Use Shiny to collect data from users in Google Sheet - r

I would like to use a Shiny interface to collect data from user inputs, such as in this Medium Article
The article is written for the googlesheets package, but we now need to use googlesheets4.
I think my code will not work due to may lay of understanding of reactive elements.
#load libraries
library(shiny)
library(shinydashboard)
library(googlesheets4)
library(DT)
ui <- fluidPage(
# Define UI
ui <- fluidPage(
# App title ----
titlePanel("Seflie Feedback"),
# Sidebar layout with input and output definitions ----
sidebarLayout(
# Sidebar to demonstrate various slider options ----
sidebarPanel(
# Input: Overall Rating
sliderInput(inputId = "helpful",
label = "I think this app is helpful",
min = 1,
max = 7,
value = 3),
actionButton("submit", "Submit")
),
mainPanel(
))
)
)
server <- function(input, output, session) {
# Reactive expression to create data frame of all input values ----
sliderValues <- reactive({
usefulRating <- input$helpful
Data <- data.frame(
Value = as.character(usefulRating),
stringsAsFactors = FALSE)
})
#This will add the new row at the bottom of the dataset in Google Sheets.
observeEvent(input$submit, {
MySheet <- gs4_find() #Obtain the id for the target Sheet
MySheet <- gs4_get('https://docs.google.com/spreadsheets/d/162KTHgd3GngqjTm7Ya9AYz4_r3cyntDc7AtfhPCNHVE/edit?usp=sharing')
sheet_append(MySheet , data = Data)
})
}
shinyApp(ui = ui, server = server)
I replaced the gs4_get() with the link rather than the ID to support you in helping me. If you are not able to access the link, you can replace the link with a google sheet ID from your own sheets temporarily.
When I run the code, I see the following: Warning: Error in is.data.frame: object 'Data' not found.
When I replace the usefulRating <- input$helpful with usefulRating <- 4 or usefulRating <- 5 or some other value, the data writes to the Sheet.
Thanks for any insights :)

#load libraries
library(shiny)
library(shinydashboard)
library(googlesheets4)
library(DT)
ui <- fluidPage(
titlePanel("Seflie Feedback"),
sidebarLayout(
sidebarPanel(
#This is where a user could type feedback
textInput("feedback", "Plesae submit your feedback"),
),
#This for a user to submit the feeback they have typed
actionButton("submit", "Submit")),
mainPanel())
server <- function(input, output, session) {
textB <- reactive({
as.data.frame(input$feedback)
})
observeEvent(input$submit, {
Selfie <- gs4_get('https://docs.google.com/spreadsheets/d/162KTHgd3GngqjTm7Ya9AYz4_r3cyntDc7AtfhPCNHVE/edit?usp=sharing')
sheet_append(Selfie, data = textB())
})
}
shinyApp(ui = ui, server = server)

Related

SHINY Summarise info based on sheet selected by user after uploading file

My goal is that user uploads an Excel file. Then, the user selects which sheets wants to be summarised, after the selection has been updated. I have managed to update selectInput with the name of the sheets but I have not been able to find\understand how to summarise based on what the sheet selected by the user. Thanks for any help.
library(shiny)
library(shinythemes)
library(data.table)
library(ggplot2)
library(dplyr)
library(readxl)
not_sel <- "Not Selected"
# Define UI for application that draws a histogram
ui <- fluidPage('MAIN TITLE',
theme = shinytheme('flatly'),
tabsetPanel(
sidebarLayout(
sidebarPanel(
fileInput('files','Import File', accept = c('.csv','.xlsx'),
multiple = F),
actionButton('boton1', 'Load', icon = icon('table')),
br(),
selectInput("indices", "Select SHEET:", choices = c(not_sel))
),
mainPanel(
tabsetPanel(
tabPanel('Data',
tableOutput('tabla'),
tableOutput('cabeza')),
tabPanel('Stats',
# selectInput('var01', 'Variable to summarise', choices = c(not_sel)),
tableOutput('stats')),
)
)
)
)
)
##############
server <- function(input, output, session) {
options(shiny.maxRequestSize=10*1024^2)
df <- eventReactive(input$boton1, {
req(input$files)
if(is.null(input$files))return(NULL)
# else{
read_excel(input$files$datapath)
# }
})
# Sheets of file uploaded
sheets_name <- reactive({
if (!is.null(input$files)) {
return(excel_sheets(path = input$files$datapath))
} else {
return(NULL)
}
})
# Update inputSelector with sheet names
observeEvent(df(),{
choices <- c(sheets_name())
updateSelectInput(inputId = "indices", choices = choices)
})
# DATA Tab
## This will show the name of the file
output$tabla <- renderTable({
input$files$name
})
## This Shows the head() but it is only showing the first sheet
output$cabeza <- renderTable({
tabla <- as_tibble(bind_cols(Date = format(as.Date(df()$Date),"%Y-%m-%d"),
Close.Price = df()$Close))
head(tabla)
})
# HERE is where I do not know how to calculate based on selection
# Table for STATS
output$stats <- renderTable({
datos <- df()
Value <- c(round(mean(datos$Close,na.rm = T),2)
)
Statistic <- c("Mean")
data.table(Statistic, Value)
})
}
# Run the application
shinyApp(ui = ui, server = server)
I want to assume that by knowing how to calculate mean based on the sheet selected, I. can replicate the code for the top rows (head()) shown in the Data Panel.
If I missed a similar question asked, I would appreciate any link and I will try the solution proposed first.
As I cannot share the file, this is how the file would look:
After working with this answer I made my app work. If there is a 'cleaner'/'better' answer, I will be happy to read.
Following the recommendation in the linked answer my server ended up like this:
ui <-fluidPage{
#My UI stayed the same with the exception of adding
uiOutput("dropdownUI") #Whererever I needed to appear
}
server <- function(input, output, session) {
...ANSWER FROM THE LINK...
## STATS Tab
output$stats <- renderTable({
Values <- c(round(mean(Dat()[,2],na.rm = T),2)
)
Statistics <- c("Mean")
data.table(Statistics, Values)
})
}

How to read a csv file in Shiny?

I'm trying to create a shiny dashboard that allows the user to select a csv file. The file contains only two columns that are order number and dateCreated. I want the user to be able to in addition, select the date range that they desire and get a summary count statistic.
So far my code is as follows:
library(shiny)
library(plotly)
library(colourpicker)
library(ggplot2)
ui <- fluidPage(
titlePanel("Case Referrals"),
sidebarLayout(
sidebarPanel(
fileInput("file", "Select a file"),
sliderInput("period", "Time period observed:",
min(data()[, c('dateCreated')]), max(data()[, c('dateCreated')]),
value = c(min(data[, c('dateCreated')]),max(data()[, c('dateCreated')])))
),
mainPanel(
DT::dataTableOutput("table")
)
)
)
# Define the server logic
server <- function(input, output) {
# file input
input_file <- reactive({
if (is.null(input$file)) {
return("")
}
})
# summarizing data into counts
data <- input_file()
data <- subset(data, dateCreated >= input$period[1] & dateCreated <= input$period[2])
output$table <- DT::renderDataTable({
data
})
}
shinyApp(ui = ui, server = server)
I get an error message saying:
Error in data()[, c("dateCreated")] : incorrect number of dimensions
Can anyone help me understand what the problem might be and/or provide a better framework for doing this? And to be clear in the csv file, the createDate variable is broken down into individual days for when the order was placed.
Thank you!
I added comments to the faulty steps.
library(shiny)
ui <- fluidPage(
titlePanel("Case Referrals"),
sidebarLayout(
sidebarPanel(
fileInput("file", "Select a file"),
# you cannot call data() in your ui.
# You would have to wrap this in renderUI inside of your server and use
# uiOutput here in the ui
sliderInput("period", "Time period observed:", min = 1, max = 10, value = 5)
),
mainPanel(
DT::dataTableOutput("table")
)
)
)
# Define the server logic
server <- function(input, output) {
input_file <- reactive({
if (is.null(input$file)) {
return("")
}
# actually read the file
read.csv(file = input$file$datapath)
})
output$table <- DT::renderDataTable({
# render only if there is data available
req(input_file())
# reactives are only callable inside an reactive context like render
data <- input_file()
data <- subset(data, dateCreated >= input$period[1] & dateCreated <= input$period[2])
data
})
}
shinyApp(ui = ui, server = server)

How to update DT datatable in Shiny when within a module and the selection criteria are changed

I try to make a shiny module to present data from dataframes using the DT package. I would like to use a module to have a standard set up of DT-table options like language and others.
I want the user to be able to select different subsets of the data interactively and thereafter be able to see the data as a DT-table. The selection of the subset will be generated outside the module because I would like the subset to be available for other uses, for example to be exported to a csv-file.
This works as intended when I don't use a module for making the DT table. When I put the code inside a module, a table is produced when the app starts. But when the selection criteria are changed, the table don't update.
I have included an app illustrating the problem. Table 1 is generated without using shiny module and updates as expected when the selection changes. Table 2 is output using the module and don't update when the selection is changed.
I'm running R-studio 1.1.463, R version 3.5.2 and DT version 0.5.
require("DT")
require("shiny")
# module for presenting data using DT
showDTdataUI <- function(id) {
ns <- NS(id)
tagList(
DT::dataTableOutput(ns("table"))
)
}
showDTdata <- function(input, output, session, DTdata) {
output$table <- renderDataTable({
DT::datatable(DTdata)
})
}
# User interface
ui <-
fluidPage(
sidebarLayout(
sidebarPanel(id="DT",
width = 4,
helpText(h4("Select")),
selectInput("selectedSpecies", label = "Species",
choices = c("setosa","versicolor","virginica"),
selected = "versicolor")
),
mainPanel(
h3("Table 1. Presenting selected data from Iris" ),
DT::dataTableOutput("table"),
h5(br("")),
h3("Table 2. Presenting selected data from Iris using shiny module"),
showDTdataUI(id="testDTModule")
)
)
)
# Define server logic ----
server <- function(session, input, output) {
selectedIris <- reactive ( {
selected <- iris[which(iris$Species==input$selectedSpecies),]
selected
})
output$table <- renderDataTable({
DT::datatable(selectedIris())
})
callModule(showDTdata, id="testDTModule", DTdata=selectedIris())
}
# Run the app ----
shinyApp(ui = ui, server = server)
You have to pass the reactive conductor in showDTdata:
showDTdata <- function(input, output, session, DTdata) {
output$table <- renderDataTable({
DT::datatable(DTdata()) # not datatable(DTdata)
})
}
callModule(showDTdata, id="testDTModule", DTdata=selectedIris) # not DTdata=selectedIris()
Does this do what you want? I removed your functions and added the selection ='multiple' to table 1 (tableX) so that we can then listen to tableX_rows_selected
P.S.: I have noticed that if you first load DT and then shiny, that the whole app won't work anymore. This is a bit weird since we call all datatable functions with DT::... but, you do get a warning message that some parts of DT are masked by shiny or viceversa.
require("shiny")
require('DT')
# User interface
ui <-
fluidPage(
sidebarLayout(
sidebarPanel(id="DT",
width = 4,
helpText(h4("Select")),
selectInput("selectedSpecies", label = "Species",
choices = c("setosa","versicolor","virginica"),
selected = "versicolor")
),
mainPanel(
h3("Table 1. Presenting selected data from Iris" ),
DT::dataTableOutput("tablex"),
br(),
h3("Table 2. Presenting selected data from Iris using shiny module"),
DT::dataTableOutput("table2")
)
)
)
# Define server logic ----
server <- function(session, input, output) {
values <- reactiveValues(rowselect = numeric())
selectedIris <- reactive ( {
selected <- iris[which(iris$Species==input$selectedSpecies),]
selected
})
output$tablex <- renderDataTable({
DT::datatable(selectedIris(), selection = 'multiple')
})
IrisSelected <- reactive({
df <- iris[c(input$tablex_rows_selected), ]
df
})
output$table2 <- renderDataTable({
req(nrow(IrisSelected()) > 0)
DT::datatable( IrisSelected())
})
}
# Run the app ----
shinyApp(ui = ui, server = server)
Without knowing of the shiny module approach, I would have probably written it like a normal function. The app below works but I am curious now after seeing the answer by #Stephane what the advantages are of using callModule approach over regular function approach
require("DT")
require("shiny")
makeTable <- function(dataframe) { DT::datatable(dataframe) %>%
formatStyle(names(dataframe), background = '#fff')
}
# User interface
ui <-
fluidPage(
sidebarLayout(
sidebarPanel(id="DT",
width = 4,
helpText(h4("Select")),
selectInput("selectedSpecies", label = "Species",
choices = c("setosa","versicolor","virginica"),
selected = "versicolor")
),
mainPanel(
dataTableOutput('Table1')
)
)
)
# Define server logic ----
server <- function(session, input, output) {
selectedIris <- reactive ( {
selected <- iris[which(iris$Species==input$selectedSpecies),]
selected
})
output$Table1 <- renderDataTable(makeTable(selectedIris()))
}
# Run the app ----
shinyApp(ui = ui, server = server)

(R/SHINY) - Using selectInput to Choose (Which) Reactive Table to Display

So I have what in my head is a simple problem.
I have a selectInput. Let's call it report_select with the options "Report 1" and "Report 2" to choose from.
In addition, I have a textInput (which is used to specify an employee ID)
I have two reactives (lets call them r_one and r_two). These result in separate data based on the employee.
I have an output$table1
The goal: I want the dropdown to control WHICH of the two reactive reports to display in table1.
Note 1: The tables individually work fine. I can display one after the other without issue.
Note 2: I am using SHINY as well as tabsetpanel and tabpanel for organization
Any methodology to help with this?
METHOD 1: (Error is "Reading Objects from shionyoutput object not allowed)
library(shiny)
library(readxl)
library(dplyr)
library(tidyr)
# Globally Pull In Files
new_compdump_data <- read_xlsx("C:/temp/FILE.xlsx")
#Format Imported Data
clean_new <- subset(new_compdump_data,is.na(new_compdump_data$Term_Date))
clean_new$AIN <- as.numeric(clean_new$AIN)
clean_new$`MIP value` <- clean_new$`MIP%`*clean_new$Salary
# Begin UI
ui <- fluidPage(
titlePanel("Data Tool"),
sidebarLayout(
sidebarPanel(
selectInput(inputId = "report_select",
label = "Select a Report",
choices = c("Base Info","Stock Info")),
textInput("stock_ain","AIN")
), #End SideBarPanel
mainPanel(
tabsetPanel(
tabPanel(title="Base Info",tableOutput("table1")
)))
))
#======= SHINY - Server Section
server <- function(input, output) {
report1 <- reactive({
subset(clean_new[c(5,1,2,3)],clean_new$AIN==input$AIN)
})
report2 <- reactive({
subset(clean_new[c(5,6,7,8)],clean_new$AIN==input$AIN)
})
report_choose <- reactive({
ifelse(input$report_select=="Base Info",report1(),
ifelse(input$report_select=="Stock Info",report2()))
})
output$table1({
report_choose()
})
} #End server info
# Run the App
shinyApp(ui = ui, server = server)
METHOD 2: Error: Same as Above
Same as above but reactive for report_choose is:
report_choose <- reactive{(
switch(input$report_select,
"Base Info"=report1(),
"Stock Info"=report2())
)}
METHOD 3: (Error is "Reading Objects from shionyoutput object not allowed)
Same (section) as above but
report_choose <- reactive({
if(input$report_select=="Base Info") {
report1()
} else {
report2()
}
})
Still no dice. Any ideas or methodology?

How to run a function that gets data from inside eventReactive and plot in table?

I'm very new to shiny and am having some trouble and have been searching all day, so hopefully someone can help me. Once an action button (actionButton, on UI) is selected by a user, I would like the server script to call a function (evenReactive in server) I wrote (myfunction, see below) that uses the input items from the UI and gets the right parameters I need to run myfunction and produce a n X2 data matrix that will be plotted as a table (renderTable in server, below). The data is a n X 2 matrix.
I have some sample code below. It's not the entre code, so you will not see the UI with the inputs I am putting in my function, or the server parts associated. But, it is the part I am trying to fix. I hope that's ok. I don't need the renderText, but when I take it out I get an error. Sorry for the formatting. Copy and pasting changed it a bit.
library(shiny)
ui <- shinyUI(fluidPage
(column(4,actionButton("gobutton", "Run"),verbatimTextOutput("ntext1")),
column(4, DT::dataTableOutput("table",width = "75%"))))
library(shiny)
shinyServer(function(input, output, session)
ntext1 <- eventReactive(input$gobutton, {
if (input$gobutton==1){
data=myfunction(input$checkbox,input$dateRange)}
})
output$ntext1 <- renderText({ntext1()})
output$table <- DT::renderDataTable(DT::datatable({
data
})
))
myfunction <-function(All,date1,date2,source_cd,tran_cd,airline_list,mag_level) {
print(All); print(date1); print(date2); print(source_cd);print(tran_cd);print(airline_list);print(mag_level)
setwd("C:/Users/TRomano/Documents/Projects/TrendAnalysis/Data")
data = read.csv("Airlines.csv",header = TRUE)
return(data)
}
For this type of problem I like to make use of reactiveValues()that are designed to store data in a reactive way.
Here is a simple app (single app, not split into server & ui) that demonstrates what I think you are trying to do
library(shiny)
library(DT)
ui <- shinyUI(
fluidPage(
column(width = 4,
actionButton("gobutton", "Run")
column(width = 4,
DT::dataTableOutput("table",
width = "75%"))))
server <- shinyServer(function(input, output, session){
rv <- reactiveValues()
rv$data <- NULL
observe({ ## will 'observe' the button press
if(input$gobutton){
print("here") ## for debugging
rv$data <- myfunction() ## store the data in the reactive value
rv$data
}
})
output$table <- DT::renderDataTable({
## The data has been stored in our rv, so can just return it here
rv$data
})
})
myfunction <- function(){
data <- data.frame(id = c(1,2,3),
val = letters[1:3])
return(data)
}
shinyApp(ui, server)
library(shiny)
library(shinydashboard)
ui <- dashboardPage(
dashboardHeader(title = "Company Name"),
dashboardSidebar(sidebarMenu(
menuItem("Results Table", tabName = "ResultsTable", icon = icon
("ResultsTable")),
dashboardBody(
tabItems(
tabItem(tabName tabItem(tabName = "ResultsTable",
fluidPage(
headerPanel(
fluidRow(
column(4,
selectInput("sour",
"Source Type:",
c("All",
unique(as.character(data_source_cd)))), offset=2
),
column(4,
selectInput("tran",
"Transaction Type:",
c("All",
unique(as.character(tran_cd)))))),
# Create a new row for the table.
fluidRow(column(8, DT::dataTableOutput("table",width = "75%"),offset = 2))))))
library(shiny)
shinyServer(function(input, output, session) {
ntext1 <- eventReactive(input$gobutton, {
if (input$dateRange[2]<input$dateRange[1]){print("You selected the date range option;however, the end date entered occurs before the starting date")}else{
output$ntext1 <- renderText({print("Analysis complete...")});
observe({
if(input$gobutton){
rv$data <- myfunction() }
})
output$table <- DT::renderDataTable(DT::datatable({
data <- rv$data
if (input$sour != "All") {
data <- data[data[,5] == input$sour,]
}else{data}
if (input$tran != "All") {
data <-data[data[,6] == input$tran,]
}else{data}
}))
}})
Once an action button is selected on the main page of my dashboard(not shown), myfunction runs analysis with the inputs from the main dashboard page. On another tab, a table will show once the analysis is complete. There are drop down menus (input$tran, input$sour) that will reduce what is in the table depending on what the user selects. If there are any errors in the input, a warning of text comes up on the main dashboard page and the tab with the table will not be created until the correct inputs are selected.
The observe function allowed me to run my function and the output data of the function set to a variable I could later use to create the table (shown).
THis is my first time posting. Any questions feel free to ask.

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