as.formula 函数调用,其中公式输入是闪亮的反应对象
as.formula function call where formula inputs are shiny reactive objects
这个问题困扰我很久了。
我有一个函数,其中第一个参数需要采用以下形式
function(data~ group_variable)
或 function(data, group = data$group_variable)
.
形式
我在控制台中顺利地使用了这个功能运行,但它是我闪亮的应用程序不可或缺的一部分,它已经困扰我很久了,因为数据和组都是用户选择的反应对象,所以它需要采用以下形式:
function(datasetInput() ~ !!input$group_variable)
或 其某些版本.
我没能找到 !!
s、enquo()
、substitute()
、as.function(substitute())
等的任何组合来使这项工作在闪亮的范围内进行应用程序。 as.Formula(substitute(data ~ group))
在控制台中工作。
这是我能做的最小的代表:
library(shiny)
library(shinyWidgets)
library(psych)
library(dplyr)
library(gt)
use <- function(name) {
# consider future support for .json?
if (grepl(".csv", name)) {
readr::read_csv(name)
} else if (grepl(".xlsx", name)) {
readxl::read_xlsx(name)
} else if (grepl(".dta", name)) {
haven::read_dta(name)
} else if (grepl(".sav", name)) {
haven::read_spss(name)
} else if (grepl(".rda", name)) {
load(name)
} else {
stop("unknown data type.")
}
}
ui <- fluidPage(
mainPanel(
fileInput("FileInput", "Input Your Data Set"),
helpText("Dataset must be one of: .csv, .sav, .dta, .xlsx, or .rda"),
materialSwitch(
inputId = "ext_desc",
label = "Extended Description",
value = FALSE,
status = "primary"
),
materialSwitch(
inputId = "desc_by_group_bool",
label = "Describe By A Group",
value = FALSE,
status = "primary"
),
varSelectInput(
inputId = "desc_group",
label = "Select A Group",
data = NULL,
width = "400px"
),
gt::gt_output("description")
)
)
server <- function(input,output, session){
datasetInput <- reactive({
infile <- input$FileInput
if (is.null(infile))
return(NULL)
dat<-use(infile$datapath)
names(dat) <- gsub(" ", "_", names(dat), fixed = TRUE)
return(dat)
})
observeEvent(datasetInput(), {
updateVarSelectInput(session, "desc_group", data = datasetInput())
})
desc <- reactive({
req(datasetInput())
if (input$desc_by_group_bool == FALSE) {
datasetInput() %>%
#select_if(is_numeric) %>%
psych::describe(., fast = !(input$ext_desc),
omit = TRUE) %>%
add_rownames(var = "Variable") %>%
dplyr::select(-c(vars)) %>%
dplyr::mutate(dplyr::across(is.numeric, round, 2)) %>%
gt::gt() %>%
gt::tab_options(
column_labels.font.size = "small",
table.font.size = "small",
row_group.font.size = "small",
data_row.padding = px(3)
) %>%
gt::tab_header(title = paste0("Data Description"))
} else {
# datasetInput() %>%
# select_if(is.numeric) %>%
psych::describeBy( datasetInput() ~ !!input$desc_group,
# here we get "invalid argument type" error
fast = !(input$ext_desc),
mat = TRUE) %>%
tibble::rownames_to_column() %>%
select(-c(item, vars)) %>%
dplyr::mutate(dplyr::across(is.numeric, round, 2)) %>%
arrange(group1) %>%
group_by(group1) %>%
gt() %>%
gt::tab_options(
column_labels.font.size = "small",
table.font.size = "small",
row_group.font.size = "small",
data_row.padding = px(3)
) %>%
tab_header(title = paste0("Data Description") ,
subtitle = paste0("Grouped by: ", input$desc_group)
)
}
})
output$description = gt::render_gt(desc())
}
shinyApp(ui = ui, server = server)
导致错误的行——以及我的问题的来源,请原谅,是上面的第 85 行。
我们有多种方法可以解决这个问题。一种方法是使用 [[]]
对特定列进行子集化。因此,将 describeBy
行更改为:
psych::describeBy( datasetInput(), group = datasetInput()[[input$desc_group]]
同时在dplyr::across
中添加where
dplyr::mutate(dplyr::across(where(is.numeric), round, 2))
这个问题困扰我很久了。
我有一个函数,其中第一个参数需要采用以下形式
function(data~ group_variable)
或 function(data, group = data$group_variable)
.
我在控制台中顺利地使用了这个功能运行,但它是我闪亮的应用程序不可或缺的一部分,它已经困扰我很久了,因为数据和组都是用户选择的反应对象,所以它需要采用以下形式:
function(datasetInput() ~ !!input$group_variable)
或 其某些版本.
我没能找到 !!
s、enquo()
、substitute()
、as.function(substitute())
等的任何组合来使这项工作在闪亮的范围内进行应用程序。 as.Formula(substitute(data ~ group))
在控制台中工作。
这是我能做的最小的代表:
library(shiny)
library(shinyWidgets)
library(psych)
library(dplyr)
library(gt)
use <- function(name) {
# consider future support for .json?
if (grepl(".csv", name)) {
readr::read_csv(name)
} else if (grepl(".xlsx", name)) {
readxl::read_xlsx(name)
} else if (grepl(".dta", name)) {
haven::read_dta(name)
} else if (grepl(".sav", name)) {
haven::read_spss(name)
} else if (grepl(".rda", name)) {
load(name)
} else {
stop("unknown data type.")
}
}
ui <- fluidPage(
mainPanel(
fileInput("FileInput", "Input Your Data Set"),
helpText("Dataset must be one of: .csv, .sav, .dta, .xlsx, or .rda"),
materialSwitch(
inputId = "ext_desc",
label = "Extended Description",
value = FALSE,
status = "primary"
),
materialSwitch(
inputId = "desc_by_group_bool",
label = "Describe By A Group",
value = FALSE,
status = "primary"
),
varSelectInput(
inputId = "desc_group",
label = "Select A Group",
data = NULL,
width = "400px"
),
gt::gt_output("description")
)
)
server <- function(input,output, session){
datasetInput <- reactive({
infile <- input$FileInput
if (is.null(infile))
return(NULL)
dat<-use(infile$datapath)
names(dat) <- gsub(" ", "_", names(dat), fixed = TRUE)
return(dat)
})
observeEvent(datasetInput(), {
updateVarSelectInput(session, "desc_group", data = datasetInput())
})
desc <- reactive({
req(datasetInput())
if (input$desc_by_group_bool == FALSE) {
datasetInput() %>%
#select_if(is_numeric) %>%
psych::describe(., fast = !(input$ext_desc),
omit = TRUE) %>%
add_rownames(var = "Variable") %>%
dplyr::select(-c(vars)) %>%
dplyr::mutate(dplyr::across(is.numeric, round, 2)) %>%
gt::gt() %>%
gt::tab_options(
column_labels.font.size = "small",
table.font.size = "small",
row_group.font.size = "small",
data_row.padding = px(3)
) %>%
gt::tab_header(title = paste0("Data Description"))
} else {
# datasetInput() %>%
# select_if(is.numeric) %>%
psych::describeBy( datasetInput() ~ !!input$desc_group,
# here we get "invalid argument type" error
fast = !(input$ext_desc),
mat = TRUE) %>%
tibble::rownames_to_column() %>%
select(-c(item, vars)) %>%
dplyr::mutate(dplyr::across(is.numeric, round, 2)) %>%
arrange(group1) %>%
group_by(group1) %>%
gt() %>%
gt::tab_options(
column_labels.font.size = "small",
table.font.size = "small",
row_group.font.size = "small",
data_row.padding = px(3)
) %>%
tab_header(title = paste0("Data Description") ,
subtitle = paste0("Grouped by: ", input$desc_group)
)
}
})
output$description = gt::render_gt(desc())
}
shinyApp(ui = ui, server = server)
导致错误的行——以及我的问题的来源,请原谅,是上面的第 85 行。
我们有多种方法可以解决这个问题。一种方法是使用 [[]]
对特定列进行子集化。因此,将 describeBy
行更改为:
psych::describeBy( datasetInput(), group = datasetInput()[[input$desc_group]]
同时在dplyr::across
where
dplyr::mutate(dplyr::across(where(is.numeric), round, 2))