我正在尝试建立一个仪表板，用户可以在其中按年份，状态和产品过滤数据。理想情况下，它应该在每个产品具有2个变量(满意度得分和重要性得分)相关联的地方运行。从数据集中过滤时，应针对用户感兴趣的各个细分市场计算汇总平均值。分数组合成一个data.frame并绘制在一个图上。
这是我在的地方
我的UI
library(shiny)
library(dplyr)
library(shinydashboard)
library(tidyverse)
ui <- dashboardPage(
dashboardHeader(title="Membership Satisfaction"),
dashboardSidebar(
sidebarMenu(
menuItem("Demographics Dashboard", tabName = "demos", icon =
icon("dashboard"))
)
),
dashboardBody(
tabItems(
tabItem(tabName = "demos",
sidebarPanel(
checkboxGroupInput("inpt","Select variables to plot",
choices =
c("Web" = 1,"Huddle" = 3, "Other" = 5,
"Test" = 7)),
checkboxGroupInput("role",
"Select Primary Role of Interest",
choices = c("Student" = 1, "Not" = 2)),
checkboxGroupInput("range",
"Select year(S) of Interest",
choices = c("2016"=2,"July 2017"=1))),
fluidPage(
plotOutput("plot")
)))))
而我的服务器:
server <- function(input,output){
library(tidyverse)
x <- reactive({
inpt <- as.double(input$inpt)
role <- as.double(input$role)
range <- as.double(input$range)
GapAnalysis_LongFormB %>%
filter(Product %in% inpt,
status %in% role,
year %in% range) %>%
summarize(avg = mean(Score, na.rm = TRUE)) %>%
pull(-1)
})
y <- reactive({
inpt <- as.double(input$inpt)+1
role <- as.double(input$role)
range <- as.double(input$range)
GapAnalysis_LongFormB %>%
filter(Product %in% inpt,
status %in% role,
year %in% range) %>%
summarize(avg = mean(Score, na.rm = TRUE))%>%
pull(-1)
})
xyCoords<- reactive({
x <- x()
y <- y()
data.frame(col1=x, col2=y)
})
output$plot <- renderPlot({
xyCoords <- xyCoords()
xyCoords %>%
ggplot(aes(x = col1, y = col2)) +
geom_point(colour ="green", shape = 17, size = 5 )+
labs(x = "Mean Satisfaction", y = "Mean Importance") +
xlim(0,5) + ylim(0,5) +
geom_vline(xintercept=2.5) +
geom_hline(yintercept = 2.5)
})
}
shinyApp (ui = ui, server = server)
以下是变量结构:
> dput(head(GapAnalysis_LongFormB))
structure(list(status = c(1, 5, 5, 1, 1, 5), year = c(1, 1, 1,
1, 1, 1), Product = structure(c(1L, 1L, 1L, 1L, 1L, 1L), .Label = c("1",
"2", "3", "4"), class = "factor"), Score = c(2, 5, 3, 5, 4, 4
)), .Names = c("status", "year", "Product", "Score"), row.names = c(NA,
6L), class = "data.frame")
它有效-仅不能完全满足我的需要。当前，它在绘制之前需要所有3个复选框输入变量(整数，角色，范围)中的输入。我需要它来需要一种产品，但需要为每个其他输入绘图。意思是，如果他们选择Web，它将绘制Web的均值。如果他们选择Web和2017年，则将绘制2017年Web的平均值。
任何帮助都非常感谢!!!!
最佳答案
变化
我认为这里有些事情会引起一些麻烦:
首先，尽管您从未定义input$range，但是您正在使用input$range。您已经定义了input$yrs，因此我将其更改为input$range。
接下来，将==与filter结合使用，而应使用%in%代替。这允许多个选择，而不仅仅是单个选择。如果只想选择一个，请使用radioButtons()而不是checkboxGroupInput()。
在summarize中，您正在使用其他不必要的子集。我们已经在数据集上使用了完全相同的filter，因此无需在summarize中应用子集。
最后，我认为您的xyCoords可能会遇到一些严重问题。因为您在两个数据集上使用了不同的过滤器，所以最终x和y的向量长度可能会有所不同。这会引起问题。我的建议是，您以某种方式将两个数据集与full_join组合在一起，以确保x和y的长度始终相同。这不是关于shiny的问题，而是关于dplyr的问题。
我还更改了一些reactive对象。
使用者介面:
library(shiny)
library(shinydashboard)
library(tidyverse)
ui <- dashboardPage(
dashboardHeader(title="Membership Satisfaction"),
dashboardSidebar(
sidebarMenu(
menuItem("Demographics Dashboard", tabName = "demos", icon =
icon("dashboard"))
)
),
dashboardBody(
tabItems(
tabItem(tabName = "demos",
sidebarPanel(
checkboxGroupInput("inpt","Select variables to plot", choices =
c("Web" = 1,"Huddle" = 3, "Other" = 5, "Test" = 7)),
checkboxGroupInput("role",
"Select Primary Role of Interest",
choices = c("Student" = 1, "Not" = 2)),
checkboxGroupInput("range",
"Select year(S) of Interest",
choices = c("2016"=2,"July 2017"=1))),
fluidPage(
plotOutput("plot")
)))))
服务器:
server <- function(input,output){
library(tidyverse)
GapAnalysis_LongFormImpt <- structure(list(status = c(1, 5, 5, 1, 1, 5), year = c(1, 1, 1,
1, 1, 1), Product = structure(c(2L, 2L, 2L, 2L, 2L, 2L), .Label = c("1",
"2", "3", "4"), class = "factor"), Score = c(1, 1, 3, 2, 2, 1
)), .Names = c("status", "year", "Product", "Score"), row.names = c(NA,
6L), class = "data.frame")
GapAnalysis_LongFormSat <- structure(list(status = c(5, 5, 1, 1, 5, 1), year = c(1, 1, 1,
1, 1, 1), Product = structure(c(1L, 1L, 1L, 1L, 1L, 1L), .Label = c("1",
"2", "3", "4"), class = "factor"), Score = c(2, 3, 2, 1, 1, 1
)), .Names = c("status", "year", "Product", "Score"), row.names = c(NA,
6L), class = "data.frame")
x <- reactive({
inpt <- as.double(input$inpt)
role <- as.double(input$role)
range <- as.double(input$range)
GapAnalysis_LongFormSat %>%
filter(Product %in% inpt,
status %in% role,
year %in% range) %>%
summarize(Avg = mean(Score, na.rm = TRUE)) %>%
pull(-1)
})
y <- reactive({
inpt <- as.double(input$inpt)
role <- as.double(input$role)
range <- as.double(input$range)
GapAnalysis_LongFormImpt %>%
filter(Product %in% inpt,
status %in% role,
year %in% range) %>%
summarize(Avg = mean(Score, na.rm = TRUE))%>%
pull(-1)
})
xyCoords<- reactive({
x <- x()
y <- y()
data.frame(col1=x, col2=y)})
output$plot <- renderPlot({
xyCoords <- xyCoords()
xyCoords %>%
ggplot(aes(x = col1, y = col2)) +
geom_point(colour ="green", shape = 17, size = 5 )+
labs(x = "Mean Satisfaction", y = "Mean Importance") +
xlim(0,5) + ylim(0,5) +
geom_vline(xintercept=2.5) +
geom_hline(yintercept = 2.5)})
}
shinyApp (ui = ui, server = server)
关于r - R Shiny DPLyr无功滤波器，我们在Stack Overflow上找到一个类似的问题：https://stackoverflow.com/questions/50118326/