如何解决case_when变异整数转换问题
我想知道如何解决case_when中的整数和双矢量问题。我需要双精度矢量作为我的数字输入,但是,“ case_when”总是会抛出一个错误,例如“ x必须是整数矢量,而不是双精度矢量”。
仅当我将“ TRUE〜0”更改为“ TRUE〜0L”时才允许输入整数输入
我需要输入0.05、0.01等通货膨胀率,而不是1,2 3这样的整数
几天来我对这个错误感到沮丧。有人可以帮我吗?
谢谢!
#Load packages
library(shiny)
library(data.table)
library(dplyr,warn.conflicts = FALSE)
library(DT)
#>
#> Attaching package: 'DT'
#> The following objects are masked from 'package:shiny':
#>
#> dataTableOutput,renderDataTable
library(tidyr)
df<-data.frame('provider'="CVS",'year'=c(2020,2021,2022,2023,2024,2025))
# Define UI for app that draws a histogram ----
ui <- fluidPage(
# App title ----
titlePanel("Hello Shiny!"),# Sidebar layout with input and output definitions ----
sidebarLayout(
# Sidebar panel for inputs ----
sidebarPanel(
tabsetPanel(
tabPanel("Brand Inf",numericInput("b1","Brand 1",min = NA,max = NA),numericInput("b2","Brand 2",numericInput("b3","Brand 3",max = NA)),tabPanel("GFR",numericInput("p1","GFR 1",numericInput("p2","GFR 2",numericInput("p3","GFR 3",max = NA))),width = 2),# Main panel for displaying outputs ----
mainPanel(
DT::dataTableOutput("table"))
))
# Define server logic required to draw a histogram ----
server <- function(input,output) {
DF<-function(var1,var2,var3,var4,var5,var6){
var1<-enexpr(var1)
var2<-enexpr(var2)
var3<-enexpr(var3)
var4<-enexpr(var4)
var5<-enexpr(var5)
var6<-enexpr(var6)
df<-df %>% rowwise %>%
mutate(inflation= case_when(year== 2020 ~ !!var1,year == 2021 ~ !!var2,year == 2022 ~ !!var3,TRUE ~ 0),GFR=case_when(year== 2020 ~ !!var4,year == 2021 ~ !!var5,year == 2022 ~ !!var6,TRUE ~ 0))
}
data<-reactive({
DF(input,input$b1,input$b2,input$b3,input$p1,input$p2,input$p3)
})
#plan awp table
output$table <- DT::renderDataTable({
DATA <- data()
})
}
shinyApp(ui,server)
静态R Markdown文档中不支持发光的应用程序
DF(0.05,0.05,0.01,0.01)
#> Error in DF(0.05,0.01): could not find function "DF"
DF
#> Error in eval(expr,envir,enclos): object 'DF' not found
由reprex package(v0.3.0)于2020-08-12创建
解决方法
尝试一下
#Load packages
library(shiny)
library(data.table)
library(dplyr,warn.conflicts = FALSE)
library(DT)
library(tidyr)
df<-data.frame(provider="CVS",year=c(2020,2021,2022,2023,2024,2025))
# Define UI for app that draws a histogram ----
ui <- fluidPage(
# App title ----
titlePanel("Hello Shiny!"),# Sidebar layout with input and output definitions ----
sidebarLayout(
# Sidebar panel for inputs ----
sidebarPanel(width=2,h3("Brand Inf"),numericInput("b1","Brand 1",min = NA,max = NA),numericInput("b2","Brand 2",numericInput("b3","Brand 3",h3("GFR"),numericInput("p1","GFR 1",numericInput("p2","GFR 2",numericInput("p3","GFR 3",max = NA)
),# Main panel for displaying outputs ----
mainPanel(
DTOutput("table"))
)
)
# Define server logic required to draw a histogram ----
server <- function(input,output) {
DF<-function(var1,var2,var3,var4,var5,var6){
df1<-df %>% rowwise %>%
transform(inflation= case_when(year== 2020 ~ var1,year == 2021 ~ var2,year == 2022 ~ var3,TRUE ~ 0),GFR=case_when(year== 2020 ~ var4,year == 2021 ~ var5,year == 2022 ~ var6,TRUE ~ 0))
return(df1)
}
data1<-reactive({
DF(as.numeric(input$b1),as.numeric(input$b2),as.numeric(input$b3),as.numeric(input$p1),as.numeric(input$p2),as.numeric(input$p3))
})
#plan awp table
output$table <- renderDT({
data1()
})
}
shinyApp(ui,server)
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