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README.Rmd
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README.Rmd
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---
output: github_document
---
<!-- README.md is generated from README.Rmd. Please edit that file -->
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/",
out.width = "100%"
)
```
# DataEditR <img src="man/figures/logo.png" align="right" alt="" width="240"/>
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[](https://www.repostatus.org/#active)
[](https://lifecycle.r-lib.org/articles/stages.html)
[](https://github.com/DillonHammill/DataEditR/actions?workflow=R-CMD-check)
[](https://CRAN.R-project.org/package=DataEditR)
[](https://cran.r-project.org/package=DataEditR)
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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, eval = FALSE}
install.packages("DataEditR")
```
The development version of **DataEditR** can be installed directly from GitHub:
```{r, eval = FALSE}
library(devtools)
install_github("DillonHammill/DataEditR")
```
To ensure that `DataEditR` works as expected, you will also need to install my fork of `rhandsontable`:
```{r, eval = FALSE}
devtools::install_github("DillonHammill/rhandsontable")
```
## Usage
**DataEditR** ships with a series of shiny modules, namely `dataInput`, `dataSelect`, `dataFilter`, `dataEdit` 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. 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
- code required to create edited data can be optionally printed to the console or saved to a file
- 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
- 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
- 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, eval = FALSE}
# Load required packages
library(DataEditR)
# Save output to R object & csv file
mtcars_new <- data_edit(mtcars,
save_as = "mtcars_new.csv")
```
```{r, echo=FALSE, fig.align="center", out.width = '100%'}
knitr::include_graphics('https://raw.githubusercontent.com/DillonHammill/DataEditR/master/man/figures/DataEditR/DataEditR-README.gif')
```
## 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")
```