R 网络中的子过滤数据集
我正在阅读关于的闪亮教程,我被层叠过滤器或子过滤器卡住了 本教程使用。数据包含BC酒类商店销售的所有产品的信息 我想做的是,当我选择变量PRODUCT\u CLASS\u NAME时,我希望PRODUCT\u MINOR\u CLASS\u NAME的选择仅限于PRODUCT\u CLASS\u NAME中的选择。所以,如果在产品类别名称中选择了啤酒,我就没有选择权,比如说,在产品类别名称下选择美国威士忌 一些设置代码:R 网络中的子过滤数据集,r,shiny,R,Shiny,我正在阅读关于的闪亮教程,我被层叠过滤器或子过滤器卡住了 本教程使用。数据包含BC酒类商店销售的所有产品的信息 我想做的是,当我选择变量PRODUCT\u CLASS\u NAME时,我希望PRODUCT\u MINOR\u CLASS\u NAME的选择仅限于PRODUCT\u CLASS\u NAME中的选择。所以,如果在产品类别名称中选择了啤酒,我就没有选择权,比如说,在产品类别名称下选择美国威士忌 一些设置代码: library(shiny) library(ggplot2) lib
library(shiny)
library(ggplot2)
library(dplyr)
bcl <- read.csv("http://pub.data.gov.bc.ca/datasets/176284/BC_Liquor_Store_Product_Price_List.csv", stringsAsFactors = F)
这是我的用户界面:
ui <- fluidPage(
titlePanel("BC Liquor Store prices"),
sidebarLayout(
sidebarPanel(
uiOutput("countryOutput"),
sliderInput("priceInput", "Price", min = 0, max = 100, value=c(0,50), pre="$"),
#radioButtons("typeInput", "Product Type", choices = c("BEER", "REFRESHMENT", "SPIRITS", "WINE"), selected="WINE"),
uiOutput("typeOutput"),
uiOutput("subtypeOutput")
#selectInput("countryInput", "Country", choices = c("CANADA", "FRANCE", "ITALY"))
),
mainPanel(
plotOutput("coolplot"),
br(),
tableOutput("results")
)
)
)
这是我的服务器:
server <- function(input, output) {
# create a reactive to filter the dataset
df <- reactive({
# df() is trying to access teh country input, but the country input hasn't been created yet via uiOutput, so there is an initial error that goes away.
# to prevent this temporary error, just include the following:
if (is.null(input$priceInput[1]) | is.null(input$priceInput[2]) | is.null(input$countryInput) | is.null(input$subtypeInput) | is.null(input$typeInput)) {
return(NULL)
}
bcl <- bcl %>%
filter(CURRENT_DISPLAY_PRICE >= input$priceInput[1],
CURRENT_DISPLAY_PRICE <= input$priceInput[2],
PRODUCT_COUNTRY_ORIGIN_NAME %in% input$countryInput,
PRODUCT_CLASS_NAME %in% input$typeInput,
PRODUCT_MINOR_CLASS_NAME %in% input$subtypeInput)
bcl
})
output$coolplot <- renderPlot({
# same error as above
if (is.null(df())) {
return(NULL)
}
ggplot(df(), aes(PRODUCT_ALCOHOL_PERCENT)) + geom_histogram(binwidth = 1)
})
output$results <- renderTable({
df()
})
output$countryOutput <- renderUI({
selectInput("countryInput", "Country",
sort(unique(bcl$PRODUCT_COUNTRY_ORIGIN_NAME))
)
})
output$typeOutput <- renderUI({
selectInput("typeInput", "Product type",
sort(unique(bcl$PRODUCT_CLASS_NAME))
)
})
output$subtypeOutput <- renderUI({
selectInput("subtypeInput", "Product subtype",
sort(unique(bcl$PRODUCT_MINOR_CLASS_NAME))
)
})
}
shinyApp(ui = ui, server = server)
我意识到这是由于没有完全理解光泽或过滤器。有没有更好的方法来获得我想要的结果
谢谢 我想你把一些过滤弄混了。看看我介绍的更新。请注意,数据集中没有带大写的列
#rm(list = ls())
library(shiny)
library(ggplot2)
library(dplyr)
bcl <- read.csv("http://deanattali.com/files/bcl-data.csv", stringsAsFactors = F)
app <- shinyApp(
ui <- fluidPage(
titlePanel("BC Liquor Store prices"),
sidebarLayout(
sidebarPanel(
selectInput("countryInput", "Country",sort(unique(bcl$Country))),
sliderInput("priceInput", "Price", min = 0, max = 100, value=c(0,50), pre="$"),
uiOutput("typeOutput"),
uiOutput("subtypeOutput")
),
mainPanel(
plotOutput("coolplot"),
br(),
tableOutput("results")
)
)
),
server <- function(input, output) {
df0 <- eventReactive(input$countryInput,{
bcl %>% filter(Country %in% input$countryInput)
})
output$typeOutput <- renderUI({
selectInput("typeInput", "Product type",sort(unique(df0()$Name)))
})
df1 <- eventReactive(input$typeInput,{
df0() %>% filter(Country %in% input$countryInput)
})
output$subtypeOutput <- renderUI({
selectInput("subtypeInput", "Product subtype",sort(unique(df1()$Subtype)))
})
df2 <- reactive({
df1() %>% filter(Price >= input$priceInput[1], Price <= input$priceInput[2],Subtype %in% input$subtypeInput)
})
output$coolplot <- renderPlot({
ggplot(df2(), aes(Alcohol_Content)) + geom_histogram(binwidth = 1)
})
output$results <- renderTable({
df2()
})
})
runApp(app)
多亏猪排帮我明白了我不知道如何使用过滤器 以下是基于猪排的最终代码,它在实际数据集上工作:
library(shiny)
library(ggplot2)
library(dplyr)
bcl <- read.csv("http://pub.data.gov.bc.ca/datasets/176284/BC_Liquor_Store_Product_Price_List.csv", stringsAsFactors = F)
ui <- fluidPage(
titlePanel("BC Liquor Store prices"),
sidebarLayout(
sidebarPanel(
selectInput("countryInput", "Country",sort(unique(bcl$PRODUCT_COUNTRY_ORIGIN_NAME))),
sliderInput("priceInput", "Price", min = 0, max = 100, value=c(0,50), pre="$"),
uiOutput("typeOutput"),
uiOutput("subtypeOutput")
),
mainPanel(
plotOutput("coolplot"),
br(),
dataTableOutput("results")
)
)
)
server <- function(input, output) {
# create a reactive to filter the dataset
df0 <- eventReactive(input$countryInput,{
bcl %>% filter(PRODUCT_COUNTRY_ORIGIN_NAME %in% input$countryInput)
})
output$typeOutput <- renderUI({
selectInput("typeInput", "Product type",sort(unique(df0()$PRODUCT_CLASS_NAME)))
})
df1 <- eventReactive(input$typeInput,{
df0() %>% filter(PRODUCT_CLASS_NAME %in% input$typeInput)
})
output$subtypeOutput <- renderUI({
selectInput("subtypeInput", "Product subtype",sort(unique(df1()$PRODUCT_MINOR_CLASS_NAME)))
})
df2 <- reactive({
df1() %>% filter(CURRENT_DISPLAY_PRICE >= input$priceInput[1],
CURRENT_DISPLAY_PRICE <= input$priceInput[2],
PRODUCT_MINOR_CLASS_NAME %in% input$subtypeInput)
})
output$coolplot <- renderPlot({
ggplot(df2(), aes(PRODUCT_ALCOHOL_PERCENT)) + geom_histogram(binwidth = 1)
})
output$results <- renderTable({
df2()
})
}
shinyApp(ui = ui, server = server)
只是在子类中用df替换bcl。对不起,我原来的帖子拉错了CSV文件。当我的实际代码引用原始CSV时,它正在从教程中提取一个经过编辑的CSV。我在上面编辑了我的代码。啊哈!这一修正奏效了。我对如何使用过滤器的理解很差。我将使用真实的数据集发布我的最终代码。谢谢