_color = input$col)
final_DT$df = bind_rows(final_DT$df, mtcars)
})
output$final_DT = renderDataTable({FinalData()})
output$plot = renderPlot({
mtcars$sel = selectedPoint()
ggplot(mtcars, aes(wt, mpg, color = mtcars$sel, fill=mpg)) +
geom_point(shape = 21, size = 6, stroke = 2) +
scale_color_manual(values = c("#ffffff00", input$col)) +
scale_fill_viridis_c() +
theme_bw()
})
output$plotSelected = renderPlot({
sel_df = FinalData()
ggplot(sel_df, aes(wt, mpg, fill = group_color, colour = group_color)) +
geom_point(shape = 21, size = 6, stroke = 2) +
scale_color_manual(values = unique(sel_df$group_color)) +
scale_fill_manual(values = unique(sel_df$group_color)) +
theme_bw()
})
observeEvent(input$addToDT, {
selectedPoint(rep(FALSE, nrow(mtcars)))
})
}
shinyApp(ui, server)
I think this is the "crux" of what your are looking for. I used a very similar example that I found in the help for entitled:
A demonstration of clicking, hovering, and brushing
(https://shiny.rstudio.com/reference/shiny/0.13.1/plotoutput)
It is very similar to your example.
I create a matrix of T/F elements where the rows are the observations and the columns are in which batch the observation is selected. So when you launch the whole matrix is False, but as you click on observations the switch to positive in the first column. Then if you click addSelection and continue you start switching the observations in the next column.
Could you confirm that this what you are looking for?
Below is the code.
shinyApp(
ui = basicPage(
fluidRow(
column(
width = 4,
plotOutput("plot",
height = 300,
click = "plot_click", # Equiv, to click=clickOpts(id='plot_click')
),
actionButton("addToDT", "Add selection", icon = icon("plus")), hr(),
h4("Clicked points"),
tableOutput("plot_clickedpoints"),
),
column(
width = 4,
verbatimTextOutput("counter"),
),
)
),
server = function(input, output, session) {
data <- reactive({
input$newplot
# Add a little noise to the cars data so the points move
cars + rnorm(nrow(cars))
})
output$plot <- renderPlot({
d <- data()
plot(d$speed, d$dist, main = paste("No of Sets Chosen", input$addToDT))
})
output$plot_clickinfo <- renderPrint({
cat("Click:
")
str(input$plot_click)
})
selectedPoints <- reactiveVal(rep(FALSE, nrow(cars)))
selectionMatrix <- reactiveVal(matrix(data = F, nrow = nrow(cars), ncol = 7))
observeEvent(input$plot_click, {
clicked <- nearPoints(data(), input$plot_click, "speed", "dist", allRows = TRUE)$selected
selectedPoints(clicked | selectedPoints())
tmp <- unlist(selectionMatrix())
tmp[, (input$addToDT + 1)] <- selectedPoints()
selectionMatrix(tmp)
})
observeEvent(input$addToDT, {
selectedPoints(rep(FALSE, nrow(cars)))
})
output$plot_clickedpoints <- renderTable({
# if (input$addToDT==0) {
res <- selectionMatrix()
return(res)
})
}
)
I am currently trying to make an interactive app on shiny where with my data frame "keep_df" you can choose which kind of plot you want to use and for the x and y axes you can choose any of the columns from keep_df. Below is my code. I'm not getting any error messages, but the code is not running as desired. I was wondering if anyone had any suggestions. Thanks!
ui <- navbarPage ("Title",
tabPanel("Chart builder",
sidebarLayout(
sidebarPanel(
pickerInput(inputId = 'chart', label = '1. Select chart type', choices = c("Scatter plot", "Bar chart", "Histogram", "Pie chart", "Box plot"), selected = NULL, multiple = FALSE),
pickerInput(inputId = 'xaxis', label = '2. Select X-axis', choices = colnames(keep_df), selected = NULL, multiple = FALSE),
pickerInput(inputId = 'yaxis', label = '3. Select Y-axis', choices = colnames(keep_df), selected = NULL, multiple = FALSE),
uiOutput("picker2"),
actionButton("view", "View selection"),
),
mainPanel(ui <- DT::dataTableOutput("charttable"), plotOutput("plots")),
)
)
)
server <- function(input, output, session) {
data <- reactive(
keep_df
)
plots <- reactive({
if (input$chart == 'Scatter plot') {
ggplot(data(), aes(x = input$xaxis, y = input$yaxis)) +
geom_point(colour = "black")
}
if (input$chart == 'Bar chart') {
ggplot(data(), aes(x = input$xaxis, y = input$yaxis)) +
geom_point(colour = "black")
}
})
output$plots <- renderPlot(
plots()
)
}
You were pretty close with your code, I noticed a few issues. First, you have an extra ui <- which I could see causing an error. Second, in the plots reactive, where you had x = input$xaxis, it would send a string to the ggplot, rather than a variable. Meaning it wouldn't read the column. I also made the plots reactive as an if and else if, rather than two if statements. Hope this helps!
Note that I didn't have the dataframe, so I just used mtcars for simplicity. There were a few lines I blocked out too. I also added the library and the shinyApp call too, since it wasn't in your example.
library(shiny)
library(ggplot2)
library(shinyWidgets)
keep_df<-mtcars #Don't have the data, just using mtcars
ui <- navbarPage ("Title",
tabPanel("Chart builder",
sidebarLayout(
sidebarPanel(
pickerInput(inputId = 'chart', label = '1. Select chart type', choices = c("Scatter plot", "Bar chart", "Histogram", "Pie chart", "Box plot"), selected = NULL, multiple = FALSE),
pickerInput(inputId = 'xaxis', label = '2. Select X-axis', choices = colnames(keep_df), selected = NULL, multiple = FALSE),
pickerInput(inputId = 'yaxis', label = '3. Select Y-axis', choices = colnames(keep_df), selected = NULL, multiple = FALSE)#,
# uiOutput("picker2"), #Not doing anything
# actionButton("view", "View selection") #Not doing anything
),
mainPanel(DT::dataTableOutput("charttable"), plotOutput("plots")), #Removed the ui <-
)
)
)
server <- function(input, output, session) {
data <- reactive(
keep_df
)
plots <- reactive({
if (input$chart == 'Scatter plot') {
#without the eval(parse(text =)), it reads as string, not variable
ggplot(data(), aes(x = eval(parse(text = input$xaxis)), y = eval(parse(text = input$yaxis)))) +
geom_point(colour = "black")
} else if (input$chart == 'Bar chart') {
ggplot(data(), aes(x = eval(parse(text = input$xaxis)), y = eval(parse(text = input$yaxis)))) +
geom_boxplot(colour = "black")
}
})
output$plots <- renderPlot(
plots()
)
}
shinyApp(ui, server)
How can I reset the graph to display a blank plot? I've created a reset button and have tried various recommendations, but they usually cause some sort of problem or they do nothing at all.
ui <- fluidPage(
theme = shinytheme("cerulean"),
navbarPage( "Unemployment Rate Comparison Tool",
tabPanel("Interactive Graph",
titlePanel("US Unemployment Rates Before and After COVID-19"),
sidebarLayout(
sidebarPanel(
selectInput(
inputId = "y",
label = "Select State(s) to Graph",
choices = unique(q_long$State),
selected = "United States",
multiple = TRUE
), # select input end
radioButtons(
inputId = "x",
label = "Displaying Unemployment Rates for 2013-2022",
choices = c("Year"),
selected = "Year"
), # Radio buttons end
actionButton("run_plot", "Run Plot"),
actionButton("reset", "Clear Output"),
), # side bar panel end
mainPanel(
span(strong("Compare State Unemployment Rates Pre and Post COVID.", style = "color:black"),style = "font-si16pt"),
div("Select the state(s) you wish to view from the drop down menu. Once you have made your selections, click \"Run Plot\"."),
br(),
plotlyOutput(outputId = "graph"),
) # Main panel end
) # select input end
), #navbar interactive graph
tabPanel("Data", DT::dataTableOutput(outputId="datasheet"))# navbar data end
) #Navbar end
) # fluid page end
server <- function(input, output, session) {
q_filtered <- eventReactive(input$run_plot, {
filter(q_long, State %in% input$y)
})
output$graph <- renderPlotly({
ggplot(q_filtered(), aes(x = .data[[input$x]], y = unemployment, color = State)) + geom_point() + geom_line() + geom_vline(aes(xintercept = 2020)) + scale_x_continuous(breaks = q$year)
}) # render plotly end
output$datasheet<-DT::renderDataTable({
DT::datatable(data=q,
rownames=FALSE)}
)
} # server end
shinyApp(ui = ui, server = server)
I am just really not sure what to do from here
Maybe like this (not tested):
server <- function(input, output) {
Plot <- reactiveVal()
q_filtered <- eventReactive(input$run_plot, {
filter(q_long, State %in% input$y)
})
observe({
gg <- ggplot(q_filtered(), aes(x = .data[[input$x]], y = unemployment, color = State)) + geom_point() + geom_line() + geom_vline(aes(xintercept = 2020)) + scale_x_continuous(breaks = q$year)
Plot(gg)
})
observeEvent(input$reset, {
Plot(plotly_empty())
})
output$graph <- renderPlotly({
Plot()
})
output$datasheet <- DT::renderDataTable({
DT::datatable(data=q,
rownames=FALSE)}
)
} # server end
I try to display interactive plots by using R shiny. I can successfully make the GUI and published, but the plots in tabPanel shows nothing, just like the picture shows below. There is the data I used (have been downloaded into my laptop).
I think problem may caused by the way how I preprocessing my data in server.R, but whatever I tried, it still display nothing. No Error shows when I run the app.
enter image description here
My code in ui.R:
library(shiny)
shinyUI(fluidPage(
titlePanel("Data Viz Lab"),
sidebarLayout(
sidebarPanel(
## Add X-Variable select element
selectInput(inputId = "var_x",
label = h5("X-Variable"),
choices = c("Structure.Cost", "Land.Value", "Home.Value", "Home.Price.index"),
selected = "Land.Value"),
## Add Fill Color select element
selectInput(inputId = "color",
label = h5("Fill Color"),
choices = c("brown", "yellow", "green", "blue", "red"),
selected = "brown"),
## Add log-scale check box
checkboxInput(inputId = "log",
label = "log-sclae for X-variable in Scatterplot?",
value = FALSE),
## Add Y-Variable select element
selectInput(inputId = "var_y",
label = h5("Y-Variable"),
choices = c("Structure.Cost", "Land.Value", "Home.Value", "Home.Price.index"),
selected = "Structure.Cost"),
## Add Circle-Size side bar
sliderInput(inputId = "size",
label = h5("Circle-Size"),
min = 1,
max = 10,
value = 3),
## Add Outlier color select element
selectInput(inputId = "color_out",
label = h5("Outlier Color"),
choices = c("white", "yellow", "green", "blue", "red"),
selected = "white")
),
mainPanel(
tabsetPanel( # Establish tabset panel
tabPanel(
# Tab1
title = "Histogram",
value = plotOutput(outputId = "hist") # Add an figure in tab1
),
tabPanel(
# Tab2
title = "Scatterplot",
value = plotOutput(outputId = "scatter") # Add an figure in tab2
)
)
)
)
))
My code in server.R:
library(shiny)
library(ggplot2)
library(sp)
library(dplyr)
# setwd()
landdata = read.csv("landdata.csv")
options(scipen = 999)
shinyServer(function(input, output) {
## Plotting Histogram
output$hist = renderPlot({
# Plotting
if (input$log == FALSE){
ggplot(landdata, aes_string(x = input$var_x)) +
geom_histogram(color = input$color)
}else{
ggplot(landdata, aes_string(x = input$var_x)) +
geom_histogram(color = input$color) +
scale_x_log10(input$var_x)
}
})
## Plotting Scatter plot
output$scatter = renderPlot({
# Data pre-processing
p = ggplot(data = landdata, aes_string(x = input$var_x, y = input$var_y)) +
geom_point() +
stat_ellipse(type = "norm", level = 0.95, color = "black")
build = ggplot_build(p)$data
pts = build[[1]]
elli = build[[2]]
Outlier = point.in.polygon(pts$x, pts$y, elli$x, elli$y)
landdata = cbind(landdata, Outlier)
landdata$Outlier = ifelse(landdata$Outlier == 0, yes = "Y", no = "N") %>% factor(level = c("Y", "N"))
# Plotting
if (input$log == FALSE){
ggplot(landdata, aes_string(x = input$var_x, y = input$var_y)) +
geom_point(aes(color = Outlier), size = input$size) +
scale_color_manual(values = c(input$color, input$color_out))
}else{
ggplot(landdata, aes_string(x = input$var_x, y = input$var_y)) +
geom_point(aes(color = Outlier), size = input$size) +
scale_color_manual(values = c(input$color, input$color_out)) +
scale_x_log10(input$var_x)
}
})
})
The mistake lies in the tabPanel setup. value is not the correct argument for the plot. value is "the value that should be sent when tabsetPanel reports that this tab is selected" (taken from the manual). That means, value has the role of an id (like id argument of tabsetPanel or outputId of plotOutput).
Remove value = to make it work (the code snippet below gave me an output on my system).
tabsetPanel( # Establish tabset panel
tabPanel(
# Tab1
title = "Histogram",
plotOutput(outputId = "hist") # Add an figure in tab1
),
tabPanel(
# Tab2
title = "Scatterplot",
plotOutput(outputId = "scatter") # Add an figure in tab2
)
)
I'm working on a Shiny app for a project where a ggplot is the main interface for the user. Depending on input from the sidebar, I'd like the app to record coordinates for two events: a single click (which I have working), or a double click (which is where I'm stuck). Essentially, I'd like to be able to create a way to record a starting and ending point based on sidebar conditions. Here's a brief example:
library(shiny)
library(ggplot2)
ui = pageWithSidebar(
headerPanel("Example"),
sidebarPanel(
radioButtons("color", "Pick Color", c("Pink", "Green", "Blue")),
selectInput("shape", "Select Shape:", c("Circle", "Triangle"))
),
mainPanel(
fluidRow(column(width = 6,
h4("Click plot to add points"),
plotOutput("plot1", click = "plot_click"),
actionButton("rem_point", "Remove Last Point")),
column(width = 6,
h4("Table of points on plot"),
tableOutput("table")))
)
)
server = function(input, output){
values = reactiveValues()
values$DT = data.frame(x = numeric(),
y = numeric(),
color = factor(),
shape = factor())
output$plot1 = renderPlot({
ggplot(values$DT, aes(x = x, y = y)) +
geom_point(aes(color = color,
shape = shape), size = 5) +
lims(x = c(0, 100), y = c(0, 100)) +
theme(legend.position = "bottom") +
scale_color_discrete(drop = FALSE) +
scale_shape_discrete(drop = FALSE)
})
observeEvent(input$plot_click, {
add_row = data.frame(x = input$plot_click$x,
y = input$plot_click$y,
color = factor(input$color, levels = c("Pink", "Green", "Blue")),
shape = factor(input$shape, levels = c("Circle", "Triangle")))
values$DT = rbind(values$DT, add_row)
})
observeEvent(input$rem_point, {
rem_row = values$DT[-nrow(values$DT), ]
values$DT = rem_row
})
output$table = renderTable({
values$DT[, c('color', 'shape')]
})
}
shinyApp(ui, server)
In this example, when the user selects Green or Blue, I'd like to only record the single click as the starting point and record NA for the end point. When they select Pink, I'd like to record the single click as the starting point and the double click as the ending point. Any help would be greatly appreciated!
(Example created by #blondeclover on a question from earlier.)
Found a solution! Just create an observeEvent() to observe a double click and update values$DT with the new information.