使用选定输入在 dplyr 中进行 R Shiny Reactive 数据帧操作
RShiny Reactive data frame manipulation in dplyr using selected input
我无法让我的 dplyr 代码在 Shiny 中运行。
我正在尝试根据用户选择的 "input" 操作数据框。我想在 ui 中使用下拉菜单,但无法在 server 中使用(使用时dplyr select()
).我已经使它与 "action buttons" 一起工作,但这会产生非常重复的代码(每个 observeEvent()
基本上具有相同的代码)。
我正在调整用 RMarkdown 编写的代码,其中我在笔记本的开头更改了 TARGET
变量的定义,这会在我重新编织时影响所有后续模型、绘图和表格。通过注释 In/Out 一行,我生成了几个不同目标变量的结果(它们共享一些但不是所有数据)。我想在 Shiny 中实现这一点,供其他用户自助服务。
# I would like to do it "this" way, but it doesn't work
library(shiny)
library(ggplot2)
library(dplyr)
library(datasets)
library(lubridate)
df <- airquality %>%
mutate(date = make_datetime(day = Day, month = Month),
Ozone1 = Ozone + 1, Temp1 = Temp + 1,
Ozone_predictor = Ozone / 2, Temp_predictor = Temp / 2) %>%
select(date, everything(), -Month, -Day)
ui <- fluidPage(
# Title
titlePanel("New York AirQuality Measurements"),
# Input Selection used to build dataframe
sidebarLayout(
sidebarPanel(
selectInput(inputId = "target",
label = "Choose a prediction target for visualization",
choices = list("Ozone", "Ozone1", "Temp")
)
),
# Plot
mainPanel(
plotOutput("plot", height = "1200px")
)
)
)
server <- function(input, output) {
df <- reactive({
if(input$target == "Ozone"){
df <- df %>%
select(-Ozone1, -contains("Temp")) %>%
tidyr::gather(key = key, value = value, -date)
if(input$target == "Ozone1"){
df <- df %>%
select(-Ozone, -contains("Temp")) %>%
tidyr::gather(key = key, value = value, -date)
}else{
df <- df %>%
select(-contains("Ozone")) %>%
tidyr::gather(key = key, value = value, -date)
}
}
})
output$plot <- renderPlot({
ggplot(df(), aes(date, value)) +
geom_line() +
facet_wrap(key ~ ., scales = "free", ncol = 1) +
labs(y = "", x = "") +
theme_classic()
})
}
# Run the application
shinyApp(ui = ui, server = server)
# This does work... but is repetitive and may be problematic
# if I have more target variables.
library(shiny)
library(ggplot2)
library(dplyr)
library(datasets)
library(lubridate)
df <- airquality %>%
mutate(date = make_datetime(day = Day, month = Month),
Ozone1 = Ozone + 1, Temp1 = Temp + 1,
Ozone_predictor = Ozone / 2, Temp_predictor = Temp / 2) %>%
select(date, everything(), -Month, -Day)
ui <- fluidPage(
# Title
titlePanel("New York AirQuality Measurements"),
# Action buttons to define dataframe selection
sidebarLayout(
sidebarPanel(
actionButton(inputId = "Ozone", label = "Ozone"),
actionButton(inputId = "Ozone1", label = "Ozone One"),
actionButton(inputId = "Temp", label = "Temperature")),
# Plot
mainPanel(
plotOutput("plot", height = "1200px")
)
)
)
server <- function(input, output) {
rv <- reactiveValues(
data = df %>%
tidyr::gather(key = key, value = value, -date)
)
observeEvent(input$Ozone,
{ rv$data <-
df %>%
select(-Ozone1, -contains("Temp")) %>%
tidyr::gather(key = key, value = value, -date)
})
observeEvent(input$Ozone1,
{ rv$data <-
df %>%
select(-Ozone, -contains("Temp")) %>%
tidyr::gather(key = key, value = value, -date)
})
observeEvent(input$Temp,
{ rv$data <-
df %>%
select(-contains("Ozone")) %>%
tidyr::gather(key = key, value = value, -date)
})
output$plot <- renderPlot({
ggplot(data = rv$data, aes(date, value)) +
geom_line() +
facet_wrap(key ~ ., scales = "free", ncol = 1) +
labs(y = "", x = "") +
theme_minimal()
})
}
# Run the application
shinyApp(ui = ui, server = server)
错误:没有适用于“select_”的方法应用于 class "c('reactiveExpr', 'reactive')"
的对象
(主要)问题是,您定义了一个反应式 df
,它与全局环境 df
中的非反应式数据框同名,它是在开始时创建的-你的应用程序。这似乎把事情搞混了。我将反应的名称更改为 data
。
在你的反应中,if
语句没有相互关联,我使用 else if
做到了这一点。此外,您不需要将 <-
数据分配给临时变量(在您的情况下 df
)。而如果你使用assign,你需要在reactive的末尾(或者在每个if/else语句的末尾)调用这个临时对象。
library(shiny)
library(ggplot2)
library(dplyr)
library(datasets)
library(lubridate)
df <- airquality %>%
mutate(date = make_datetime(day = Day, month = Month),
Ozone1 = Ozone + 1, Temp1 = Temp + 1,
Ozone_predictor = Ozone / 2, Temp_predictor = Temp / 2) %>%
select(date, everything(), -Month, -Day)
ui <- fluidPage(
# Title
titlePanel("New York AirQuality Measurements"),
# Input Selection used to build dataframe
sidebarLayout(
sidebarPanel(
selectInput(inputId = "target",
label = "Choose a prediction target for visualization",
choices = list("Ozone", "Ozone1", "Temp")
)
),
# Plot
mainPanel(
plotOutput("plot", height = "1200px")
)
)
)
server <- function(input, output) {
data <- reactive({
if(input$target == "Ozone"){
df %>%
select(-Ozone1, -contains("Temp")) %>%
tidyr::gather(key = key, value = value, -date)
} else if(input$target == "Ozone1"){
df %>%
select(-Ozone, -contains("Temp")) %>%
tidyr::gather(key = key, value = value, -date)
}else if (input$target == "Temp") {
df %>%
select(-contains("Ozone")) %>%
tidyr::gather(key = key, value = value, -date)
}
})
output$plot <- renderPlot({
ggplot(data(), aes(date, value)) +
geom_line() +
facet_wrap(key ~ ., scales = "free", ncol = 1) +
labs(y = "", x = "") +
theme_classic()
})
}
# Run the application
shinyApp(ui = ui, server = server)
我无法让我的 dplyr 代码在 Shiny 中运行。
我正在尝试根据用户选择的 "input" 操作数据框。我想在 ui 中使用下拉菜单,但无法在 server 中使用(使用时dplyr select()
).我已经使它与 "action buttons" 一起工作,但这会产生非常重复的代码(每个 observeEvent()
基本上具有相同的代码)。
我正在调整用 RMarkdown 编写的代码,其中我在笔记本的开头更改了 TARGET
变量的定义,这会在我重新编织时影响所有后续模型、绘图和表格。通过注释 In/Out 一行,我生成了几个不同目标变量的结果(它们共享一些但不是所有数据)。我想在 Shiny 中实现这一点,供其他用户自助服务。
# I would like to do it "this" way, but it doesn't work
library(shiny)
library(ggplot2)
library(dplyr)
library(datasets)
library(lubridate)
df <- airquality %>%
mutate(date = make_datetime(day = Day, month = Month),
Ozone1 = Ozone + 1, Temp1 = Temp + 1,
Ozone_predictor = Ozone / 2, Temp_predictor = Temp / 2) %>%
select(date, everything(), -Month, -Day)
ui <- fluidPage(
# Title
titlePanel("New York AirQuality Measurements"),
# Input Selection used to build dataframe
sidebarLayout(
sidebarPanel(
selectInput(inputId = "target",
label = "Choose a prediction target for visualization",
choices = list("Ozone", "Ozone1", "Temp")
)
),
# Plot
mainPanel(
plotOutput("plot", height = "1200px")
)
)
)
server <- function(input, output) {
df <- reactive({
if(input$target == "Ozone"){
df <- df %>%
select(-Ozone1, -contains("Temp")) %>%
tidyr::gather(key = key, value = value, -date)
if(input$target == "Ozone1"){
df <- df %>%
select(-Ozone, -contains("Temp")) %>%
tidyr::gather(key = key, value = value, -date)
}else{
df <- df %>%
select(-contains("Ozone")) %>%
tidyr::gather(key = key, value = value, -date)
}
}
})
output$plot <- renderPlot({
ggplot(df(), aes(date, value)) +
geom_line() +
facet_wrap(key ~ ., scales = "free", ncol = 1) +
labs(y = "", x = "") +
theme_classic()
})
}
# Run the application
shinyApp(ui = ui, server = server)
# This does work... but is repetitive and may be problematic
# if I have more target variables.
library(shiny)
library(ggplot2)
library(dplyr)
library(datasets)
library(lubridate)
df <- airquality %>%
mutate(date = make_datetime(day = Day, month = Month),
Ozone1 = Ozone + 1, Temp1 = Temp + 1,
Ozone_predictor = Ozone / 2, Temp_predictor = Temp / 2) %>%
select(date, everything(), -Month, -Day)
ui <- fluidPage(
# Title
titlePanel("New York AirQuality Measurements"),
# Action buttons to define dataframe selection
sidebarLayout(
sidebarPanel(
actionButton(inputId = "Ozone", label = "Ozone"),
actionButton(inputId = "Ozone1", label = "Ozone One"),
actionButton(inputId = "Temp", label = "Temperature")),
# Plot
mainPanel(
plotOutput("plot", height = "1200px")
)
)
)
server <- function(input, output) {
rv <- reactiveValues(
data = df %>%
tidyr::gather(key = key, value = value, -date)
)
observeEvent(input$Ozone,
{ rv$data <-
df %>%
select(-Ozone1, -contains("Temp")) %>%
tidyr::gather(key = key, value = value, -date)
})
observeEvent(input$Ozone1,
{ rv$data <-
df %>%
select(-Ozone, -contains("Temp")) %>%
tidyr::gather(key = key, value = value, -date)
})
observeEvent(input$Temp,
{ rv$data <-
df %>%
select(-contains("Ozone")) %>%
tidyr::gather(key = key, value = value, -date)
})
output$plot <- renderPlot({
ggplot(data = rv$data, aes(date, value)) +
geom_line() +
facet_wrap(key ~ ., scales = "free", ncol = 1) +
labs(y = "", x = "") +
theme_minimal()
})
}
# Run the application
shinyApp(ui = ui, server = server)
错误:没有适用于“select_”的方法应用于 class "c('reactiveExpr', 'reactive')"
的对象(主要)问题是,您定义了一个反应式 df
,它与全局环境 df
中的非反应式数据框同名,它是在开始时创建的-你的应用程序。这似乎把事情搞混了。我将反应的名称更改为 data
。
在你的反应中,if
语句没有相互关联,我使用 else if
做到了这一点。此外,您不需要将 <-
数据分配给临时变量(在您的情况下 df
)。而如果你使用assign,你需要在reactive的末尾(或者在每个if/else语句的末尾)调用这个临时对象。
library(shiny)
library(ggplot2)
library(dplyr)
library(datasets)
library(lubridate)
df <- airquality %>%
mutate(date = make_datetime(day = Day, month = Month),
Ozone1 = Ozone + 1, Temp1 = Temp + 1,
Ozone_predictor = Ozone / 2, Temp_predictor = Temp / 2) %>%
select(date, everything(), -Month, -Day)
ui <- fluidPage(
# Title
titlePanel("New York AirQuality Measurements"),
# Input Selection used to build dataframe
sidebarLayout(
sidebarPanel(
selectInput(inputId = "target",
label = "Choose a prediction target for visualization",
choices = list("Ozone", "Ozone1", "Temp")
)
),
# Plot
mainPanel(
plotOutput("plot", height = "1200px")
)
)
)
server <- function(input, output) {
data <- reactive({
if(input$target == "Ozone"){
df %>%
select(-Ozone1, -contains("Temp")) %>%
tidyr::gather(key = key, value = value, -date)
} else if(input$target == "Ozone1"){
df %>%
select(-Ozone, -contains("Temp")) %>%
tidyr::gather(key = key, value = value, -date)
}else if (input$target == "Temp") {
df %>%
select(-contains("Ozone")) %>%
tidyr::gather(key = key, value = value, -date)
}
})
output$plot <- renderPlot({
ggplot(data(), aes(date, value)) +
geom_line() +
facet_wrap(key ~ ., scales = "free", ncol = 1) +
labs(y = "", x = "") +
theme_classic()
})
}
# Run the application
shinyApp(ui = ui, server = server)