我试图仅显示选中的复选框数据，以便在复选框面板上显示UI，其中前三个复选框彼此互斥（即，只能从前三个中选择一个，并且可以从中选择一个KPI的数量）复选框选项）在闪亮的应用程序，但努力解决这个问题。根据复选框中的用户选择，图表应自动更改，例如MO_ID和＆amp;之间的单独线条图。每种选择药物或制造商或药物类别垂直选择的KPI数量。我尝试在下面执行此操作是我的代码，您的帮助将受到高度赞赏
DrugData.csv
MO_ID capture_rate_high_adj NBRx_adjusted_high_share Total_adjusted_high_share TRx_baseline_low_share DrugType DrugClass MANUFACTURER date goal1completions goal
1212016 0.097167749 0.020752878 0.003667932 0.00225614 DRUG 1 ART Manufacturer5 1012016 4 goal1
1612011 0.216740195 0.041761676 0.008145028 0.004881227 DRUG 1 II Manufacturer4 1012016 10 goal2
10112016 0.679445079 0.13818709 0.033960635 0.020129843 DRUG 1 NNRTI Manufacturer3 1012016 8 goal3
512016 0.532274828 0.113680095 0.030975403 0.018364531 DRUG 2 PI Manufacturer2 1012016 13 goal5
1012015 0.541738943 0.122225515 0.036405199 0.021408197 DRUG 3 STR Manufacturer1 1012016 6 goal4
1012015 0.323315694 0.08475766 0.026376663 0.015392466 DRUG 4 NNRTI Manufacturer5 1012016 12 goal7
1012014 0.426477779 0.100488819 0.034437931 0.020072081 DRUG 1 PI Manufacturer4 1012016 7 goal6
1012016 0.627661362 0.146335677 0.052207204 0.030324811 DRUG 2 STR Manufacturer3 1012016 12 goal6
2712016 0.682537914 0.173016511 0.067592392 0.039461229 DRUG 3 NNRTI Manufacturer2 1012016 10 goal7
1712016 0.395454954 0.106938038 0.043405249 0.025173052 DRUG 4 PI Manufacturer1 1012016 10 goal8
1012016 0.405448121 0.097840719 0.042806791 0.024596638 DRUG 1 STR Manufacturer5 1012016 10 goal9
1812016 0.61654553 0.154245245 0.080707769 0.046582374 DRUG 2 NNRTI Manufacturer4 1012016 10 goal10
1912016 0.448994855 0.082140864 0.049786133 0.028663422 DRUG 3 PI Manufacturer3 1012016 10 goal11
2012016 0.563174269 0.103926623 0.06641121 0.038270423 DRUG 4 STR Manufacturer2 1012016 10 goal12
2112016 0.294613984 0.062050611 0.041020625 0.023675833 DRUG 1 ART Manufacturer1 1012016 10 goal13
2212016 0.408718205 0.075283165 0.0575669 0.03282064 DRUG 2 II Manufacturer5 1012016 10 goal14
2312016 0.111911856 0.018734629 0.015831974 0.009130108 DRUG 3 NNRTI Manufacturer4 1012016 10 goal15
2412016 0.150495864 0.026025458 0.024094392 0.013900663 DRUG 4 PI Manufacturer3 1012016 10 goal16
我的代码
我还尝试从文件夹中通过下拉菜单选择相同格式的任何文件.csv文件来更改分析数据，但有些文件无法正常工作。非常感谢您的帮助。
###############Assigning Packages
library(shiny)
library(dplyr)
library(DT)
library(plotly)
library(rhandsontable)
#############################
# Importing Data
cDat <- read.table(file = "data/DrugData.csv", sep = ",", header =
TRUE, row.names = NULL)
cDat1 <- read.table(file = "data/DrugData1.csv", sep = ",", header =
TRUE, row.names = NULL)
DF <- read.csv("/Users/anshulujlayan/Documents/output.csv", sep=",",
row.names=1)
#( DF <- data.frame(Value = 1:10, Name = LETTERS[1:10],
# Date = seq(from = Sys.Date(), by = "days", length.out = 10),
# stringsAsFactors = FALSE) )
editTable(DF, outdir="/Users/anshulujlayan/Documents", outfilename="newaakritiDF")
############################
#filenames <- list.files(path = "input$files[['data/']]", pattern= "*.csv" )
folder <- "/Users/anshulujlayan/Documents/Team_Profile/First_Assignement_29_September_2017 /data" # path to folder that holds multiple .csv files
filenames <- list.files(path=folder, pattern="*.csv")
print(filenames)
print(DF)
MANUFACTURER_list <- unique(cDat$MANUFACTURER)
DrugClass_list <- unique(cDat$DrugClass)
DrugType_list <- unique(cDat$DrugType)
columns <- names(cDat)
abc <- cDat$MO_ID
d <- as.character(cDat$MO_ID)
d <- paste0(substr(d, 0, 2), "-", substr(d, 3, 4), "-", substr(d, start = 4, 7))
cDat$MO_ID <- as.Date(d, format = "%d-%m-%y")
mno <- cDat$filteredData
HL_list <- c("High","low")
print(mno)
editTable <- function(DF, outdir=getwd(), outfilename="newAakritiDF"){
server <- function(input, output, session) {
values <- reactiveValues()
## Handsontable
observe({
if (!is.null(input$hot)) {
values[["previous"]] <- isolate(values[["DF"]])
DF = hot_to_r(input$hot)
} else {
if (is.null(values[["DF"]]))
DF <- DF
else
DF <- values[["DF"]]
}
values[["DF"]] <- DF
})
output$hot <- renderRHandsontable({
DF <- values[["DF"]]
rhandsontable(DF)
})
## Save
observeEvent(input$save, {
fileType <- isolate(input$fileType)
finalDF <- isolate(values[["DF"]])
dput(finalDF, file=file.path(outdir, sprintf("%s.txt", outfilename)))
# saveRDS(finalDF, file=file.path(outdir, sprintf("%s.rds", outfilename)))
}
)
inputdata <- reactive({
if (grepl("[/\\\\]", input$dataset)) {
stop("Invalid dataset")
}
read.csv(file.path("folder", input$dataset))
})
filteredData <- reactive({
cDat %>% filter(MANUFACTURER %in% input$campaign &
DrugClass %in% input$campaign1 &
DrugType %in% input$campaign2 )
})
selectedData <- reactive({
filteredData() %>%
select_(.dots = input$columns)
})
output$mytable1 <- renderDataTable({
selectedData()
})
output$downloadData <- downloadHandler(
filename = function() {
"DrugDataab.csv"
},
content = function(file) {
write.table(x = selectedData(),
file = file,
quote = FALSE, sep = ",", row.names = FALSE)
}
)
observe({
if(input$selectall == 0) return(NULL)
else if (input$selectall%%2 == 0)
{
updateCheckboxGroupInput(session,"campaign","",choices=MANUFACTURER_list)
}
else
{
updateCheckboxGroupInput(session,"campaign","",choices=MANUFACTURER_list,selecte d=MANUFACTURER_list)
}
})
observe({
if(input$selectall2 == 0) return(NULL)
else if (input$selectall2%%2 == 0)
{
updateCheckboxGroupInput(session,"campaign1","",choices=DrugClass_list)
}
else
{
updateCheckboxGroupInput(session,"campaign1","",choices=DrugClass_list,selected= DrugClass_list)
}
})
observe({
if(input$selectall3 == 0) return(NULL)
else if (input$selectall3%%2 == 0)
{
updateCheckboxGroupInput(session,"campaign2","",choices=DrugType_list)
}
else
{
updateCheckboxGroupInput(session,"campaign2","",choices=DrugType_list,selected=D rugType_list)
}
})
observe({
if(input$selectall4 == 0) return(NULL)
else if (input$selectall4%%2 == 0)
{
updateCheckboxGroupInput(session,"columns","",choices=columns)
}
else
{
updateCheckboxGroupInput(session,"columns","",choices=columns,selected=columns)
}
})
output$plot <- renderPlotly({
plot_ly(cDat, x = ~abc, y = ~columns)
})
filterednewData <- reactive({
# no need for "filter"
cDat[cDat$MANUFACTURER %in% input$checkGroup, ]
})
output$Conversionrate1 <- renderPlotly({
# use filteredData() instead of the full dataset
plot_ly(
filteredData(),
x = ~MO_ID,
y = ~goal1completions,
split = ~MANUFACTURER,
mode = "lines + markers",
hoverinfo = "y" # "y" instead of y ... at least in the newest version
)
})
}
####################### UI.R ##############
ui <- fluidPage(
# Application title
titlePanel("Forecasting Engine"),
# Sidebar with a slider input for the number of bins
sidebarLayout(
sidebarPanel(style = "background-color: #98d8c6",
fluidRow(
column(6,
h6(style = "font-weight: bold;color: #275c4d","Manufacture"),
div(style = "height: 200px; background-color:white; max-height: 200px; border: 1px solid rgba(128, 128, 128, 0.52); padding-left: 10px",
br(),
checkboxGroupInput('campaign', 'Manufacturer',
MANUFACTURER_list,
selected = MANUFACTURER_list)
)
),
column(6,
h6(style = "font-weight: bold;color: #275c4d","Drug Class"),
div(style = "overflow-y: scroll; max-height: 200px; min-height: 200px; background-color:white;padding-left: 10px;border: 1px solid rgba(128, 128, 128, 0.52);",
checkboxGroupInput('campaign1', 'DrugClass',
DrugClass_list,
selected = DrugClass_list)
)
)
),
fluidRow(
column(6,
h6(style = "font-weight: bold;color: #275c4d","Drug List"),
div(style = "overflow-y:scroll;border: 1px solid rgba(128, 128, 128, 0.52); max-height: 200px; min-height: 200px; background-color:white; padding-left: 10px",
br(),
checkboxGroupInput('campaign2', 'DrugType',
DrugType_list,
selected = DrugType_list))),
column(6,
h6(style = "font-weight: bold;color: #275c4d","KPI"),
div(style = "overflow-y:scroll;border: 1px solid rgba(128, 128, 128, 0.52); max-height: 200px; min-height: 200px; background-color:white;padding-left: 10px",
# checkboxGroupInput("columns","Select Columns",choices=vchoices,inline = T)
checkboxGroupInput('columns', 'Columns',
columns,
selected = columns))
)),br(),
fluidRow(
column(3,actionLink(style="background-color: #275c4d;color: #fff;width: 150px","selectall","ALL")),
column(3,actionLink(style="background-color: #275c4d;color: #fff;width: 50px","selectall2","RESET")),
column(3,actionLink(style="background-color: #275c4d;color: #fff;width: 50px","selectall3","ALL")),
column(3,actionLink(style="background-color: #275c4d;color: #fff;width: 50px","selectall4","RESET"))
),br(),
actionButton(style="background-color: #275c4d;color: #fff;width: 150px","","CDAT"),
actionButton(style="background-color: #275c4d;color: #fff;width: 150px","","CDAT1"),
fluidRow(
column(style = "margin-top: 30px;font-weight: bold;line-height: 10px",6,"","Select Frequency"),
column(6,
selectInput("analysis", label = "",
c("Monthly" = "all",
"Yearly" = "specific"),
selected = "all")
) ),br(),
fluidRow(
column(style = "font-weight: bold;line-height: 10px",6,"Select Scenerio",
selectInput(
"subsetType", "",
c("Monthly" = "all",
"Yearly" = "specific"),
selected = "all")
),
column(6,
div(style = "overflow-y:scroll;border: 1px solid rgba(128, 128, 128, 0.52); max-height: 50px; min-height: 50px; background- color:white; padding-left: 10px",
checkboxGroupInput('campaign5', '',
HL_list,
selected = HL_list))
) ),
fluidRow(
column(style = "font-weight: bold;line-height: 10px",6,
actionButton(style="background-color: #275c4d;text- align:center;color: grey;width: 200px","selectall5","View Final Forecast")
),
column(6,
div(style = "font-weight: bold;line-height: 10px",
actionButton(style="background-color: #275c4d;color: grey;width: 200px","selectall6","View Baseline Forecast")
) )),
downloadButton("downloadData", "Download Data"),
# checkboxGroupInput("checkGroup", label = h3("Goal"),
# setNames(object = paste0("Manufacturer", 1:5),
# nm = paste0("Manufacturer ", 1:5)),
# selected = "Manufacturer 1"),
selectInput(inputId = "dataset",
label = "Choose platform annotation file",
choices = c("cDat","pressure"))
),
##### Show data in Main Panel
# Show a plot of the generated distribution
mainPanel(
tabsetPanel(type = "tabs",
tabPanel("Table", dataTableOutput('mytable1'), dataTableOutput('mytable2')),
tabPanel("Plot", plotlyOutput("Conversionrate1"),
verbatimTextOutput("event")),
tabPanel("Editable Parameter", br(),actionButton("save", "Save"), br(),
rHandsontableOutput("hot"))
))
)
)
shinyApp(ui = ui, server = server)
}
答案 0 :(得分：0)
您可以将dplyr filter与%in%运营商一起使用。
library(shiny)
library(ggplot2)
library(dplyr)
# Change rownames
cDat <- read.table(file.path(DATA_DIR, "DrugData.csv"), sep = ",", header =
TRUE, row.names = NULL)
campaigns_list <- unique(cDat$MANUFACTURER)
server <- function(input, output, session) {
output$mytable1 <- renderDataTable({
#cDat[input$campaign_list,]
#print(input)
cDat %>% filter(MANUFACTURER %in% input$campaign)
})
}
ui <- fluidPage(
# Application title
titlePanel("Example"),
# Sidebar with a slider input for the number of bins
sidebarLayout(
sidebarPanel(
checkboxGroupInput('campaign', 'Manufacturer',
campaigns_list,
selected = campaigns_list)
),
# Show a plot of the generated distribution
mainPanel(
dataTableOutput('mytable1'))
)
)
shinyApp(ui = ui, server = server)
答案 1 :(得分：0)
使用包dplyr这很容易。只需像这样更改您的代码。
###############Assigning Packages
library(shiny)
library(ggplot2)
library(dplyr)
library(DT)
#############################
# Importing Data
cDat <- read.table(file = "data/DrugData.tsv", sep = ",", header =
TRUE, row.names = NULL)
############################
###### Preparing list for Checkbox & Change rownames
#campaigns_list <- unique(cDat$MANUFACTURER)
MANUFACTURER_list <- unique(cDat$MANUFACTURER)
DrugClass_list <- unique(cDat$DrugClass)
DrugType_list <- unique(cDat$DrugType)
columns <- names(cDat)
####################### Server.R##########
server <- function(input, output, session) {
filteredData <- reactive({
cDat %>% filter(MANUFACTURER %in% input$campaign &
DrugClass %in% input$campaign1 &
DrugType %in% input$campaign2 )
})
selectedData <- reactive({
filteredData() %>%
select_(.dots = input$columns)
})
output$mytable1 <- renderDataTable({
selectedData()
})
}
####################### UI.R ##############
ui <- fluidPage(
# Application title
titlePanel("Example"),
# Sidebar with a slider input for the number of bins
sidebarLayout(
sidebarPanel(
checkboxGroupInput('campaign', 'Manufacturer',
MANUFACTURER_list,
selected = MANUFACTURER_list),
checkboxGroupInput('campaign1', 'DrugClass',
DrugClass_list,
selected = DrugClass_list),
checkboxGroupInput('campaign2', 'DrugType',
DrugType_list,
selected = DrugType_list),
checkboxGroupInput('columns', 'Columns',
columns,
selected = columns)
),
##### Show data in Main Panel
# Show a plot of the generated distribution
mainPanel(
dataTableOutput('mytable1'))
)
)
shinyApp(ui = ui, server = server)
希望这会有所帮助。