shinyfilters

Overview

shinyfilters makes it easy to create Shiny inputs from vectors, data.frames, and more.

• filterInput(): Create filter inputs on any object
• updateFilterInput(): Update filter inputs
• serverFilterInput(): Server logic to update filter inputs
• apply_filters(): Apply filter inputs to objects

Installation

The latest release is available on CRAN:

# install.packages("pak")
pak::pak("shinyfilters")

Or, you can install the development version:

pak::pak("joshwlivingston/shinyfilters")

Usage

Vectors

library(shinyfilters)
library(shiny)

ui <- fluidPage(
    sidebarLayout(
        sidebarPanel(
            #############################################
            # Create a filterInput() inside a shiny app:
            filterInput(
                x = letters,
                id = "letter",
                label = "Pick a letter:"
            )
            #############################################
        ),
        mainPanel(
            textOutput("selected_letter")
        )
    )
)
server <- function(input, output, session) {
    output$selected_letter <- renderText({
        paste("You selected:", input$letter)
    })
}
shinyApp(ui, server)

Data.frames

library(shinyfilters)

library(DT)
library(shiny)

df <- data.frame(
    x = letters,
    y = sample(c("red", "green", "blue"), 26, replace = TRUE),
    z = round(runif(26, 0, 3.5), 2),
    q = sample(Sys.Date() - 0:7, 26, replace = TRUE)
)

ui <- fluidPage(
    sidebarLayout(
        sidebarPanel(
            #############################################################
            # 1. Create a filterInput() for each column in a data.frame:
            filterInput(
                x = df,
                range = TRUE,
                selectize = TRUE,
                slider = TRUE,
                multiple = TRUE
            )
            #############################################################
        ),
        mainPanel(
            DTOutput("df_full"),
            verbatimTextOutput("input_values"),
            DTOutput("df_filt")
        )
    )
)

server <- function(input, output, session) {
    output$df_full <- renderDT(datatable(df))
    ################################################################
    # 2. Create a server to manage the data.frame's filterInput()'s
    res <- serverFilterInput(
        x = df, 
        input = input, 
        range = TRUE
    )
    ################################################################
    
    #####################################################
    # 3. Use the server's results
    output$input_values <- renderPrint(res$input_values)
    output$df_filt <- renderDT(datatable(
        apply_filters(df, res$input_values)
    ))
    #####################################################
}

shinyApp(ui, server)

Extending shinyfilters

You can extend shinyfilters by adding or overwriting methods to the following:

• filterInput(), updateFilterInput()
• args_filter_input()
• get_filter_logical()

See vignette("customizing-shinyfilters") for more.