DataEditR

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An Interactive R Package for Viewing, Entering Filtering and Editing Data

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// repository documentation

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# DataEditR <img src="man/figures/logo.png" align="right" alt="" width="240"/>

[![Project Status: Active – The project has reached a stable, usable
state and is being actively
developed.](https://www.repostatus.org/badges/latest/active.svg)](https://www.repostatus.org/#active)
[![Lifecycle:
stable](https://img.shields.io/badge/lifecycle-stable-brightgreen.svg)](https://lifecycle.r-lib.org/articles/stages.html)
[![R build
status](https://github.com/DillonHammill/DataEditR/workflows/R-CMD-check/badge.svg)](https://github.com/DillonHammill/DataEditR/actions?workflow=R-CMD-check)
[![CRAN
status](https://www.r-pkg.org/badges/version/DataEditR)](https://CRAN.R-project.org/package=DataEditR)
[![CRAN_Download_Badge](https://cranlogs.r-pkg.org/badges/grand-total/DataEditR)](https://cran.r-project.org/package=DataEditR)

Manual data entry and editing in R can be tedious, especially if you
have limited coding experience and are accustomed to using software with
a Graphical User Interface (GUI). **DataEditR** is an R package built on
shiny and rhandsontable that makes it easy to interactively view, enter,
filter and edit data. If you are new to **DataEditR** visit
<https://dillonhammill.github.io/DataEditR/> to get started.

## Installation

**DataEditR** can be installed from CRAN:

``` r
install.packages("DataEditR")
```

The development version of **DataEditR** can be installed directly from
GitHub:

``` r
library(devtools)
install_github("DillonHammill/DataEditR")
```

## Usage

**DataEditR** ships with a series of shiny modules, namely `dataInput`,
`dataSelect`, `dataFilter`, `dataEdit`, `dataSync` and `dataOutput`
which have been wrapped up into a single function called `data_edit()`
to create an interactive data editor. You can use `data_edit()` as a
standalone application, or include the relevant modules within your own
shiny applications. A standalone `data_code()` function is also
available for generating tidyverse-style code from data edits.
Alternatively, `DataEditR` also ships with an RStudio add-in should you
prefer to interact with it in this way.

#### General features:

- RStudio add-in
- flexible display options (either `dialog` box, `browser` or RStudio
  `viewer` pane)
- fast rendering to quickly view datasets
- ability to interactively create data.frames from scratch
- load tabular data saved to file using any reading function
  (e.g. `read.csv()`)
- save edited data to file using any writing function
  (e.g. `write.csv()`)
- return appropriately formatted data as an R object for downstream use
- tidyverse-style code generation to reproduce edits using `dplyr` verbs
  (via `data_code()`)
- support for custom themes through `bslib` package
- customisable user interface (title, logo and modules)
- row indices are always displayed for easy navigation
- switch between datasets or files without having to leave the
  application

#### Data editing features:

- column selection using the `dataSelect` module
- row selection using the `dataFilter` module
- automatic synchronisation of edits to filtered or selected data
  subsets with the master dataset
- change tracking to visually highlight edited and added cells (`track`
  parameter)
- edit row or column names
- addition or removal of rows or columns
- manual column resizing
- drag to fill cells
- copy or paste data to and from external software
- custom column types to simplify user input (e.g. checkboxes and
  dropdown menus)
- support for readonly columns to prevent users from editing certain
  columns
- support for factor columns (automatically converted for editing)
- control over which column names can be edited
- stretch columns horizontally to fill available space
- programmatically add columns or rows to data prior to loading into the
  data editor

A quick demonstration of some of these features can be seen below, where
we use `data_edit()` to make changes to the `mtcars` dataset and save
the result to a new csv file:

``` r
# Load required packages
library(DataEditR)

# Save output to R object & csv file
mtcars_new <- data_edit(mtcars,
                        save_as = "mtcars_new.csv")
```

## Credits

**DataEditR** is built using the fantastic
[rhandsontable](https://github.com/jrowen/rhandsontable) package.
**DataEditR** makes use of many features for entering and editing data,
but **rhandsontable** has support for much more sophisticated
interactive representations of data should you need them. The user
interface of **DataEditR** has been inspired by the
[editData](https://github.com/cardiomoon/editData) package which is a
great alternative to **DataEditR**.

## Code of Conduct

Please note that the **DataEditR** project is released with a
[Contributor Code of
Conduct](https://contributor-covenant.org/version/2/0/CODE_OF_CONDUCT.html).
By contributing to this project, you agree to abide by its terms.

## Citation

If you use **DataEditR** in your work, please cite the package as
follows:

``` r
citation("DataEditR")
#> To cite package 'DataEditR' in publications use:
#> 
#>   Hammill D (2026). _DataEditR: An Interactive Editor for Viewing,
#>   Entering, Filtering & Editing Data_. R package version 1.0.0,
#>   <https://github.com/DillonHammill/DataEditR>.
#> 
#> A BibTeX entry for LaTeX users is
#> 
#>   @Manual{,
#>     title = {DataEditR: An Interactive Editor for Viewing, Entering, Filtering & Editing Data},
#>     author = {Dillon Hammill},
#>     year = {2026},
#>     note = {R package version 1.0.0},
#>     url = {https://github.com/DillonHammill/DataEditR},
#>   }
```

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