r - 当标准选择相反时，过滤选项不起作用
问题描述
我在这里面临一个奇怪的问题，真的不知道为什么会这样。所以需要大家的帮助。
当您运行以下应用程序并从下拉列表中选择“相关性”时，不会显示任何绘图。但是，当您首先选择“趋势”然后选择“相关性”时，将显示该图。这里很奇怪。不知道我在这里做错了什么。请帮忙
---
title: "Untitled"
output:
flexdashboard::flex_dashboard:
orientation: columns
vertical_layout: scroll
runtime: shiny
theme: cosmo
---
```{r setup, include=FALSE}
library(shiny)
library(flexdashboard)
library(tidyverse)
```
```{r}
Copy_of_mill_para <- structure(list(Date = structure(c(1505779200, 1505779500, 1505779800,
1505780100, 1505780400, 1505780700, 1505781000, 1505781300, 1505781600
), class = c("POSIXct", "POSIXt"), tzone = "UTC"), A = c(42,
40, 41, 45, 25, 39, 44, 25, 39), B = c(27, 36, 40, 31, 44, 34,
39, 44, 41), C = c(39, 42, 33, 26, 29, 42, 24, 34, 35)), row.names = c(NA,
-9L), class = "data.frame")
Copy_of_mill_para1 <- Copy_of_mill_para %>%
gather(variable, value, -Date)
```
Summary
=================
Inputs {.sidebar}
-----------------------------------------------------------------------
```{r}
selectInput("c", "Filter1", choices = c("","Trend","Correlation"))
output$filter_2 <- renderUI({
if (input$c == "") {
return()
} else if (input$c == "Trend") {
label = "Trend"
selectInput("b",
label,
choices = c("ALL", levels(factor(Copy_of_mill_para1$variable))))
} else {
label = "First Variable"
selectInput("b",
label,
choices = c(levels(factor(Copy_of_mill_para1$variable))))
}
})
output$filter_3 <- renderUI({
# If missing input, return to avoid error later in function
if (input$c == "Trend"|input$c == "") {
return()
} else {
selectInput("a",
"Second Variable",
choices = c(levels(factor(Copy_of_mill_para1$variable))))
}
})
uiOutput("filter_2")
uiOutput("filter_3")
output$filter_7 <- renderUI({
if (input$c == "Trend")
radioButtons("r",h5("Highlight"),choices = list("No", "Yes"),selected = "No", inline = T)
})
uiOutput("filter_7")
```
Column {data-width=350}
-----------------------------------------------------------------------
### Chart A
```{r}
output$g1 <- renderPlot({
req(input$c)
if (input$c == "Trend") {
plot_data <- Copy_of_mill_para1
}
if (input$c == "Trend" & input$b != "ALL") {
plot_data <- Copy_of_mill_para1 %>% filter(variable == input$b)
}
if (input$c == "Correlation"){
plot_data <- Copy_of_mill_para
}
if (input$c == "Trend" & input$r != "Yes") {
ggplot(plot_data, aes(x = Date, y = value, color = variable)) +
geom_line(size = .2)
}
else if (input$c == "Trend"& input$r == "Yes") {
ggplot(plot_data, aes(x = Date, y = value, color = variable)) +
geom_line(size = .2)+geom_point(data = plot_data %>% filter(variable == "A"),aes(x=Date, y = value),color='red',size=3)
}
else if (input$c == "Correlation") {
req(input$a)
req(input$b)
ggplot(plot_data, aes_string(x = input$b, y = input$a)) +
geom_point()
}
})
plotOutput("g1")
```
解决方案
if合并您的语句可能更容易，并添加req(input$...)以确保这些输入在评估之前存在（最初将为 NULL）。
此外，它对“ALL”变量进行错误检查以制作相关图 - 您可以在绘制之前首先确保输入值包含在（使用%in%）数据中（为此添加了语句）。
output$g1selectInput当您使用依赖项更改 c 时，将被调用两次。解决此问题的一种方法是isolate在您不想触发的输入上使用output$g1。
但请看看这是否有帮助。很大程度上取决于您希望最终结果的样子。
### Chart A
```{r}
output$g1 <- renderPlot({
req(input$b, input$c)
if (input$c == "Trend") {
req(input$r)
if (input$b != "ALL") {
plot_data <- Copy_of_mill_para1 %>% filter(variable == input$b)
} else {
plot_data <- Copy_of_mill_para1
}
if (input$r != "Yes") {
p <- ggplot(plot_data, aes(x = Date, y = value, color = variable)) +
geom_line(size = .2)
} else {
p <- ggplot(plot_data, aes(x = Date, y = value, color = variable)) +
geom_line(size = .2)+geom_point(data = plot_data %>% filter(variable == "A"),aes(x=Date, y = value),color='red',size=3)
}
}
if (input$c == "Correlation") {
req(input$a)
plot_data <- Copy_of_mill_para
if (input$b %in% Copy_of_mill_para1$variable && input$a %in% Copy_of_mill_para1$variable) {
p <- ggplot(plot_data, aes_string(x = input$b, y = input$a)) +
geom_point()
}
}
p
})
plotOutput("g1")
这是完整的 Rmarkdown，其中包含一些输入合并和其他小的修改：
---
title: "Untitled"
output:
flexdashboard::flex_dashboard:
orientation: columns
vertical_layout: scroll
runtime: shiny
theme: cosmo
---
```{r setup, include=FALSE}
library(shiny)
library(flexdashboard)
library(tidyverse)
```
```{r}
Copy_of_mill_para <- structure(list(
Date = structure(c(1505779200, 1505779500, 1505779800, 1505780100, 1505780400, 1505780700, 1505781000, 1505781300, 1505781600),
class = c("POSIXct", "POSIXt"), tzone = "UTC"),
A = c(42, 40, 41, 45, 25, 39, 44, 25, 39),
B = c(27, 36, 40, 31, 44, 34, 39, 44, 41),
C = c(39, 42, 33, 26, 29, 42, 24, 34, 35)),
row.names = c(NA, -9L), class = "data.frame")
Copy_of_mill_para1 <- Copy_of_mill_para %>%
gather(variable, value, -Date)
```
Summary
=================
Inputs {.sidebar}
-----------------------------------------------------------------------
```{r}
selectInput("c", "Filter1", choices = c("", "Trend", "Correlation"))
output$filter_2 <- renderUI({
if (input$c == "") {
return()
} else if (input$c == "Trend") {
div(
selectInput("b", "Trend", choices = c("ALL", levels(factor(Copy_of_mill_para1$variable)))),
radioButtons("r", h5("Highlight"), choices = list("No", "Yes"), selected = "No", inline = T)
)
} else {
div(
selectInput("b", "First Variable", choices = c(levels(factor(Copy_of_mill_para1$variable)))),
selectInput("a", "Second Variable", choices = c(levels(factor(Copy_of_mill_para1$variable))))
)
}
})
uiOutput("filter_2")
```
Column {data-width=350}
-----------------------------------------------------------------------
### Chart A
```{r}
output$g1 <- renderPlot({
req(input$b)
if (isolate(input$c) == "Trend") {
req(input$r)
if (input$b != "ALL") {
plot_data <- Copy_of_mill_para1 %>% filter(variable == input$b)
} else {
plot_data <- Copy_of_mill_para1
}
if (input$r != "Yes") {
p <- ggplot(plot_data, aes(x = Date, y = value, color = variable)) +
geom_line(size = .2)
} else {
p <- ggplot(plot_data, aes(x = Date, y = value, color = variable)) +
geom_line(size = .2)+geom_point(data = plot_data %>% filter(variable == "A"),aes(x=Date, y = value),color='red',size=3)
}
}
if (isolate(input$c) == "Correlation") {
req(input$a)
plot_data <- Copy_of_mill_para
if (input$b %in% Copy_of_mill_para1$variable && input$a %in% Copy_of_mill_para1$variable) {
p <- ggplot(plot_data, aes_string(x = input$b, y = input$a)) +
geom_point()
}
}
p
})
plotOutput("g1")
```
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