I have a doubt in shiny ploting a GGPlot Bar Graph.
I can recognize coordinates of mouse click (x,y), but I need know a value of bar (x-axis) to refresh the graph with parameter and simulate a drill-down.
Anyone can help me?
library(shiny)
library(ggplot2)
ui <- fluidPage(
plotOutput("plot", click = "GGPlot_click")
)
server <- function(input, output, session) {
v <- reactiveValues(
click1 = NULL
)
# Handle clicks on the plot
observeEvent(input$GGPlot_click, {
v$click1 <- input$GGPlot_click
})
observeEvent(input$reset, {
v$click1 <- NULL
})
output$plot <- renderPlot({
pg <- ggplot(cars, aes(speed, dist)) + geom_bar(stat="identity")
print(pg)
if (!is.null(v$click1$x))
print(paste(v$click1$x, v$click1$y, sep = " / "))
#print(v$click1)
})
}
shinyApp(ui, server)
images and code: https://github.com/faustobranco/stackquestion
I find a way to resolve:
imagens and codes: https://github.com/faustobranco/StackQuestions
library(shiny)
library(ggplot2)
ui <- fluidPage(
plotOutput("plot", click = "plot_click"),
verbatimTextOutput("info")
)
server <- function(input, output, session) {
output$plot <- renderPlot({
ggplot(cars, aes(speed, dist)) + geom_bar(stat="identity")
})
output$info <- renderText({
xy_str <- function(e) {
if(is.null(e)) return("NULL\n")
paste0("x=", round(e$x, 1), "\n")
}
x_Numeric <- function(e) {
if(is.null(e)) return(0)
round(e$x, 1)
}
paste0(
"click: x = ", xy_str(input$plot_click),
"Nearest x-axis[?]: ", toString(which(abs(as.numeric(cars$speed)-as.numeric(x_Numeric(input$plot_click)))==min(abs(as.numeric(cars$speed)-as.numeric(x_Numeric(input$plot_click))))))
)
})
}
shinyApp(ui, server)
Related
Given this data here:
p <- ggplot(mpg, aes(displ, cty)) + geom_point() + facet_grid(drv ~ cyl)
g <- ggplot_gtable(ggplot_build(p))
strip_both <- which(grepl('strip-', g$layout$name))
fills <- c("red","green","blue","yellow","red","green","blue","yellow")
k <- 1
for (i in strip_both) {
j <- which(grepl('rect', g$grobs[[i]]$grobs[[1]]$childrenOrder))
g$grobs[[i]]$grobs[[1]]$children[[j]]$gp$fill <- fills[k]
k <- k+1
}
grid.draw(g)
I want to add a legend for the colors of the facets:
as shown here
One option to achieve your desired result would be with an auxiliary geom_point layer which draws nothing but is only used to map a variable with your desired four categories on the fill aes. Doing so will automatically add a fill legend for which we could set your desired colors using scale_fill_manual. Additionally I switched the key_glyph for the point layer to draw_key_rectto mimic your desired style for the legend keys and added na.rm to silent the warning about removed NAs:
library(ggplot2)
library(grid)
p <- ggplot(mpg, aes(displ, cty)) + geom_point() + facet_grid(drv ~ cyl) +
geom_point(data = data.frame(x = NA_real_, y = NA_real_, fill = c("AB", "D", "FF", "v")),
aes(x = x, y = y, fill = fill), na.rm = TRUE, key_glyph = "rect") +
scale_fill_manual(values = c("AB" = "red", D = "yellow", FF = "blue", v = "green"), name = NULL) +
theme(legend.position = "bottom")
g <- ggplot_gtable(ggplot_build(p))
strip_both <- which(grepl('strip-', g$layout$name))
fills <- c("red","green","blue","yellow","red","green","blue","yellow")
k <- 1
for (i in strip_both) {
j <- which(grepl('rect', g$grobs[[i]]$grobs[[1]]$childrenOrder))
g$grobs[[i]]$grobs[[1]]$children[[j]]$gp$fill <- fills[k]
k <- k+1
}
grid.draw(g)
I would like to download rhandsontable output object from an R Shiny app into .xlsx and .pdf format. Does anyone have any idea how to do this? For example, I want to download the tables in the results tab in the app below (the codes are copied from my other question earlier):
library(shiny)
library(rhandsontable)
ui <- navbarPage("App",
tabPanel("Input",
numericInput('num_of_table', "Number of sub tabs: ", value = 1, min = 1, max = 10),
uiOutput("input")),
tabPanel("Results",
uiOutput("results"))
)
server <- function(input, output,session) {
### Input ###
input_table <- reactive({
list_of_input_table = list()
for (i in c(1:input$num_of_table)){
mat <- matrix(c(1:25) * i, ncol = 5, nrow = 5)
list_of_input_table[[i]] = as.data.frame(mat)
}
index = c(1:i)
list_of_input_table[index]
})
observeEvent(input$num_of_table, {
lapply(seq_len(input$num_of_table), function(i) {
output[[paste0('input_table_', i)]] <- renderRHandsontable({
rhandsontable(input_table()[[i]])
})
})
})
output$input <- renderUI({
nTabs = input$num_of_table
myTabs1 = lapply(seq_len(nTabs), function(x){
tabPanel(paste("Tab", x),
column(12,
rHandsontableOutput(paste0("input_table_", x))))
})
do.call(tabsetPanel, myTabs1)
})
### Results ###
results_table <- reactive({
list_of_results_table = list()
for (i in c(1:input$num_of_table)){
req(input[[paste0("input_table_", i)]])
list_of_results_table[[i]] <- hot_to_r(input[[paste0("input_table_", i)]])[2:5]/hot_to_r(input[[paste0("input_table_", i)]])[1:4]
}
return(list_of_results_table)
})
observeEvent(input$num_of_table, {
lapply(seq_len(input$num_of_table), function(i) {
output[[paste0('results_table_', i)]] <- renderRHandsontable({
rhandsontable(results_table()[[i]])
})
})
})
output$results <- renderUI({
nTabs = input$num_of_table
myTabs2 = lapply(seq_len(nTabs), function(x){
tabPanel(paste("Tab", x),
column(12,
rHandsontableOutput(paste0("results_table_", x))))
})
do.call(tabsetPanel, myTabs2)
})
}
shinyApp(ui,server)
Appreciate any help! Thanks!
This will download the results but you will need to first click all the tabs in the results to essentially have the results rhandsontables active and then hit the downloadButton which you can also change to a downloadLink().
library(shiny)
library(rhandsontable)
library(writexl)
ui <- navbarPage("App",
tabPanel("Input",
numericInput('num_of_table', "Number of sub tabs: ", value = 1, min = 1, max = 10),
uiOutput("input")
),
tabPanel("Results",
downloadButton("dwnld", "Download Results"),
uiOutput("results"))
)
server <- function(input, output,session) {
### Input ###
input_table <- reactive({
list_of_input_table = list()
for (i in c(1:input$num_of_table)){
mat <- matrix(c(1:25) * i, ncol = 5, nrow = 5)
list_of_input_table[[i]] = as.data.frame(mat)
}
index = c(1:i)
list_of_input_table[index]
})
observeEvent(input$num_of_table, {
lapply(seq_len(input$num_of_table), function(i) {
output[[paste0('input_table_', i)]] <- renderRHandsontable({
rhandsontable(input_table()[[i]])
})
})
})
output$input <- renderUI({
nTabs = input$num_of_table
myTabs1 = lapply(seq_len(nTabs), function(x){
tabPanel(paste("Tab", x),
column(12,
rHandsontableOutput(paste0("input_table_", x))))
})
do.call(tabsetPanel, myTabs1)
})
### Results ###
results_table <- reactive({
list_of_results_table = list()
for (i in c(1:input$num_of_table)){
req(input[[paste0("input_table_", i)]])
list_of_results_table[[i]] <- hot_to_r(input[[paste0("input_table_", i)]])[2:5]/hot_to_r(input[[paste0("input_table_", i)]])[1:4]
}
return(list_of_results_table)
})
observeEvent(input$num_of_table, {
lapply(seq_len(input$num_of_table), function(i) {
output[[paste0('results_table_', i)]] <- renderRHandsontable({
rhandsontable(results_table()[[i]])
})
})
})
output$results <- renderUI({
nTabs = input$num_of_table
myTabs2 = lapply(seq_len(nTabs), function(x){
tabPanel(paste("Tab", x),
column(12,
rHandsontableOutput(paste0("results_table_", x))))
})
do.call(tabsetPanel, myTabs2)
})
output$dwnld <- downloadHandler(
filename = function(){ paste0("results.xlsx")},
content = function(file){
resultslist <- lapply(1:input$num_of_table, function(x) hot_to_r(input[[paste0("results_table_",x)]]))
write_xlsx(resultslist, path = file)
}
)
}
shinyApp(ui,server)
I am trying to build a dynamic Shiny app that insert sliders in a bs_accordion_sidebar.
The "add" button is working well but I can't figure out what I should add in my "delete" button code to update the barplot ?
Also, when clicking on the panel title, I think it should collapse and change his color but nothing happen ?
Thanks for any help !
library(shiny)
library(bsplus)
# global button counter
cpt <- 0
# function to create a new slider input
newinput <- function(ID, tag){
div(id=ID,
bs_append(
tag = tag,
title_side = ID,
content_side = NULL,
content_main = sliderInput( inputId = paste0("slider_",ID),
label = paste0("slider_",ID),
value = 0,
min=0,
max=10)
)
)
}
# UI
ui <- shinyUI(fluidPage(
titlePanel("bs_append and insertUI"),
sidebarPanel(
fluidRow(
actionButton("add", "+"),
mytag <- bs_accordion_sidebar(id = "accordion",
spec_side = c(width = 4, offset = 0),
spec_main = c(width = 8, offset = 0)),
div(id = "placeholder"),
actionButton("delete", "-")
)
),
mainPanel(
plotOutput('show_inputs')
),
use_bs_accordion_sidebar()
))
# SERVER
server <- shinyServer(function(input, output) {
# reactive function to collect all input values
AllInputs <- reactive({
myvalues <- sapply(names(input)[!names(input) %in% c("add", "delete")], function(x) input[[x]])
print(myvalues)
return(myvalues)
})
# simple output barplot
output$show_inputs <- renderPlot({
barplot(AllInputs())
})
# take a dependency on 'add' button
observeEvent(input$add, {
cpt <<- cpt + 1
insertUI(
selector ='#placeholder',
where = "beforeEnd",
ui = newinput(ID = cpt,
tag = mytag)
)
})
# take a dependency on 'delete' button
observeEvent(input$delete, {
removeUI(selector = paste0('#', cpt))
cpt <<- cpt - 1
})
})
shinyApp(ui, server)
I have found the answer here : https://stackoverflow.com/a/51517902/12812645
it was necessary to nullify the input deleted by removeUI
here is the corrected code using shinyjs :
library(shiny)
library(bsplus)
library(shinyjs)
# global button counter
cpt <- 0
# function to create a new slider input
newinput <- function(ID, tag){
div(id=ID,
bs_append(
tag = tag,
title_side = ID,
content_side = NULL,
content_main = sliderInput( inputId = paste0("slider_",ID),
label = paste0("slider_",ID),
value = 0,
min=0,
max=10)
)
)
}
# UI
ui <- shinyUI(fluidPage(
titlePanel("bs_append and insertUI"),
sidebarPanel(
fluidRow(
actionButton("add", "+"),
mytag <- bs_accordion_sidebar(id = "accordion",
spec_side = c(width = 4, offset = 0),
spec_main = c(width = 8, offset = 0)),
div(id = "placeholder"),
actionButton("delete", "-")
)
),
mainPanel(
plotOutput('show_inputs')
),
useShinyjs(debug = TRUE),
use_bs_accordion_sidebar()
))
# SERVER
server <- shinyServer(function(input, output) {
# reactive function to collect all input values
AllInputs <- reactive({
myvalues <- sapply(names(input)[!names(input) %in% c("add", "delete")], function(x) input[[x]])
myvalues <- unlist(myvalues[!unlist(lapply(myvalues, is.null))])
print(myvalues)
return(myvalues)
})
# simple output barplot
output$show_inputs <- renderPlot({
barplot(AllInputs())
})
# take a dependency on 'add' button
observeEvent(input$add, {
cpt <<- cpt + 1
insertUI(
selector ='#placeholder',
where = "beforeEnd",
ui = newinput(ID = cpt,
tag = mytag)
)
})
# take a dependency on 'delete' button
observeEvent(input$delete, {
removeUI(selector = paste0('#', cpt))
runjs(paste0('Shiny.onInputChange("slider_',cpt,'", null)'))
cpt <<- cpt - 1
})
})
shinyApp(ui, server)
How can I create a "table result" to each relationship I assumed in the selectInput "Col" and "Row"? Dinamicaly, after each press 'ok' botom.
library(shiny)
shinyUI(fluidPage(
h4("Give a valor between 0 to 5, to each col/row relationship"),
uiOutput("colrow"),
hr(),
h5("Result:"),
tableOutput("result")
))
shinyServer(
function(input, output, session) {
cols <<- c("Select"="", "col01" = "c01", "col02" = "c02")
rows <<- c("Select"="", "row01" = "r01", "row02" = "r02")
values <<- c("Select"="", 1:5)
output$colrow <- renderUI({
div(selectInput("ipt_col", label = "Col",
choices = c(cols),
selected = cols[1],
width = "50%"),
selectInput("ipt_row", label = "Row",
choices = c(rows),
selected = rows[1],
width = "50%"),
selectInput("ipt_vlr", label = "Value",
choices = c(values),
selected = ""),
actionButton("bt_ok", "ok")
)
})
colrow_vlr <- eventReactive(input$bt_ok, {
as.data.frame(matrix(input$ipt_vlr, 1,1, dimnames = list(input$ipt_row,input$ipt_col)))
})
output$result <- renderTable({
colrow_vlr()
})
})
I changed your code a little bit and now it works. I added comments at where the changes were made.
library(shiny)
ui <- fluidPage(
h4("Give a valor between 0 to 5, to each col/row relationship"),
uiOutput("colrow"),
hr(),
h5("Result:"),
# using DT which is recommended in shiny
DT::dataTableOutput("result")
)
server <- function(input, output, session) {
# no need to assign in the global env especially 'cols' is reserved
cols <- c("Select"="", "col01" = "c01", "col02" = "c02")
rows <- c("Select"="", "row01" = "r01", "row02" = "r02")
values <- c("Select"="", 1:5)
output$colrow <- renderUI({
div(selectInput("ipt_col", label = "Col",
choices = cols, # no need to wrap with c()
selected = cols[1],
width = "50%"),
selectInput("ipt_row", label = "Row",
choices = rows,
selected = rows[1],
width = "50%"),
selectInput("ipt_vlr", label = "Value",
choices = values,
selected = ""),
actionButton("bt_ok", "ok")
)
})
colrow_vlr <- eventReactive(input$bt_ok, {
as.data.frame(matrix(input$ipt_vlr, 1,1, dimnames = list(input$ipt_row,input$ipt_col)))
})
output$result <- DT::renderDataTable({
colrow_vlr()
})
}
shinyApp(ui = ui, server = server)
To a 3 year old post
ggplot2: facet_wrap strip color based on variable in data set
Baptiste has given the following solution:
d <- data.frame(fruit = rep(c("apple", "orange", "plum", "banana", "pear", "grape")),
farm = rep(c(0,1,3,6,9,12), each=6),
weight = rnorm(36, 10000, 2500),
size=rep(c("small", "large")))
p1 = ggplot(data = d, aes(x = farm, y = weight)) +
geom_jitter(position = position_jitter(width = 0.3),
aes(color = factor(farm)), size = 2.5, alpha = 1) +
facet_wrap(~fruit)
dummy <- ggplot(data = d, aes(x = farm, y = weight))+ facet_wrap(~fruit) +
geom_rect(aes(fill=size), xmin=-Inf, xmax=Inf, ymin=-Inf, ymax=Inf) +
theme_minimal()
library(gtable)
g1 <- ggplotGrob(p1)
g2 <- ggplotGrob(dummy)
gtable_select <- function (x, ...)
{
matches <- c(...)
x$layout <- x$layout[matches, , drop = FALSE]
x$grobs <- x$grobs[matches]
x
}
panels <- grepl(pattern="panel", g2$layout$name)
strips <- grepl(pattern="strip-t", g2$layout$name)
g2$layout$t[panels] <- g2$layout$t[panels] - 1
g2$layout$b[panels] <- g2$layout$b[panels] - 1
new_strips <- gtable_select(g2, panels | strips)
library(grid)
grid.newpage()
grid.draw(new_strips)
gtable_stack <- function(g1, g2){
g1$grobs <- c(g1$grobs, g2$grobs)
g1$layout <- transform(g1$layout, z= z-max(z), name="g2")
g1$layout <- rbind(g1$layout, g2$layout)
g1
}
## ideally you'd remove the old strips, for now they're just covered
new_plot <- gtable_stack(g1, new_strips)
grid.newpage()
grid.draw(new_plot)
(I have just updated the "strip-t" pattern and opened the grid library as it was suggested in the old post)
I repost this because it's an old brillant stuff and I want to use it myself for a presentation.
I'm a beginner in ggplot and this could also help me for various scripts.
Here are my questions :
- How is it possible to choose the color and not to give the same blue and red please? In my script, I have 3 colors to set, and I hope it can be less agressive. Is it possible to do it ?
- Another question, is it possible to integrate this in the legend, i.e to know what are this colors refering ?
Many thanks
you can change the strip colours with the fill scale in the dummy plot. Combining the legends is a bit tricky, but here's a starting point.
library(ggplot2)
library(gtable)
library(gridExtra)
library(grid)
gtable_stack <- function(g1, g2){
g1$grobs <- c(g1$grobs, g2$grobs)
g1$layout <- transform(g1$layout, z= z-max(z), name="g2")
g1$layout <- rbind(g1$layout, g2$layout)
g1
}
gtable_select <- function (x, ...)
{
matches <- c(...)
x$layout <- x$layout[matches, , drop = FALSE]
x$grobs <- x$grobs[matches]
x
}
d <- data.frame(fruit = rep(c("apple", "orange", "plum", "banana", "pear", "grape")),
farm = rep(c(0,1,3,6,9,12), each=6),
weight = rnorm(36, 10000, 2500),
size=rep(c("small", "large")))
p1 = ggplot(data = d, aes(x = farm, y = weight)) +
geom_jitter(position = position_jitter(width = 0.3),
aes(color = factor(farm)), size = 2.5, alpha = 1) +
facet_wrap(~fruit)
dummy <- ggplot(data = d, aes(x = farm, y = weight))+ facet_wrap(~fruit) +
geom_rect(aes(fill=size), xmin=-Inf, xmax=Inf, ymin=-Inf, ymax=Inf) +
theme_minimal() + scale_fill_brewer(palette = "Pastel2")
g1 <- ggplotGrob(p1)
g2 <- ggplotGrob(dummy)
# extract legends
leg <- g1$grobs[[grep("guide-box", g1$layout$name)]]
dummy_leg <- g2$grobs[[grep("guide-box", g2$layout$name)]]
combined_leg <- rbind.gtable(leg, dummy_leg)
g1$grobs[[grep("guide-box", g1$layout$name)]] <- combined_leg
# move dummy panels one cell up
panels <- grepl(pattern="panel", g2$layout$name)
strips <- grepl(pattern="strip-t", g2$layout$name)
g2$layout$t[panels] <- g2$layout$t[panels] - 1
g2$layout$b[panels] <- g2$layout$b[panels] - 1
new_strips <- gtable_select(g2, panels | strips)
# stack new strips on top of gtable
# ideally you'd remove the old strips, for now they're just covered
new_plot <- gtable_stack(g1, new_strips)
grid.newpage()
grid.draw(new_plot)