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Andreas Gammelgaard Damsbo 2025-04-14 11:18:24 +02:00
parent 9b966e9b9c
commit e980edc149
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6 changed files with 45 additions and 29 deletions
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2
R/app_version.R
View file

@ -1 +1 @@
app_version <- function()'Version: 25.4.2.250414_1007'
app_version <- function()'Version: 25.4.3.250414_1045'

2
R/helpers.R
View file

@ -378,9 +378,7 @@ data_type_filter <- function(data,type){
out <- data[data_type(data) %in% type]
code <- rlang::call2("data_type_filter",!!!list(type=type),.ns = "FreesearchR")
if (!is.null(code)){
attr(out, "code") <- code
}
out
}

30
inst/apps/FreesearchR/app.R
View file

@ -10,7 +10,7 @@
#### Current file: /Users/au301842/FreesearchR/R//app_version.R
########
app_version <- function()'Version: 25.4.2.250414_1007'
app_version <- function()'Version: 25.4.3.250414_1045'
########
@ -2737,9 +2737,7 @@ data_type_filter <- function(data,type){
out <- data[data_type(data) %in% type]
code <- rlang::call2("data_type_filter",!!!list(type=type),.ns = "FreesearchR")
if (!is.null(code)){
attr(out, "code") <- code
}
out
}
@ -8293,8 +8291,12 @@ ui_elements <- list(
shiny::tags$br(),
shiny::tags$br(),
shiny::uiOutput(outputId = "column_filter"),
shiny::helpText("Variable data type filtering."),
shiny::tags$br(),
shiny::tags$br(),
IDEAFilter::IDEAFilter_ui("data_filter"),
shiny::helpText("Observations level filtering."),
shiny::tags$br(),
shiny::tags$br()
)
),
@ -8312,8 +8314,8 @@ ui_elements <- list(
width = 9,
shiny::tags$p(
shiny::markdown("Below, are several options for simple data manipulation like update variables by renaming, creating new labels (for nicer tables in the report) and changing variable classes (numeric, factor/categorical etc.)."),
shiny::tags$p("There are also more advanced options to modify factor/categorical variables as well as create new factor from a continous variable or new variables with *R* code. At the bottom you can restore the original data."),
shiny::tags$p("Please note that data modifications are applied before any data or variable filtering is applied.")
shiny::markdown("There are also more advanced options to modify factor/categorical variables as well as create new factor from a continous variable or new variables with *R* code. At the bottom you can restore the original data."),
shiny::markdown("Please note that data modifications are applied before any data or variable filtering is applied.")
)
)
),
@ -8334,6 +8336,7 @@ ui_elements <- list(
),
shiny::tags$br(),
shiny::helpText("Reorder the levels of factor/categorical variables."),
shiny::tags$br()
),
shiny::column(
width = 4,
@ -8343,7 +8346,8 @@ ui_elements <- list(
width = "100%"
),
shiny::tags$br(),
shiny::helpText("Create factor/categorical variable from a continous variable (number/date/time).")
shiny::helpText("Create factor/categorical variable from a continous variable (number/date/time)."),
shiny::tags$br()
),
shiny::column(
width = 4,
@ -8353,11 +8357,11 @@ ui_elements <- list(
width = "100%"
),
shiny::tags$br(),
shiny::helpText(shiny::markdown("Create a new variable/column based on an *R*-expression."))
shiny::helpText(shiny::markdown("Create a new variable/column based on an *R*-expression.")),
shiny::tags$br()
)
),
shiny::tags$br(),
shiny::tags$br(),
tags$h4("Compare modified data to original"),
shiny::tags$br(),
shiny::tags$p(
@ -9047,8 +9051,9 @@ server <- function(input, output, session) {
# rv$data
), {
shiny::req(input$column_filter)
rv$data_variables <- data_type_filter(rv$data, input$column_filter)
rv$code <- modifyList(rv$code,list(variable=attr(rv$data_variables, "code")))
out <- data_type_filter(rv$data, input$column_filter)
rv$data_variables <- out
rv$code$variables <- attr(out, "code")
# rv$code$modify[[length(rv$code$modify) + 1]] <- attr(rv$data, "code")
})
@ -9167,10 +9172,13 @@ server <- function(input, output, session) {
})
output$code_variables <- shiny::renderUI({
prismCodeBlock(paste0("#Variables filter\n", rv$code$variables))
shiny::req(rv$code$variables)
out <- expression_string(rv$code$variables, assign.str = "df <- df |>\n")
prismCodeBlock(paste0("#Variables filter\n", out))
})
output$code_filter <- shiny::renderUI({
shiny::req(rv$code$filter)
prismCodeBlock(paste0("#Data filter\n", rv$code$filter))
})

2
inst/apps/FreesearchR/rsconnect/shinyapps.io/agdamsbo/freesearcheR.dcf
View file

@ -5,6 +5,6 @@ account: agdamsbo
server: shinyapps.io
hostUrl: https://api.shinyapps.io/v1
appId: 13611288
bundleId: 10098710
bundleId: 10111316
url: https://agdamsbo.shinyapps.io/freesearcheR/
version: 1

10
inst/apps/FreesearchR/server.R
View file

@ -371,8 +371,9 @@ server <- function(input, output, session) {
# rv$data
), {
shiny::req(input$column_filter)
rv$data_variables <- data_type_filter(rv$data, input$column_filter)
rv$code <- modifyList(rv$code,list(variable=attr(rv$data_variables, "code")))
out <- data_type_filter(rv$data, input$column_filter)
rv$data_variables <- out
rv$code$variables <- attr(out, "code")
# rv$code$modify[[length(rv$code$modify) + 1]] <- attr(rv$data, "code")
})
@ -491,10 +492,13 @@ server <- function(input, output, session) {
})
output$code_variables <- shiny::renderUI({
prismCodeBlock(paste0("#Variables filter\n", rv$code$variables))
shiny::req(rv$code$variables)
out <- expression_string(rv$code$variables, assign.str = "df <- df |>\n")
prismCodeBlock(paste0("#Variables filter\n", out))
})
output$code_filter <- shiny::renderUI({
shiny::req(rv$code$filter)
prismCodeBlock(paste0("#Data filter\n", rv$code$filter))
})

16
inst/apps/FreesearchR/ui.R
View file

@ -158,8 +158,12 @@ ui_elements <- list(
shiny::tags$br(),
shiny::tags$br(),
shiny::uiOutput(outputId = "column_filter"),
shiny::helpText("Variable data type filtering."),
shiny::tags$br(),
shiny::tags$br(),
IDEAFilter::IDEAFilter_ui("data_filter"),
shiny::helpText("Observations level filtering."),
shiny::tags$br(),
shiny::tags$br()
)
),
@ -177,8 +181,8 @@ ui_elements <- list(
width = 9,
shiny::tags$p(
shiny::markdown("Below, are several options for simple data manipulation like update variables by renaming, creating new labels (for nicer tables in the report) and changing variable classes (numeric, factor/categorical etc.)."),
shiny::tags$p("There are also more advanced options to modify factor/categorical variables as well as create new factor from a continous variable or new variables with *R* code. At the bottom you can restore the original data."),
shiny::tags$p("Please note that data modifications are applied before any data or variable filtering is applied.")
shiny::markdown("There are also more advanced options to modify factor/categorical variables as well as create new factor from a continous variable or new variables with *R* code. At the bottom you can restore the original data."),
shiny::markdown("Please note that data modifications are applied before any data or variable filtering is applied.")
)
)
),
@ -199,6 +203,7 @@ ui_elements <- list(
),
shiny::tags$br(),
shiny::helpText("Reorder the levels of factor/categorical variables."),
shiny::tags$br()
),
shiny::column(
width = 4,
@ -208,7 +213,8 @@ ui_elements <- list(
width = "100%"
),
shiny::tags$br(),
shiny::helpText("Create factor/categorical variable from a continous variable (number/date/time).")
shiny::helpText("Create factor/categorical variable from a continous variable (number/date/time)."),
shiny::tags$br()
),
shiny::column(
width = 4,
@ -218,11 +224,11 @@ ui_elements <- list(
width = "100%"
),
shiny::tags$br(),
shiny::helpText(shiny::markdown("Create a new variable/column based on an *R*-expression."))
shiny::helpText(shiny::markdown("Create a new variable/column based on an *R*-expression.")),
shiny::tags$br()
)
),
shiny::tags$br(),
shiny::tags$br(),
tags$h4("Compare modified data to original"),
shiny::tags$br(),
shiny::tags$p(