module-filterDF: Shiny module to interactively filter a 'data.frame'
In dtsonipmph/esquisse: Explore and Visualize Your Data Interactively

Description Usage Arguments Value Examples

Module generate inputs to filter data.frame according column's type. Code to reproduce the filter is returned as an expression with filtered data.

filterDF_UI(id, show_nrow = TRUE)

filterDF(
  input,
  output,
  session,
  data_table = reactive(),
  data_vars = shiny::reactive(NULL),
  data_name = reactive("data"),
  label_nrow = "Number of rows:",
  drop_ids = TRUE,
  picker = FALSE
)

`id`	Module id. See `callModule`.
`show_nrow`	Show number of filtered rows and total.
`input, output, session`	standards `shiny` server arguments.
`data_table`	`reactive` function returning a `data.frame` to filter.
`data_vars`	`reactive` function returning a `character` vector of variable to use for filters.
`data_name`	`reactive` function returning a `character` string representing `data_table` name.
`label_nrow`	Text to display before the number of rows of filtered data / source data.
`drop_ids`	Drop columns containing more than 90% of unique values, or than 50 distinct values.
`picker`	Use `shinyWidgets::pickerInput` instead of `shiny::selectizeInput` (default).

A list with 2 elements :

data_filtered : reactive function returning data filtered.
code : reactiveValues with 2 slots : expr (raw expression to filter data) and dplyr (code with dplyr pipeline).

if (interactive()) {
  
  library(shiny)
  library(shinyWidgets)
  library(ggplot2)
  library(esquisse)
  
  # Add some NAs to mpg
  mpg_na <- mpg
  mpg_na[] <- lapply(
    X = mpg_na,
    FUN = function(x) {
      x[sample.int(n = length(x), size = sample(15:30, 1))] <- NA
      x
    }
  )
  
  ui <- fluidPage(
    tags$h2("Filter data.frame"),
    
    radioButtons(
      inputId = "dataset", 
      label = "Data:",
      choices = c(
        "iris", "mtcars", "economics", 
        "midwest", "mpg", "mpg_na", "msleep", "diamonds",
        "faithfuld", "txhousing"
      ),
      inline = TRUE
    ),
    
    fluidRow(
      column(
        width = 3,
        filterDF_UI("filtering")
      ),
      column(
        width = 9,
        progressBar(
          id = "pbar", value = 100, 
          total = 100, display_pct = TRUE
        ),
        DT::dataTableOutput(outputId = "table"),
        tags$p("Code dplyr:"),
        verbatimTextOutput(outputId = "code_dplyr"),
        tags$p("Expression:"),
        verbatimTextOutput(outputId = "code"),
        tags$p("Filtered data:"),
        verbatimTextOutput(outputId = "res_str")
      )
    )
  )
  
  server <- function(input, output, session) {
    
    data <- reactive({
      get(input$dataset)
    })
    
    res_filter <- callModule(
      module = filterDF, 
      id = "filtering", 
      data_table = data,
      data_name = reactive(input$dataset)
    )
    
    observeEvent(res_filter$data_filtered(), {
      updateProgressBar(
        session = session, id = "pbar", 
        value = nrow(res_filter$data_filtered()), total = nrow(data())
      )
    })
    
    output$table <- DT::renderDT({
      res_filter$data_filtered()
    }, options = list(pageLength = 5))
    
    
    output$code_dplyr <- renderPrint({
      res_filter$code$dplyr
    })
    output$code <- renderPrint({
      res_filter$code$expr
    })
    
    output$res_str <- renderPrint({
      str(res_filter$data_filtered())
    })
    
  }
  
  shinyApp(ui, server)
  
}