rhandsontable in shiny: change separator of thousands and decimals - r

I would like to know how to change the thousand separator to a point and the decimal separator to a comma when using the rhandsontable function.
Here's a small, reproducible example.
library(tidyverse)
library(shiny)
library(shinydashboard)
library(rhandsontable)
data_test <- iris
ui <- dashboardPage(
skin = "black",
dashboardHeader(
title = "Test",
titleWidth = 100
),
dashboardSidebar(collapsed = TRUE),
dashboardBody(
fluidRow(column(
width = 3,
selectInput(
inputId = "specie",
label = "Specie",
choices = unique(data_test$Species),
multiple = FALSE
)),
rHandsontableOutput("rTable")))
)
server <- function(input, output, session) {
rv <- reactiveValues(table1 = NULL)
observeEvent(input$specie,{
data <- data_test %>%
filter(Species == input$specie) %>%
mutate(Sepal.Length2 = 0,
Sepal.Width2 = 0,
Petal.Length2 = 0,
Petal.Width2 = 0,
amount = 50,
percentage = 100) %>%
select(1:4,6:11)
rv$table1<- data})
observe({
if (!is.null(input$rTable)){
mytable <- as.data.frame(hot_to_r(input$rTable))
mytable[,7] <- mytable[,5]*100
mytable[,8] <- mytable[,6]*100
numberofrows <- nrow(mytable)
rv$table1 <- mytable}
})
output$rTable <- renderRHandsontable({
rhandsontable(rv$table1) %>%
hot_col("Sepal.Length", format = "0.0,0") %>%
hot_col("Sepal.Width", format = "0.0,0") %>%
hot_col("Petal.Length", format = "0.0,0") %>%
hot_col("Petal.Width", format = "0.0,0") %>%
hot_col("Sepal.Length2", format = "0.0,0") %>%
hot_col("Sepal.Width2", format = "0.0,0") %>%
hot_col("Petal.Length2", format = "0.0,0") %>%
hot_col("Petal.Width2", format = "0.0,0") %>%
hot_col("amount", format = "$0.0,0") %>%
hot_col("percentage", format = "0,0") %>%
hot_cols(colWidths = 130)
})
}
shinyApp(ui = ui, server=server)
I tried the hot_col functions as seen in the example but this doesn't solve my problem, I also tried other functions like prettyNum, format, formatC, etc but I couldn't solve it either.
Any help is much appreciated.

I would use the d3.format library, as follows:
library(rhandsontable)
library(shiny)
mydata <- as.data.frame(
matrix(runif(40, 0, 100000), nrow = 10, ncol = 4)
)
ui <- fluidPage(
tags$head(
tags$script(src = "https://cdn.jsdelivr.net/npm/d3-format#3")
),
rHandsontableOutput("mytable")
)
server <- function(input, output) {
output$mytable <- renderRHandsontable({
rhandsontable(mydata,rowHeaderWidth = 100)%>%
hot_cols(
renderer = 'function(instance, td, row, col, prop, value, cellProperties) {
Handsontable.renderers.NumericRenderer.apply(this, arguments);
var locale = d3.formatLocale({
decimal: ",",
thousands: ".",
grouping: [3]
});
var fformat = locale.format(",");
td.innerHTML = fformat(value);
}')
})
}
shinyApp(ui,server)

Related

How to copy multiple row and column headers in a rendered table when using DT table copy function?

A similar question was posted but never answered: r shiny problem with datatable to copy a table with table head (colspan)
When running the below reproducible code, I'd like the DT "copy" button to include ALL table column and row headers, when there are multiple headers. So far DT copy only copies one header.
I have the code to do this using an action button/observeEvent() outside of DT (not shown in below code), but if possible I'd instead like to use DT's native copy clipboard function (like in the code below) because of other benefits it offers including but not limited to simplicity.
The images at the bottom better explain.
Maybe it's not possible. But maybe it is!
Reproducible code:
library(DT)
library(shiny)
library(dplyr)
library(htmltools)
library(data.table)
data <-
data.frame(
ID = c(1,1,1,2,2,2,3,3,3),
Period = c(1, 2, 3, 1, 2, 3, 1, 2, 3),
Values = c(5, 10, 15, 0, 2, 4, 3, 6, 9),
State = c("X0","X1","X2","X0","X2","X0", "X2","X1","X9")
)
numTransit <- function(x, from=1, to=3){
setDT(x)
unique_state <- unique(x$State)
all_states <- setDT(expand.grid(list(from_state = unique_state, to_state = unique_state)))
dcast(x[, .(from_state = State[from],
to_state = State[to]),
by = ID]
[,.N, c("from_state", "to_state")]
[all_states,on = c("from_state", "to_state")],
to_state ~ from_state, value.var = "N"
)
}
ui <- fluidPage(
tags$head(tags$style(".datatables .display {margin-left: 0;}")),
h4(strong("Transition table inputs:")),
numericInput("transFrom", "From period:", 1, min = 1, max = 3),
numericInput("transTo", "To period:", 2, min = 1, max = 3),
h4(strong("Output transition table:")),
DTOutput("resultsDT"),
)
server <- function(input, output, session) {
results <-
reactive({
results <- numTransit(data, input$transFrom, input$transTo) %>%
replace(is.na(.), 0) %>%
bind_rows(summarise_all(., ~(if(is.numeric(.)) sum(.) else "Sum")))
results <- cbind(results, Sum = rowSums(results[,-1]))
})
output$data <- renderTable(data)
output$resultsDT <- renderDT(server=FALSE, {
datatable(
data = results(),
rownames = FALSE,
extensions = c("Buttons", "Select"), # for Copy button
selection = 'none', # for Copy button
filter = 'none',
container = tags$table(
class = 'display',
tags$thead(
tags$tr(
tags$th(rowspan = 2,sprintf('To state where end period = %s',input$transTo),style="border-right: solid 1px;"),
tags$th(colspan = 10,sprintf('From state where initial period = %s', input$transFrom))),
tags$tr(mapply(tags$th, colnames(results())[-1],
style = sprintf("border-right: solid %spx;", rep(0, ncol(results()) - 1L)),
SIMPLIFY = FALSE))
)
),
options = list(scrollX = F,
buttons = list(list(extend = "copy",text = 'Copy',exportOptions = list(modifier = list(selected = TRUE)))), # for Copy button
dom = 'Bft', # added 'B' for Copy button
lengthChange = T,
pagingType = "numbers",
autoWidth = T,
info = FALSE,
searching = FALSE)
) %>%formatStyle(c(1), `border-right` = "solid 1px")
})
}
shinyApp(ui, server)
Additional example:
Below is another, simpler example of trying to copy/paste all headers using DT, starting with the example used in post How to copy tableOutput to clipboard? (however adding the "sketch" container to datatable for a second column header to illustrate the copy/paste issue I'm trying to address):
library(shiny)
library(dplyr)
library(DT)
library(htmltools)
df <- mtcars
one <- function(.data, var, na = TRUE) {
return({
.data %>%
group_by(.data[[var]]) %>%
filter(!is.na(.data[[var]])) %>%
tally() %>%
mutate(`%` = 100*n/sum(n))
})
}
# ADDED SKETCH TO ORIGINAL EXAMPLE:
sketch = htmltools::withTags(table(
class = 'display',
thead(tr(th(colspan = 3, 'Table')),
tr(lapply(c('Variable','n','%'),th))
)
))
ui <- fluidPage(
selectInput("var", label = "Select Variable", choices = c("", names(df))),
DTOutput("valu", width = "15%")
)
server <- function(input, output) {
output$valu <- renderDT({
if(input$var != '') {
data <- df %>% one(input$var, na = input$check)
DT::datatable(data,
class = 'cell-border stripe',
rownames = FALSE,
extensions = c("Buttons", "Select"),
selection = 'none',
container = sketch, # ADDED SKETCH CONTAINER TO ORIGINAL EXAMPLE
options =
list(
select = TRUE,
dom = "Bt",
buttons = list(
list(
extend = "copy",
text = 'Copy'))
)) %>% formatStyle(
0,
target = "row",
fontWeight = styleEqual(1, "bold")
)
}
}, server = FALSE)
output$value <- renderTable({
if(input$var != '') {
data <- df %>% one(input$var, na = input$check)
return(data)
}
}, spacing = "xs", bordered = TRUE)
}
shinyApp(ui, server)
Hmm... for Copy I don't know yet. But you can export such a table to Excel and then copy from Excel. I agree this is not highly convenient, but I don't know another way. This requires some JS libraries:
tags$script(src = "xlsx.core.min.js"), # https://github.com/SheetJS/sheetjs/blob/master/dist/xlsx.core.min.js
tags$script(src = "FileSaver.min.js"), # https://raw.githubusercontent.com/eligrey/FileSaver.js/master/dist/FileSaver.min.js
tags$script(src = "tableexport.min.js"), # https://github.com/clarketm/TableExport/tree/master/dist
tags$link(rel = "stylesheet", href = "tableexport.min.css")
library(shiny)
library(DT)
library(shinyjs)
js_export <-
"
var $table = $('#DTtable').find('table');
var instance = $table.tableExport({
formats: ['xlsx'],
exportButtons: false,
filename: 'myTable',
sheetname: 'Sheet1'
});
var exportData0 = instance.getExportData();
var exportData = exportData0[Object.keys(exportData0)[0]]['xlsx'];
instance.export2file(exportData.data, exportData.mimeType, exportData.filename,
exportData.fileExtension, exportData.merges,
exportData.RTL, exportData.sheetname);
"
ui <- fluidPage(
useShinyjs(),
tags$head(
# put these files in the www subfolder
tags$script(src = "xlsx.core.min.js"),
tags$script(src = "FileSaver.min.js"),
tags$script(src = "tableexport.min.js")
),
DTOutput("DTtable"),
actionButton("export", "Export table", class = "btn-primary")
)
sketch <- htmltools::withTags(table(
class = "display",
thead(
tr(
th(rowspan = 2, "Species"),
th(colspan = 2, "Sepal"),
th(colspan = 2, "Petal")
),
tr(
lapply(rep(c("Length", "Width"), 2), th)
)
)
))
server <- function(input, output, session){
output[["DTtable"]] <- renderDT({
datatable(
head(iris, 6),
container = sketch, rownames = FALSE
) %>%
formatPercentage("Sepal.Length") %>%
formatCurrency("Sepal.Width")
})
observeEvent(input[["export"]], {
runjs(js_export)
})
}
shinyApp(ui, server)
Note that it also takes the formatting into account, but I'm wondering why there are some dates :-/

R shiny: How to copy data derived from plotly_selection events into a data frame/table and update each time by pressing an actionButton?

I'm putting together a shiny app to play around with some athlete GPS data. Essentially, I'm looking to structure my script so that each time the user selects an area of interest on the plotly plot and the "Add" actionButton is clicked, the table below will add the calculated Start_time, Time_at_peak, Max_velocity, Time_to_peak, and Distance_to_peak values.
The issue can be seen in the GIF below: - Once the area of interest is selected and the "Add" button clicked, the first values seem correct. However, when the user selects a second area of interest to add to the table, it overwrites the initial entry and will keep overwriting each time a new selection is made. This is seemingly because because the code is inside the observeEvent(event_data("plotly_selected"), which, confusingly, it needs to be in order to calculate the variables of interest.
I'm currently a little stumped and can't seem to find any relevant information. As such, any guidance would be greatly appreciated!
Here is a we transfer link to some test data that can be uploaded to the app: https://wetransfer.com/downloads/5a7c5da5a7647bdbe133eb3fdac79c6b20211119052848/afe3e5
library(shiny)
library(readr)
library(DT)
library(dplyr)
library(plotly)
library(lubridate)
library(tidyr)
library(purrr)
library(htmlwidgets)
library(shinydashboard)
library(dashboardthemes)
library(shinyjs)
x_df <- data.frame(Start_time = character(1), Time_at_peak = character(1), Max_velocity = integer(1),
Time_to_peak = integer(1), Distance_to_peak = integer(1))
x_df$Start_time <- as.character("0:00:00.0")
x_df$Time_at_peak <- as.character("0:00:00.0")
x_df$Max_velocity <- as.integer(0)
x_df$Time_to_peak <- as.integer(0)
x_df$Distance_to_peak <- as.integer(0)
runApp(shinyApp(
ui=(fluidPage(
titlePanel("Event to Table"),
mainPanel(
fileInput(
inputId = "filedata",
label = "Upload data file (.csv)",
accept = c(".csv")),
plotlyOutput('myPlot'),br(),br(),br(),br(),
DTOutput("testing"), br(), br(),
fluidRow(
valueBoxOutput("starttime", width = 2),
valueBoxOutput("endtime", width = 2),
valueBoxOutput("maxvelocity", width = 2),
valueBoxOutput("timediff", width = 3),
valueBoxOutput("distance", width = 3)
),
useShinyjs(),
fluidRow(
div(style = "text-align:center", actionButton("Add", "Add Data to Table"),
downloadButton("export", "Export Table as .CSV"))), br(),
DTOutput(outputId = "table")))
),
server = (function(input, output, session) {
data<-reactive({
req(input$filedata)
read.csv(input$filedata$datapath, header = TRUE)%>%
rename(Velocity = 'Speed..m.s.',
Player = 'Player.Display.Name',
Latitude = 'Lat',
Longtitude = 'Lon',
AccelImpulse = 'Instantaneous.Acceleration.Impulse',
HeartRate = 'Heart.Rate..bpm.')
})
observe({
thedata<-data()
updateSelectInput(session, 'y', choices = names(data))
})
output$myPlot = renderPlotly({
plot_ly(data = data(), x = ~Time, y = ~Velocity, height = 450,
marker =list(color = 'rgb(132,179,202)', size = 0.1),
line = list(color = 'rgb(132,179,202)', size = 0.1, width = 0.9),
type = 'scatter', mode = 'markers+lines') %>%
layout(dragmode = "select",
showlegend = F,
title = list(text = 'Velocity Trace', font = list(size = 20)),
xaxis = list(title = list(text = "", standoff = 0), nticks = 10),
yaxis = list(title = list(text = "Velocity (m/s)"), nticks = 5, gridcolor = "#46505a"),
font = list(color = 'black'),
margin = list(t = 70))
})
observeEvent(event_data("plotly_selected"), {
event.data <- event_data("plotly_selected")
if (max(event.data$y) < 1.5) {
maxvel <- (max(event.data$y))
maxpos <- match(maxvel, event.data$y)
}
else {
filter1 <- filter (event.data, event.data$y > 1.5)
maxvel <- (max(filter1$y))
maxpos <- match(maxvel, event.data$y)
}
zero_val <- function(x) x == 0
zero_index <- event.data$y[1:maxpos] %>% detect_index(zero_val, .dir = "backward")
if (zero_index==0) {starttime <- event.data$x[1]}
else {starttime <- event.data$x[zero_index]}
endvel <- which.max(event.data$y)
endtime <- event.data$x[endvel]
timediff <- paste(today(), endtime) %>% as_datetime() - paste(today(), starttime) %>% as_datetime()
sprint <- as_tibble(event.data$y[zero_index:endvel])
ms <- as_tibble(rep(0.1, count(sprint)))
time_vel <- cbind(ms, sprint)
distance <- sum(time_vel[1]*time_vel[2])
sprintselect <- as_tibble(cbind(Start_time = starttime,
Time_at_peak = endtime,
Max_velocity = round(maxvel, 2),
Time_to_peak = round(timediff, 1),
Distance_to_peak = round(distance, 1)))
values <- reactiveValues()
values$df <- x_df
addData <- observe({
if(input$Add > 0) {
newLine <- isolate(data.frame(Start_time = sprintselect$Start_time, Time_at_peak = sprintselect$Time_at_peak,
Max_velocity = sprintselect$Max_velocity,
Time_to_peak = sprintselect$Time_to_peak,
Distance_to_peak = sprintselect$Distance_to_peak,
stringsAsFactors= FALSE))
values$df <- isolate(rbind(values$df, newLine))}
})
output$testing <- renderDataTable({values$df})
})
})
))
I've managed to figure it out and thought I'd post an answer rather than delete the question - just in case someone out there is looking to do a similar thing and they are unsure how to do it.
Firstly, I removed the pre-populated table x_df from the beginning - it was no longer required.
Although I thought the code needed to sit inside the observeEvent(event_data("plotly_selected") to function correctly, it did not - thankfully, because that was at the root of the issue. Instead, I used observeEvent(input$Add, { (which is the correct code to use as opposed to if(input$Add > 0)) to anchor the event to the click of the Add button.
The values <- reactiveValues() was placed outside the observeEvent() and an IF statement was used to either add the data to the values$df data frame on it's own if it was the first selection, or bind it to the existing saved data.
Here's the new code and a GIF demonstrating.
library(shiny)
library(readr)
library(DT)
library(dplyr)
library(plotly)
library(lubridate)
library(tidyr)
library(purrr)
library(htmlwidgets)
library(shinydashboard)
library(dashboardthemes)
library(shinyjs)
runApp(shinyApp(
ui=(fluidPage(
titlePanel("Event to Table"),
mainPanel(
fileInput(
inputId = "filedata",
label = "Upload data file (.csv)",
accept = c(".csv")),
plotlyOutput('myPlot'),br(),br(),br(),br(),
DTOutput("testing"), br(), br(),
fluidRow(
valueBoxOutput("starttime", width = 2),
valueBoxOutput("endtime", width = 2),
valueBoxOutput("maxvelocity", width = 2),
valueBoxOutput("timediff", width = 3),
valueBoxOutput("distance", width = 3)
),
useShinyjs(),
fluidRow(
div(style = "text-align:center", actionButton("Add", "Add Data to Table"),
downloadButton("export", "Export Table as .CSV"))), br(),
DTOutput(outputId = "table")))
),
server = (function(input, output, session) {
values <- reactiveValues(df_data = NULL)
data<-reactive({
req(input$filedata)
read.csv(input$filedata$datapath, header = TRUE)%>%
rename(Velocity = 'Speed..m.s.',
Player = 'Player.Display.Name',
Latitude = 'Lat',
Longtitude = 'Lon',
AccelImpulse = 'Instantaneous.Acceleration.Impulse',
HeartRate = 'Heart.Rate..bpm.')
})
observe({
thedata<-data()
updateSelectInput(session, 'y', choices = names(data))
})
output$myPlot = renderPlotly({
plot_ly(data = data(), x = ~Time, y = ~Velocity, height = 450,
marker =list(color = 'rgb(132,179,202)', size = 0.1),
line = list(color = 'rgb(132,179,202)', size = 0.1, width = 0.9),
type = 'scatter', mode = 'markers+lines') %>%
layout(dragmode = "select",
showlegend = F,
title = list(text = 'Velocity Trace', font = list(size = 20)),
xaxis = list(title = list(text = "", standoff = 0), nticks = 10),
yaxis = list(title = list(text = "Velocity (m/s)"), nticks = 5, gridcolor = "#46505a"),
font = list(color = 'black'),
margin = list(t = 70))
})
observeEvent(input$Add, {
event.data <- event_data("plotly_selected")
if (max(event.data$y) < 1.5) {
maxvel <- (max(event.data$y))
maxpos <- match(maxvel, event.data$y)
}
else {
filter1 <- filter (event.data, event.data$y > 1.5)
maxvel <- (max(filter1$y))
maxpos <- match(maxvel, event.data$y)
}
zero_val <- function(x) x == 0
zero_index <- event.data$y[1:maxpos] %>% detect_index(zero_val, .dir = "backward")
if (zero_index==0) {starttime <- event.data$x[1]}
else {starttime <- event.data$x[zero_index]}
endvel <- which.max(event.data$y)
endtime <- event.data$x[endvel]
timediff <- paste(today(), endtime) %>% as_datetime() - paste(today(), starttime) %>% as_datetime()
sprint <- as_tibble(event.data$y[zero_index:endvel])
ms <- as_tibble(rep(0.1, count(sprint)))
time_vel <- cbind(ms, sprint)
distance <- sum(time_vel[1]*time_vel[2])
sprintselect <- as_tibble(cbind(Start_time = starttime,
Time_at_peak = endtime,
Max_velocity = round(maxvel, 2),
Time_to_peak = round(timediff, 1),
Distance_to_peak = round(distance, 1)))
newLine <- isolate(data.frame(Start_time = sprintselect$Start_time, Time_at_peak = sprintselect$Time_at_peak,
Max_velocity = sprintselect$Max_velocity,
Time_to_peak = sprintselect$Time_to_peak,
Distance_to_peak = sprintselect$Distance_to_peak,
stringsAsFactors= FALSE))
if (is.null(values$df)){
values$df <- newLine}
else {
values$df <- isolate(rbind(values$df, newLine))}
output$testing <- renderDataTable({values$df})
})
})
))

How to copy tableOutput to clipboard?

I'm trying to copy the table output to the clipboard on a click of a button. I tried looking into the rclipboard package, but it doesn't appear to be able to copy output, in my limited understanding.
I added an actionButton with an icon to the screenshot to show what I'm trying to achieve. Right now the button doesn't do anything.
Code:
library(shiny)
library(dplyr)
df <- mtcars
one <- function(.data, var, na = TRUE) {
return({
.data %>%
group_by(.data[[var]]) %>%
filter(!is.na(.data[[var]])) %>%
tally() %>%
mutate(`%` = 100*n/sum(n))
})
}
ui <- fluidPage(
selectInput("var", label = "Select Variable", choices = c("", names(df))),
tableOutput("value")
)
server <- function(input, output) {
output$value <- renderTable({
if(input$var != '') {
data <- df %>% one(input$var, na = input$check)
return(data)
}
}, spacing = "xs", bordered = TRUE)
}
shinyApp(ui, server)
Perhaps you can use copy button from DT to copy the whole table. You can also copy only selected rows. Try this
library(shiny)
library(dplyr)
library(DT)
df <- mtcars
one <- function(.data, var, na = TRUE) {
return({
.data %>%
group_by(.data[[var]]) %>%
filter(!is.na(.data[[var]])) %>%
tally() %>%
mutate(`%` = 100*n/sum(n))
})
}
ui <- fluidPage(
selectInput("var", label = "Select Variable", choices = c("", names(df))),
DTOutput("valu", width = "15%")
#tableOutput("value")
)
server <- function(input, output) {
output$valu <- renderDT({
if(input$var != '') {
data <- df %>% one(input$var, na = input$check)
DT::datatable(data,
class = 'cell-border stripe',
rownames = FALSE,
extensions = c("Buttons", "Select"),
selection = 'none',
options =
list(
select = TRUE,
dom = "Bt", ## remove f to remove search ## Brftip
buttons = list(
list(
extend = "copy",
text = 'Copy'#,
#exportOptions = list(modifier = list(selected = TRUE))
)
)
)) %>% formatStyle(
0,
target = "row",
fontWeight = styleEqual(1, "bold")
)
}
}, server = FALSE)
output$value <- renderTable({
if(input$var != '') {
data <- df %>% one(input$var, na = input$check)
return(data)
}
}, spacing = "xs", bordered = TRUE)
}
shinyApp(ui, server)

Upload a file and then geocode the addresses in shiny app

Error while geocoding addresses in my shiny app
I wish to upload a file in my shiny app and and then calculate latitude and longitude.Below is the code and here is the LINK(https://github.com/Pujaguptagithub/My_Data) to the dataset used.Please help as I am new to shiny.
library(shiny)
library(dplyr)
library(readxl)
library(sf)
library(mapsapi)
library(gsubfn)
library(pipeR)
ui <- fluidPage(
fileInput('csvFile', 'Choose xlsx file',
accept = c(".xlsx")),
tableOutput("rawData"),
tableOutput("modifiedData")
)
server <- function(input, output, session) {
rawData <- eventReactive(input$csvFile, {
read_excel(input$csvFile$datapath)
})
output$rawData <- renderTable({
rawData() %>% head
})
output$modifiedData <- renderTable({
rawData() %>% mutate(Locations = paste(as.character(rawData()$Address),
as.character(rawData()$City),as.character(rawData()$State),
as.character(rawData()$`Zip Code`), as.character(rawData()$Country),
sep=",")) %>%
mutate(aaa = gsub("NA;", "", Locations)) %>%
mutate(bbbb = mp_geocode(addresses = aaa, region = NULL, bounds = NULL,
key = "AIzaSyBQDna1fNBT5qeET39A0lp9nNEdezRLVyI")) %>%
mutate(ccc = mp_get_points(bbbb)) %>%
mutate(pnt = sub(ccc$pnt, pattern = "c", replacement = "")) %>%
mutate(eee = sub(pnt, pattern = "[(]", replacement = "")) %>%
mutate(ffff = sub(eee, pattern = "[)]", replacement = "")) %>%
mutate(gggg = sub(ffff, pattern = ",", replacement = "")) %>%
mutate(hhh = unlist(strsplit(gggg, split = " "))) %>%
mutate(Latitude = as.numeric(hhh[seq(2, length(hhh), 2)])) %>%
mutate(Longitude = as.numeric(hhh[seq(1, length(hhh), 2)]))
})
}
shinyApp(ui, server)
The below code works perfect outside the shiny :
Locations <- paste(Latlong$Address, Latlong$City,Latlong$State,Latlong$`Zip
Code`, Latlong$Country, sep=",")
Locations <- gsub("NA;", "", Locations)
Locations <- mp_geocode(addresses = Locations, region = NULL, bounds =
NULL, key = "AIzaSyBQDna1fNBT5qeET39A0lp9nNEdezRLVyI")
Locations = mp_get_points(Locations)
geom <- sub(Locations$pnt, pattern = "c", replacement = "")
geom <- sub(geom, pattern = "[(]", replacement = "")
geom <- sub(geom, pattern = "[)]", replacement = "")
geom <- sub(geom, pattern = ",", replacement = "")
lonlat <- unlist(strsplit(geom, split = " "))
Latlong$Latitude <- as.numeric(lonlat[seq(2, length(lonlat), 2)])
Latlong$Longitude <- as.numeric(lonlat[seq(1, length(lonlat), 2)])
check my entire app below, the only problem is due to line "df_svb <- Latlong", please help to get rid off the error.
library(shinyjs)
library(shinyWidgets)
library(shiny)
library(shinydashboard)
library(tidyverse)
library(devtools)
library(rsconnect)
library(readxl)
library(DT)
library(writexl)
library(stringi)
library(shinydashboardPlus)
library(ggmap)
library(zipcode)
library(leaflet)
library(htmltools)
library(data.table)
library(plotly)
library(mapsapi)
library(readxl)
Template <- read_excel("C:/Users/Template.xlsx")
header <- dashboardHeader(
# Set height of dashboardHeader
tags$li(class = "dropdown",
tags$style(".main-header .logo {height: 0px;}")),
title = div(img(src = 'svb_small.png',
style = "position:absolute; left:15px;
height: 80px;"))
)
##### Sidebar
sidebar <- dashboardSidebar(
shinyjs::useShinyjs(),
width = 400,
menuItem('Inputs',
id = 'side_panel',
#icon = icon("bar-chart-o"),
startExpanded = TRUE,
br(), br(),
fileInput('csvFile', 'Choose xlsx file',
accept = c(".xlsx")),
div(style = "font-size: 150%; font-family: sans-serif;",
selectizeGroupUI(
id = "my_filters",
params = list(
Country = list(inputId = "Country", title = "Country:"),
Company = list(inputId = "Company", title = "Company:")),
inline = FALSE)),
br(),
br(),
br(),
br(),
br(),
br(),
br(),
br(),
br(),
br(),
br(),
br(),
br(),
br(),
br(),
br(),
downloadBttn('downloadData',
label = 'Download Template',
style = "gradient",
color = "primary"
)
)
)
body <- dashboardBody(
tags$style(type = "text/css", "#map_1 {height: calc(100vh - 80px)
!important;}"),
addSpinner(
leafletOutput("map_1"),
spin = 'folding-cube')
)
# Put them together into a dashboardPage
ui <- dashboardPage(header,sidebar,body, skin = "black")
options(shiny.maxRequestSize = 15*1024^2)
server <- function(input, output, session) {
rawData <- eventReactive(input$csvFile, {
read_excel(input$csvFile$datapath)
})
# Download template
output$downloadData <- downloadHandler(
filename = function() {"CBRE Geocoding and mapping Application.xlsx"},
content = function(file) {write_xlsx(Template, path = file)}
)
#SelectizeGroup function creates mutually dependent input filters
res_mod <- callModule(
module = selectizeGroupServer,
id = "my_filters",
data = df_svb,
vars = c('Country', 'Company')
)
modifiedData <- renderTable({
Latlong <- rawData()
Locations <- paste(Latlong$Address,
Latlong$City,Latlong$State,Latlong$`Zip Code`,
Latlong$Country, sep=",")
Locations <- gsub("NA;", "", Locations)
Locations <- mp_geocode(addresses = Locations, region = NULL, bounds=
NULL, key =
"AIzaSyBQDna1fNBT5qeET39A0lp9nNEdezRLVyI")
Locations = mp_get_points(Locations)
geom <- sub(Locations$pnt, pattern = "c", replacement = "")
geom <- sub(geom, pattern = "[(]", replacement = "")
geom <- sub(geom, pattern = "[)]", replacement = "")
geom <- sub(geom, pattern = ",", replacement = "")
lonlat <- unlist(strsplit(geom, split = " "))
Latlong$Latitude <- as.numeric(lonlat[seq(2, length(lonlat), 2)])
Latlong$Longitude <- as.numeric(lonlat[seq(1, length(lonlat), 2)])
Latlong
})
############################################################
df_svb <- Latlong
df_svb <- Latlong%>% mutate(
X = paste0('<font color="#006A4D">',
'<font-family: sans-serif>',
'<font size = "5">',
'<strong><font color="black">Country: </font color="black">
</strong>',
Country,
'<br><strong><font color="black">Company: </font color="black">
</strong>',
Company))
qpal <- colorFactor("BuPu", as.factor(df_svb$Company))
output$map_1 <- renderLeaflet(
leaflet(data = res_mod()) %>%
setView(-94.578568, 39.099728, zoom = 5) %>%
addProviderTiles(providers$Esri.WorldImagery, group = "Imagery Map") %>%
addProviderTiles(providers$Esri.WorldStreetMap, group = 'Street Map') %>%
addCircleMarkers(~Longitude, ~Latitude, group = 'svb',
fillColor = ~qpal(res_mod()$Company),
color = c("#006A4D","#FF0000"),
stroke = FALSE,
fillOpacity = 15,radius = 15,
labelOptions = labelOptions(noHide = T)
) %>%
addLayersControl(baseGroups = c('Street Map', "Imagery Map"),
options = layersControlOptions(collapsed = TRUE)) %>%
hideGroup('CBRE Locations') %>%
addLegend("topright", pal = qpal, values = ~res_mod()$Company,
title = "Company:", opacity = 1,group = 'svb' )
)
#Zooms in map when 1 office is chosen.
observe({
req(n_distinct(res_mod()$Country) == 1)
proxy <- leafletProxy('map_1')
proxy %>% setView(head(res_mod()$Longitude,1),
head(res_mod()$Latitude,1), zoom = 12)
})
}
shinyApp(ui, server)
UPDATE:
To add the data as a map, add this to the UI definition:
leafletOutput(outputId="myMap", height = 480)
And this will guide you on creating the server function:
output$myMap <- renderLeaflet({
# Test Data
#name <- c("London","Paris","Dublin")
#latitude <- c(51.5074,48.8566, 53.3498)
#longitude <- c(0.1278,2.3522, -6.2603)
#Latlong <- data.frame(name, latitude, longitude)
# Convert data frame to shape
coordinates(Latlong)<-~longitude+latitude
proj4string(Latlong)<- CRS("+proj=longlat +datum=WGS84")
shapeData <- spTransform(data,CRS("+proj=longlat"))
# Map the shape
map <- tm_shape(shapeData, name="Cities") +
tm_dots(size=0.2,title="Cities") +
tm_basemap("OpenStreetMap")+
tm_basemap("Esri.WorldImagery")
tmap_leaflet(map)
})
Original:
The issue seems to be in your call to the geocode function mp_get_points(). This is returning an xml document that can't be inserted into the new dataframe column ccc.
Is there any reason why you abandoned your original code? This seems to work fine if I insert it into your shiny app.
output$modifiedData <- renderTable({
Latlong <- rawData()
Locations <- paste(Latlong$Address, Latlong$City,Latlong$State,Latlong$`Zip
Code`, Latlong$Country, sep=",")
Locations <- gsub("NA;", "", Locations)
Locations <- mp_geocode(addresses = Locations, region = NULL, bounds =
NULL, key = "AIzaSyBQDna1fNBT5qeET39A0lp9nNEdezRLVyI")
Locations = mp_get_points(Locations)
geom <- sub(Locations$pnt, pattern = "c", replacement = "")
geom <- sub(geom, pattern = "[(]", replacement = "")
geom <- sub(geom, pattern = "[)]", replacement = "")
geom <- sub(geom, pattern = ",", replacement = "")
lonlat <- unlist(strsplit(geom, split = " "))
Latlong$Latitude <- as.numeric(lonlat[seq(2, length(lonlat), 2)])
Latlong$Longitude <- as.numeric(lonlat[seq(1, length(lonlat), 2)])
Latlong
})

Disable column editing in rhandsontable?

Suppose I have the following shiny app:
library(shiny)
library(rhandsontable)
ui <- shinyUI(fluidPage(
titlePanel("Handsontable"),
sidebarLayout(
sidebarPanel(
helpText("Handsontable demo output. Column add/delete does work ",
"for tables with defined column properties, including type."),
radioButtons("useType", "Use Data Types", c("TRUE", "FALSE"))
),
mainPanel(
rHandsontableOutput("hot", width = 350)
)
)
))
server <- shinyServer(function(input, output, session) {
values = reactiveValues()
data = reactive({
if (!is.null(input$hot)) {
DF = hot_to_r(input$hot)
} else {
if (is.null(values[["DF"]]))
DF = data.frame(val = 1:10, bool = TRUE, nm = LETTERS[1:10],
dt = seq(from = Sys.Date(), by = "days", length.out = 10),
stringsAsFactors = F)
else
DF = values[["DF"]]
}
values[["DF"]] = DF
DF
})
output$hot <- renderRHandsontable({
DF = data()
if (!is.null(DF))
rhandsontable(DF, useTypes = as.logical(input$useType), stretchH = "all")
})
})
# Run the application
shinyApp(ui = ui, server = server)
How can I disable editing for the first two columns?
The whole table and individual columns can to set to readOnly to prevent the user from making changes.(http://jrowen.github.io/rhandsontable/#read-only)
library(shiny)
library(rhandsontable)
ui <- shinyUI(fluidPage(
titlePanel("Handsontable"),
sidebarLayout(
sidebarPanel(
helpText("Handsontable demo output. Column add/delete does work ",
"for tables with defined column properties, including type."),
radioButtons("useType", "Use Data Types", c("TRUE", "FALSE"))
),
mainPanel(
rHandsontableOutput("hot", width = 350)
)
)
))
server <- shinyServer(function(input, output, session) {
values = reactiveValues()
data = reactive({
if (!is.null(input$hot)) {
DF = hot_to_r(input$hot)
} else {
if (is.null(values[["DF"]]))
DF = data.frame(val = 1:10, bool = TRUE, nm = LETTERS[1:10],
dt = seq(from = Sys.Date(), by = "days", length.out = 10),
stringsAsFactors = F)
else
DF = values[["DF"]]
}
values[["DF"]] = DF
DF
})
output$hot <- renderRHandsontable({
DF = data()
if (!is.null(DF))
rhandsontable(DF, useTypes = as.logical(input$useType), stretchH = "all") %>%
hot_col("val", readOnly = TRUE) %>%
hot_col("bool",readOnly = TRUE )
})
})
# Run the application
shinyApp(ui = ui, server = server)

Resources