Editable DataTables for shiny apps.

Modularized version

Author: Jason Bryer, Ph.D. Email: [email protected]

Use the devtools package to install the development version of DTedit:

devtools::install_github('jbryer/DTedit')

The dtedit_demo will run a sample shiny app with to editable data tables.

DTedit::dtedit_demo()

Getting Started with DTedit

You can download a simple shiny app using DTedit here: inst/template/app.R

There are three steps to using DTedit in your shiny application.

1. Define callback function for inserting, updating, and deleting data.

my.insert.callback <- function(data, row) {
        # 'data' contains the dataframe *after* the row has been inserted/added
        # 'row' is the row number where data has been inserted
	return(data)
}

my.update.callback <- function(data, olddata, row) {
        # 'data' contains the dataframe *after* the row has been updated
        # 'row' is the row number where data has been updated
        # 'olddata' is the previous version of the data
	return(data)
}

my.delete.callback <- function(data, row) {
        # 'data' contains the dataframe *before* the row has been deleted
        # 'row' is the row number where data is to be deleted
	return(data[-c(row),])
}

Typically these functions would interact with a database. As written here, the data would be lost between shiny sessions.

2. Create the dtedit object within your server function.

return_values <- callModule(DTedit::dtedit,
	   id = 'mycontacts',
	   thedataframe = mydata,
	   edit.cols = c('name', 'email', 'useR', 'notes'),
	   edit.label.cols = c('Name', 'Email Address', 'Are they an R user?', 'Additional notes'),
	   input.types = c(notes='textAreaInput'),
	   view.cols = c('name', 'email', 'useR'),
	   callback.update = my.update.callback,
	   callback.insert = my.insert.callback,
	   callback.delete = my.delete.callback)

The input and output are passed from the server function. The id parameter will define the name of the object available to the dteditUI. The thedataframe is a data.frame for the initial view of the data table. This can be an empty (i.e. no rows) data.frame.

The structure of the data.frame will define the inputs (e.g. factor will be drop down, Date will use dateInput, numeric will use numericInput, etc.).

data.frame can be a reactivevalue, in which case dtedit's own internal copy of the data will change when data.frame changes. Note that the reactivevalue object itself is passed, not the value (i.e. don't use '()' after the reactivevalue variable name). There are many other parameters to customize the behavior of dtedit, see ?dtedit for the full list.

return_values is a list of reactivevalues. return_values$thedata() contains the current state of the DTedit's copy of the data. return_values$edit.count() contains the number of edits done within DTedit (not including changes to DTedit's copy of the data secondary to changes in thedataframe, if thedataframe is a reactivevalue).

3. Use DTedit::dteditUI in your UI to display the editable data table.

The id you will pass to dteditUI is the id you passed to the dtedit created on the server side.

dteditUI('mycontacts')