The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.

shinypivottabler

The great pivottabler package enables pivot tables to be created with just a few lines of R.

The pivottabler package aims to:

• Provide an easy way of creating pivot tables, without requiring the user to specify low-level layout logic.
• Provide multiple ways of specifying calculation logic to cover both simple and more sophisticated requirements.
• Provide styling options so the pivot tables can be themed/branded as needed.

All calculations for the pivot tables take place inside R, enabling the use of a wide-range of R functions in the calculation logic, and are optimized with the use of packages dplyr & data.table

shinypivottabler just adds a simple and useful Shiny module to build, visualize, customize and export custom pivot tables.

shinypivottabler vs rpivotTable ?

The rpivotTable package is visualization library built around the Javascript pivottable library.

PivotTable.js is a Javascript Pivot Table library with drag’n’drop functionality built on top of jQuery/jQueryUI and written in CoffeeScript (then compiled to JavaScript) by Nicolas Kruchten at Datacratic. It is available under an MIT license

rpivotTable is really a great pivot table library with some really cool features such as :

• drag’n’ drop table definition
• lot of available aggregators
• possibility to print interactive charts

But it’s a full Javascript tool, and so all the data are sended to the client, and all computations are done on the client. So it’s not a good idea to use rpivotTable with a huge database.

No charts (yet…?) in shinypivottabler but :

• a full efficient R tool, on server-side
• possibility to add new aggregate functions
• possibility to combine two indicators
• output customization and excel export

Installation

You can install:

• the latest development version from GitHub with

devtools::install_github("datastorm-open/shinypivottabler")

Demo application

online

https://datastorm-demo.shinyapps.io/shinypivottabler/

local

runApp(system.file("demo_app", package = "shinypivottabler"))

Example

require(shinypivottabler)

n <- 10000000

# create artificial dataset
data <- data.frame("gr1" = sample(c("A", "B", "C", "D"), size = n,
                                 prob = rep(1, 4), replace = T),
                   "gr2" = sample(c("E", "F", "G", "H"), size = n,
                                 prob = rep(1, 4), replace = T),
                   "gr3" = sample(c("I", "J", "K", "L"), size = n,
                                 prob = rep(1, 4), replace = T),
                   "gr4" = sample(c("M", "N", "O", "P"), size = n,
                                 prob = rep(1, 4), replace = T),
                   "value1" = rnorm(n),
                   "value2" = runif(n))


server = function(input, output, session) {
  shiny::callModule(module = shinypivottabler,
                    id = "id",
                    data = data,
                    pivot_cols = c("gr1", "gr2", "gr3", "gr4"))
}

ui = shiny::fluidPage(
  shinypivottablerUI(id = "id")
)

shiny::shinyApp(ui = ui, server = server)


# more info in documentation : 
?shinypivottabler

• Define your pivot table

• Visualize & export

• Customize

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.