I have the following code that I am unsuccessfully trying to run. I just want to be able to filter a graph output based on an input range. In this example, if the range input is set to 1-5, I would like to see 5 points on the graph, likewise range input of 2-5 shows 4 points.
##UI
require(shiny)
shinyUI(fluidPage(
titlePanel(title=h4("Races", align="center")
),
sidebarPanel(
sliderInput("num", "Number:",
min = 0, max = 5,step=1,value=c(0,2)),
mainPanel(
plotOutput("plot2")))))
##server
library(dplyr)
library(ggplot2)
shinyServer(function(input,output){
num<-c(1,2,3,4,5)
let<-c("A","B","C","D","E")
date<-c("2015-5-1","2015-6-1","2015-7-1","2015-8-1","2015-9-1")
df<-data.frame(num,let,date)
dat<-reactive({
df %>% filter(num==input$num)})
output$plot2<-renderPlot({
ggplot(dat(),aes(x=date,y=num))+geom_point(colour='red')},height = 400,
width = 600)})
I would like to show the range of values on the graph based on the input range but only 1 value is showing, not the range of values with corresponding dates.
Thanks in advance.
Is this what you want? Edit: Now you would be able to see all the points you have specified
#rm(list = ls())
library(shiny)
library(ggplot2)
num<-c(1,2,3,4,5)
let<-c("A","B","C","D","E")
date<-c("2015-5-1","2015-6-1","2015-7-1","2015-8-1","2015-9-1")
df <- data.frame(num,let,date)
ui <- fluidPage(
titlePanel(title=h4("Races", align="center")),
sidebarPanel(
sliderInput("num", "Number:",min = 0, max = 5,step=1,value=c(1,2))),
mainPanel(plotOutput("plot2")))
server <- function(input,output){
dat <- reactive({
test <- df[df$num %in% seq(from=min(input$num),to=max(input$num),by=1),]
print(test)
test
})
output$plot2<-renderPlot({
ggplot(dat(),aes(x=date,y=num))+geom_point(colour='red')},height = 400,width = 600)}
shinyApp(ui, server)
Related
I'm trying to create interactive visualisation (using R shiny) but I have a problem, I want to create an interactive barplot, where user is able to select (like subset) data from my df, I want to have a plot of quantiles (from 0.75 to 1, by 0.01). So user can select using slider which quantile of data he wants to see.
for example - 10000 value in my column is 0.75 percentile, so when user selects 0.75 percentile order on slider, R shiny generates barplot for this column with values from min value to 10000.
same for 0.76 etc...
I've tried but i don't know how to set this, i just can do barplot with number of breaks, but don't know how to set max value like in my desired output
Something like this? You can add some selectInput for the column choice.
library(shiny)
library(tidyverse)
ui <- fluidPage(
titlePanel("Iris Quantile"),
sidebarLayout(
sidebarPanel(
sliderInput("quantile",
"Quantile",
min = 0,
max = 1,
value = 0.75,
step = 0.01)
),
mainPanel(
plotOutput("distPlot")
)
)
)
server <- function(input, output) {
filter_iris <- function(column, value){
quantile_value <- quantile(iris %>% pull(all_of(column)), value)
iris %>% filter(.data[[column]] < quantile_value)
}
output$distPlot <- renderPlot({
ggplot(data = filter_iris("Petal.Length", input$quantile), aes(x = Petal.Length)) +
geom_bar()
})
}
shinyApp(ui = ui, server = server)
I want to design a reactive interaction graph for a time series for shiny.
It is used for when I have a time series. I change the first point of the time series.
Then I can get the reactive graph changed for the point changed.
I have trouble for how to assign the value input into the function. Specifically, for the
yinput<-sensi(num). I want to the input be some number range from 0.1 to 0.9.but my sensitive's
function only allow to enter one input.
Is there any idea for that?
Thanks
library(ggplot2)
sensi<-function(input)
{
y<-c(input,5,12,21,30,50,90,100)
return(y)
}
Date = c("2020/07/16","2020/07/23","2020/07/30","2020/08/06","2020/08/13","2020/08/20","2020/08/27","2020/09/13")
num<-c(0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9)
yinput<-sensi(num)
df <- data.frame(yinput, Date = as.Date(Date))
ui <- fluidPage(
titlePanel(title=h4("plot1", align="center")),
sidebarPanel(
sliderInput("num", "Number:",min = 0, max = 0.9,value=0.5)),
mainPanel(plotOutput("plot2")))
server <- function(input,output){
dat <- reactive({
test <- df[df$num %in% seq(from=min(input$num),to=max(input$num),by=1),]
print(test)
test
})
output$plot2<-renderPlot({
ggplot(df) + aes(Date, y) + geom_line()})}
shinyApp(ui, server)
Here's a very basic example
You should be doing your 'thinking' inside your 'server' function.
Hopefully this example will show you how reactive inputs and outputs relate to each other, and you can extend it to your plot.
require(shiny)
ui <- fluidPage(
sliderInput("num", "Number:", min = 0.1, max = 0.9, value = 0.5),
textOutput("number_display")
)
server <- function(input, output){
output$number_display <-
renderText({
as.character(input$num)
})
}
shinyApp(ui = ui, server = server)
Where I've said as.character(input$num), you'll want to do something with num to make your plot.
I want to create a small shiny app to explore a scoring function that I am writing for a set of data observations. This is my first shiny app so bear with me.
What I want to show is the data table where one column is computed by a function (let's say f(x) = x^2 + y) where x is another (numeric) column in the table and y should be adjustable with a slider in the sidebar.
I want to make the table reactive, so that as soon as the slider is adjusted, the content that is displayed will be updated. Does anyone have a link to a tutorial (I could not find a similar problem) or a suggestion how to handle this. If so, please let me know!
This is the code I have so far:
library(shiny)
#### INIT ####
x <- 1
y <- 0.5
z <- 2
df <- data.frame(
a=1:10,
b=10:1
)
df['score'] <- df[,x]^y + z
#### UI ####
ui <- fluidPage(
title = "Examples of DataTables",
sidebarLayout(
sidebarPanel(
sliderInput("x", "x:",
min = 0, max = ncol(df),
value = 1),
sliderInput("y", "y:",
min = 1, max = 10,
value = 1),
sliderInput("z", "z:",
min = 1, max = 100,
value = 20)
),
mainPanel(
tabsetPanel(
id = 'dataset',
tabPanel("df", dataTableOutput("df"))
)
)
)
)
#### SERVER ####
server <- function(input, output) {
sliderValues <- reactive({
df['score'] <- df[,input$x]^input$y + input$z
})
sliderValues()
output$df<- renderDataTable(df)
}
#### RUN ####
shinyApp(ui = ui, server = server)
Just make the data.frame you actually plot reactive. For example
server <- function(input, output) {
calcualtedValues <- reactive({
df['score'] <- df[,input$x]^input$y + input$z
df
})
output$df<- renderDataTable(calcualtedValues())
}
Here the calcualtedValues reactive element returns a new data.frame when the input is updated, and then you actually render that updated data.frame rather than the original data.frame each time.
I've looked through R Shiny tutorials and stackoverflow for answers related to my query. I usually wait for 3-4 days to solve a coding problem before I attempt to post.
I have an animated slider in my UI that loops through time interval in a column (column a) . I'm trying to produce an animated line plot that plots y values of another column (column b), corresponding to the nrow() of that time interval. The slider works perfectly, but I haven't been able to plot the output.
I mightve missed some concepts related to reactivity in Shiny app. Appreciate any guidance I can get related to my query. I'll be happy to post more info if needed.
a <- c(0,1,2,3,4,5,6)
b <- c(50,100,40,30,20,80)
mydata <- cbind(a,b)
mydata <- as.data.frame(mydata())
ui <- fluidPage (
headerPanel("basic app"),
sidebarPanel(
sliderInput("slider",
label = "Time elapsed",
min = 0,
max = nrow(mydata()),
value = 1, step = 1,
animate =
animationOptions(interval = 200, loop = TRUE))
),
mainPanel(
plotlyOutput("plot")
)
)
server <- function(input, output) {
sliderValues <- reactive({
data.frame(
Name = "slider",
Value = input$slider)
})
output$plot <- renderPlot({
x<- as.numeric(input$slider)
y <- as.numeric(b[x])
ggplot(mydata,aes_string(x,y))+ geom_line()
})
}
Just as a demo, I wanted the animated plot to come out like this, but in correspondance to UI slider values :
library(gganimate)
library(ggplot2)
fake <- c(1,10)
goods <- c(11,20)
fakegoods <- cbind(fake,goods)
fakegoods <- data.frame(fakegoods)
ggplot(fakegoods, aes(fake, goods)) + geom_line() + transition_reveal(1, fake)
Does this accomplish what you are looking for? Note that I removed the first element, 0, from vector a as your original example had more elements in a than b, and in order for them to be cbind together they must be the same length.
library(ggplot2)
library(shiny)
a <- c(1,2,3,4,5,6)
b <- c(50,100,40,30,20,80)
mydata <- cbind(a,b)
mydata <- as.data.frame(mydata)
ui <- fluidPage (
headerPanel("basic app"),
sidebarPanel(
sliderInput("slider",
label = "Time elapsed",
min = min(mydata$a),
max = max(mydata$a),
value = min(mydata$a), step = 1,
animate =
animationOptions(interval = 200, loop = TRUE))
),
mainPanel(
plotOutput("plot")
)
)
server <- function(input, output) {
output$plot <- renderPlot({
plotdata <- mydata[1:which(input$slider==mydata$a),]
p <- ggplot(plotdata,aes(x = a,y = b))
if(nrow(plotdata)==1) {
p + geom_point()
} else {
p + geom_line()
}
})
}
Given the following ui.R and server.R and circuit.csv; I can produce a simple plot which reacts to the user input (power in this case).
However, not all values for power are returned. For example, .5 produces a plot whereas .6 does not, so on and so forth at random occurrence throughout the power range.
If i plot as a table instead, to check my work, same thing, certain power inputs work as expected and others produce no table, and also no plot when asking to plot.
ui.R
library(shiny)
library(ggplot2)
shinyUI(fluidPage(
hr(),
sidebarLayout(
sidebarPanel(
sliderInput("power",label = "Power",
min = 0, max = 5, value = .5, step = .1)
),
mainPanel(
p("Lum vs Distance by Power"),
plotOutput('plot1')
)
)
))
server.R
library(shiny)
library(ggplot2)
df <- read.table(file = "circuit.csv", sep=",", header = TRUE)
shinyServer(function(input, output) {
output$plot1 <- renderPlot({
df2 <- subset(df,df$pow==input$power)
p <- ggplot(df2)+
geom_point(aes(x=dist, y=lum))
print(p)
})
})
Link to github (for csv data)
I would post images but am not allowed to do so at this time.